Financial Services

The online gaming industry has experienced tremendous growth in recent years, with millions of players engaging in immersive virtual worlds and competitive gameplay. Unfortunately, this surge in popularity has also sparked an increase in online gaming fraud. Unscrupulous individuals have sought to exploit the industry through fraudulent activities, leading to financial losses and reputational damage for gaming vendors.According to a recent study conducted by Lloyds Bank, children are spending more time playing online games than ever before – over five million children between the ages of three and 15 are now regularly playing games online, up from approximately 4.6 million in 2019.Fraudsters, always ready to take advantage of opportunities presented by new trends, are now increasingly targeting this rising demographic. Gaming vendors have a responsibility to shield minors from fraud in online gaming by implementing robust safety measures, educating young players and their parents, and actively monitoring and addressing fraudulent activities.   A vulnerable target That same study from Lloyds revealed that over a third (36%) of parents are concerned about the possibility of their children falling victim to gaming fraud and losing money. In today's tech-savvy world, the ease of payment authorization has only exacerbated these concerns. All it takes for a child to make a payment is to key in their parents' online store username and password. It is a practice fraught with danger. Parents can only do so much to safeguard their children while gaming, and despite their best efforts, there will always remain a lingering possibility of encountering scammers. Gaming vendors should establish robust age verification processes during account creation to ensure that minors are not exposed to age-inappropriate content. Additionally, they should incorporate comprehensive parental controls that allow parents to regulate their children's online activities, including chat limitations, spending controls, and access to certain features.But contrary to common assumptions, the gaming population is not restricted to teenagers or young adults. With an average age of 35, gamers have significant purchasing power and actively participate in the gaming ecosystem. They spend an average of over six hours per week gaming, dedicating nearly an hour each day to their preferred gaming experiences. This engagement is spread across all age groups and financial profiles, making the gaming community a vast market to attract cybercrime. Types of fraud in online gaming In 2022, the revenue from the worldwide gaming market was estimated at almost 347 billion U.S. dollars, with the mobile gaming market generating an estimated 248 billion U.S. dollars of the total. The gaming market is constantly evolving, and technological advancements are opening new possibilities for game developers to create more immersive and engaging experiences.But alarming reports indicate that scammers have honed in on the younger demographic of gamers, leveraging their innocence to exploit their finances and identities. Identity theft (67%) and hacking (61%) rank as the two most prevalent forms of fraud experienced by young gamers, according to the Lloyds Bank study. Here are some different types of online gaming fraud: Account hacking: Hackers employ various techniques like phishing, keylogging, and credential stuffing to gain unauthorized access to players' accounts. Once compromised, accounts could be used for fraudulent activities, including unauthorized in-game transactions or selling virtual assets for real money. Chargeback fraud: This occurs when players make legitimate purchases within a game using real money and then issue chargebacks, falsely claiming that the transaction was unauthorized or fraudulent. This results in financial losses for gaming vendors as they lose the revenue and virtual goods/services provided to the player. Virtual asset fraud: Virtual assets, such as in-game currency, items, or characters, hold economic value. Fraudsters engage in scams involving fake virtual asset transactions or market manipulation, exploiting players' desires to acquire rare or high-value items. Match-fixing and cheating: Competitive gaming is at the heart of many online games. Fraudsters seek to manipulate matches, exploit glitches, or use cheat software to gain an unfair advantage over others. This undermines the integrity of the gaming experience and discourages fair competition. The game changer for online platforms: fraud prevention strategies  Given the anticipated growth of these threats in the foreseeable future, it is imperative that online platforms prioritize the protection of young gamers and their parents. In line with the enhanced safeguards and anti-fraud initiatives observed in banks and financial institutions, it is high time for game companies to elevate their security and consumer protection measures by adopting the following guidelines: Implement strong account security measures: Encourage players to create unique, complex passwords, and consider implementing multifactor authentication solutions. Regularly educate players about common hacking techniques and promote safe browsing habits to prevent phishing attempts. Utilize fraud detection systems: Invest in advanced fraud detection tools that employ machine learning algorithms and biometrics templates to identify suspicious activities and patterns. These systems can flag potentially fraudulent transactions, allowing you to take appropriate measures promptly. Monitor and analyze user behavior: Keep an eye on players' activities and digital identity, such as unusual login patterns, high-value transactions, or frequent chargebacks. Analyze gameplay data, interactions, and purchasing behavior to identify patterns indicative of fraud or cheating. Secure payment processing systems: Choose reputable payment gateways that prioritize security measures. Employ tokenization and encryption technologies to safeguard players' payment information during transactions. Regularly test and update your payment system's security infrastructure. Raise player awareness: Educate your player community about common fraud techniques and the importance of securing their accounts with identity authentication. Share security tips through newsletters, blog posts, and in-game messaging. Foster a culture of vigilance and encourage players to report any suspicious activities. Foster fair gameplay and zero tolerance policy: Implement robust anti-cheat measures and regularly update your game to address vulnerabilities and exploits. Promote fair competition and enforce a zero-tolerance policy against cheating, match-fixing, and other forms of unfair gameplay. Leveling-up Ultimately, the ability to protect players online could be the ultimate gamechanger for gaming platforms. By embracing identity verification mechanisms that rely on secure and privacy-centric facial recognition, online fraud and identity theft can be significantly curtailed. Moreover, the verification and onboarding processes can be streamlined, simplifying the user experience further. Just as bringing top-tier games on board is crucial, game platforms must ensure their customers engage in a secure gaming environment. Streamlining the onboarding and sign-in process is essential to remain competitive. But how do you balance the need for speed and ease of use with essential ID checks? By combining the best data with our automated ID verification checks, Experian helps you safeguard your business and onboard customers efficiently. Using passive, invisible checks when customers sign into their accounts helps to keep fraudsters at bay and protects legitimate players without the need for irritating security challenges. Experian’s best-in-class solutions employ device recognition, behavioral biometrics, machine learning and global fraud databases to spot and block suspicious activity before it becomes a problem. Learn more *This article leverages/includes content created by an AI language model and is intended to provide general information.

While today’s consumers expect a smooth, frictionless digital experience, many financial institutions still rely on outdated technology and manual reviews to acquire new customers. These old processes can prevent lenders from making accurate and timely credit decisions, leading to lost opportunities, revenue, and goodwill. By optimizing their customer acquisition strategies, financial institutions can allocate their resources effectively and say yes to consumers faster. This guide will walk you through the current challenges facing customer acquisition and how robust optimization strategies can help. Current challenges in customer acquisition To stay competitive and engage high-value customers, you’ll need an efficient customer acquisition process that weeds out both fraudulent actors and risky consumers. However, achieving this balancing act comes with a unique set of challenges. Because today’s consumers can access goods and services almost anywhere online at any time, more than 54 percent of customers expect a heightened digital and frictionless experience. Failing to meet this expectation can lead to huge losses for lenders. Some of the most common challenges in customer acquisition include: Although 52 percent of consumers prefer digital banking options over visiting branches in person, many lenders still rely on paper documents, which can add weeks to the onboarding process. Requiring consumers to provide substantial information about themselves during an application process can lead to abandoned applications. 67 percent of consumers will leave an application if they experience complications. Verifying consumer identities is growing increasingly important. In fact, about 35 percent of customers drop out of digital onboarding because their identity can't be confirmed. Poorly defined campaign planning can cause businesses to market to the wrong population segments, resulting in wasted time and resources. What is optimization for customer acquisition?  Customer acquisition optimization is the process of implementing new methods and solutions to make acquiring new customers more efficient and cost-effective. For lenders, this means streamlining steps in the credit decisioning process to focus on the right prospects and reduce friction. What types of processes can be optimized for customer acquisition?  You might be surprised just how many processes can be optimized for customer acquisition. Here are just a few examples: Having a holistic view of consumers allows you to take the guesswork out of targeting so you can better identify and engage high-potential customers. Utilizing predictive and lifestyle data enables you to pinpoint a more precisely segmented audience for marketing. Digital application solutions that reach across multiple channels, allowing applicants to leave one channel and pick up right where they left off in another. Real-time identity verification and fraud detection during onboarding and after, helping expedite approvals and mitigate risks. Utilizing API integration to leverage multiple metrics beyond credit scores when screening applicants' financial situation. Building custom risk models that pair to your existing data so you can say yes to more customers and better manage portfolio risk. Benefits of customer acquisition optimization Optimization can bring numerous benefits to your business, providing a faster return on investment. Here are some examples. By better pinpointing your marketing through predictive and lifestyle data, you can achieve increased conversions. Faster onboarding with less friction helps retain more customers. Real-time fraud detection and identity verification reduce customer roadblocks, allowing you to realize significant growth. Custom risk models and decisioning platforms can pair your data with additional data elements, providing more than just a credit score rating for your applicants. This can help you say yes to more customers. Using AI and machine learning tools will reduce the need for manual reviews and thus increase booking rates and applications. A real-life example of these benefits can be found with the Michigan State University Federal Credit Union (MSUFCU.) With over $7.2 billion in assets and 330,000 members, the client was manually reviewing all its applications. Experian reviewed the client's risk levels and approvals, comparing their risk and bankruptcy scores to determine which were most predictive. This analysis led Experian to recommend a new decisioning platform (PowerCurve Originations®) for instant credit decisions, an alternative data score tool, and Experian Advisory Services for risk-based pricing. After implementing these optimization solutions, MSUFCU saw a 55 percent increase in average monthly automations, four times improved online application response time and began competing more effectively in the marketplace. How Experian can help Experian offers a number of customer acquisition tools, allowing companies to be more responsive in an increasingly competitive market, while still reducing fraud risk. These tools include: Acquisition optimization marketing Experian offers a web-based platform that lets clients manage their marketing efforts all in the same place. You can upload and enhance client files, identify lookalike prospects, and use firmographic and credit data to get a holistic view of your clients and your prospects. Data-driven acquisition and decisioning engine PowerCurve Originations® is a data-driven decisioning engine that accepts applications from multiple channels, automates data collection and verification and proactively monitors decision results. It's flexible enough to reach across multiple channels, letting customers set aside their application in one digital channel and resume where they left off in another. It also provides businesses with access to comprehensive data assets, proactive monitoring and streamlined development with minimal coding. Enhanced fraud detection and identity verification Experian's Precise ID® is a risk-based fraud detection and prevention platform that provides analytics to accurately verify customers and mitigate fraud loss behind the scenes, ensuring a smoother onboarding process. Robust consumer attributes for better customized models Experian gives clients access to a wider berth of consumer attributes, helping you better screen applicants beyond just looking at credit scores. Trended 3DTM attributes let you uncover unique patterns in consumers' behavior over time, allowing you to manage portfolio risk, build better models and determine the next best actions. Premier AttributesSM aggregates credit data at the most granular and meaningful levels to provide clear insights into consumer credit behavior. It encompasses more than 2,100 attributes across 51 industries to help you develop highly predictive custom models. Enterprise-wide credit decisioning engine Experian's enterprise-wide credit decision platform lets you combine machine learning with proprietary data to return optimized decisions and quickly respond to requests. Robust credit decisioning software lets you convert data into meaningful actions and strategies. With Experian's machine learning decisioning options, companies are realizing a 25 percent reduction in manual reviews, a 25 percent increase in loan and credit applications and a 26 percent increase in booking rates. Highly predictive custom models Experian's Ascend Intelligence ServicesTM can help you create highly predictive custom models that create sophisticated decisioning strategies, allowing you to accurately predict risk and make the best decisions fast. This end-to-end suite of solutions lets you achieve a more granular view of every application and grow portfolios while still minimizing risk. Experian can help optimize your customer acquisition Experian provides a suite of decisioning engines, consumer attributes and customized modeling to help you optimize your customer acquisition process. These tools allow businesses to better target their marketing efforts, streamline their onboarding with less friction and improve their fraud detection and mitigation efforts. The combination can deliver a powerful ROI. Learn more about Experian's customer acquisition solutions. Learn more

Fraud is a serious concern for everyone, including businesses and individuals. In fact, according to our 2023 U.S. Identity and Fraud Report, nearly two-thirds (64%) of consumers are very or somewhat concerned with online security, and over 50% of businesses have a high level of concern about fraud risk. The fraud landscape is constantly evolving, and staying vigilant against the latest trends is critical to safeguarding your organization and consumers. As we reflect on 2023, let’s look at the top fraud trends and their continued potential impact on your business. The evolution of new fraud trends When economic uncertainty reigns, a rise in fraud often follows. To begin with, consumers tend to be financially stressed in such periods and prone to making risky decisions. In addition, fraudsters are keenly aware of the opportunities inherent in unstable times and develop tactics to take advantage of them. For example, as consumers rein in spending and financial institutions struggle to maintain new account volumes, fraudsters might ramp up their new account and loan activities. Fraud is becoming more sophisticated. For instance, thanks to the rapid rise in the availability of artificial intelligence (AI) tools, fraudsters are increasingly able to impersonate companies and individuals with ease, as well as consolidate data from diverse sources and use it more efficiently. The most impactful fraud trends of 2023 The fraud trends that emerged in 2023 were diverse, though they all had one thing in common: fraudsters' keen ability to take advantage of new technologies and opportunities. And businesses are feeling the repercussions, with nearly 70% reporting that fraud losses have increased in recent years. Here are five trends we forecasted in the fraud and identity space that challenged fraud fighters on the front lines this year. Deposit and checking account fraud With everyone focused on fraud in the on-line channels, it is interesting that financial institutions reported more fraud occurring at brick-and-mortar locations. Preying on the good nature of helpful branch employees, criminals are taking risks by showing up in person to open accounts, pass bad deposits and try to work their way into other financial products.  The Treasury Department reports complaints doubling YoY, after increasing more than 150% between 2020 and 2021.  Synthetic identity fraud Not quite fake, not quite real, so-called synthetic or "Frankenstein" identities mash up real data with false information to create unique customer profiles that can outsmart retailers' or financial institutions' fraud control systems. With synthetic identity (SID) fraud real data is often stolen or purchased on the dark web and combined with other information — even Artificial Intelligence (AI)-created faces — so that fraudsters can build up a synthetic identity's credit score before taking advantage of them to borrow and spend money that will never be paid back. One major risk? As fraud rates rise due to the use of tactics like synthetic identities, it could become more challenging and expensive to access credit. Fake job postings and mule schemes Well-paying remote work was in high demand this year, creating opportunities for fraudsters to create fake jobs to harvest data such as Social Security numbers from unsuspecting applicants. Experian also predicts a continued rise in "mule" jobs, in which workers unknowingly sign on to do illegal work, such as re-shipping stolen goods. According to the Better Business Bureau, an estimated 14 million people get caught in a fake employment scam yearly. Job seekers can protect themselves by being skeptical of jobs that ask them to do work that appears suspicious, requires money, financial details, or personal information upfront. Peer-to-peer payment fraud Peer-to-peer payment tools are increasingly popular with consumers and fraudsters, who appreciate that they're both instant and irreversible. Experian expects to continue to see an increase in fraudulent activity on these payment systems, as fraudsters use social engineering techniques to deceive consumers into paying for nonexistent merchandise or even sharing access credentials. Stay safe while using peer-to-peer payment tools by avoiding common scams like requests to return accidental payments, opting for payment protection whenever possible and choosing other transaction methods like paying with a credit card. Social media shopping fraud Social media platforms are eager to make in-app shopping fun and friction-free for consumers — and many brands and shoppers are keen to get on board. In fact, approximately 58% of users in the U.S. have purchased a product after seeing it on social media. Unfortunately, these tools neglect effective identity resolution and fraud prevention, leaving sellers vulnerable to fraudulent purchases. And while buyers have some recourse when a purchase turns out to be a scam, it's wise to be cautious while shopping on social media platforms by researching sellers, only using credit cards and being cognizant of common scams, like when vendors on Facebook Marketplace ask for payment upfront. Employer text fraud Fraudulent text messages — also known as “smishing,” a mash-up of Short Messaging Service (SMS) and phishing — continues to rise. In fact, according to data security company Lookout, 2022 was the biggest year ever for such mobile phishing attacks, with more than 30 percent of personal and enterprise mobile phone users exposed every quarter. One modern example of these types of schemes? Expect to continue to see a rise in gift card fraud targeting companies. For example, an employee might receive a text from their "boss" asking them to purchase gift cards and relay the numbers. The fraudsters get to shop, and the company is left with the bill. Why fraud prevention and detection solutions matter Nearly two-thirds of consumers say they are "very" or "somewhat concerned" with online security, and more than 85 percent expect businesses to respond to their identity and fraud concerns. Addressing and preventing fraud — and communicating these fraud-prevention actions to customers — is an essential strategy for businesses that want to maintain customer trust, thereby decreasing churn and maximizing conversions on new leads. There's a financial imperative to address fraud as well. Businesses stand to lose a great deal of money without adequate fraud prevention strategies. Account takeover fraud, for example, is an increasing threat to financial institutions, which saw a 90 percent increase in account takeover losses from 2020 to 2021. By making account takeover fraud prevention a priority, financial institutions can alleviate risks and prevent major losses. How to build an effective fraud strategy in 2024 In 2024, fraud management solutions must be even more technically advanced than the fraudulent techniques they're combating. But more than that, they need to be appealing to consumers, who are likely to abandon signup or purchase attempts when they become too onerous. In fact, 37% of consumers have moved their business elsewhere due to a negative account opening experience. Worryingly for businesses, this number was even higher among high-income households and those aged 25 to 39. To succeed, effective fraud strategies must be seamless, low friction, data-driven and customer-focused. That means making use of up-to-date technologies that boost security while prioritizing a positive customer experience.  Concerned about fraud? Let Experian help As we look back at the top fraud trends of 2023, it's clear that scammers are becoming increasingly sophisticated in their methods. Fraud can create huge risks for your business — but there are ways to act. Experian's suite of fraud prevention and identity verification tools can help you detect and combat fraud. Find out more about Experian's fraud risk management strategies and how they can help keep you and your customers safe. Learn more

Financial institutions are under increasing pressure to grow deposits and onboard more demand deposit accounts (DDA). But as demand increases, so do fraud attempts from scammers. While a robust mitigation effort is needed to stop fraud, this same effort can also drive away potential clients. In fact, 37 percent of U.S. adults said that they abandoned opening an account online due to experiencing friction. This leaves institutions in a unique quandary: how do they stop DDA fraud without scaring away potential clients? The answer lies in utilizing robust, machine learning tools that can help you navigate fraud attempts without increasing onboarding friction.  Chris Ryan, Go to Market Lead for Experian Identity and Fraud, shares his thoughts on demand deposit account fraud and which decisioning tools can best combat it.   Q: What is a demand deposit account and how is it used? "Demand deposit is just your basic checking account," Ryan explains." The funds are deposited and held by an institution, which enables you to spend those assets or resources, whether it be through checks, debit cards, person-to-person, Automated Clearing House (ACH) — all the things we do every day as consumers to manage our operating budget."  Q: What is demand deposit account fraud?   "There are two different ways that demand deposit account fraud works," Ryan says. "One is with existing account holders, and the other is with the account opening process.” When fraud affects existing account holders, it typically involves tricking an account holder into sending money to a scammer or using fraudulent actions, like phishing emails or credit card skimmers, to gain access to their accounts. There is also a resurgence in fraud involving duplication, theft and forgery of paper checks, Ryan explains.   Fraud impacting the account opening process occurs when scammers originate new DDAs. This can work in a variety of ways, such as these three examples:  A scammer steals your identity and opens an account at the same bank where you have a home equity loan. They link their DDA to your line of credit, transferring your money into their new account and withdrawing the funds.  A scammer uses a synthetic identity (SID) to open a fraudulent DDA. They will then use this new DDA to open more lucrative accounts that the institution cross-sells to them. A scammer uses a stolen or SID to open “mule” accounts to receive funds they dupe consumers into sending through fake relationship schemes, bogus merchandise sales and dozens of similar scams. While both types of fraud need to be dealt with, account opening fraud can have especially large repercussions for lenders or financial institutions.  Q: What are the consequences of DDA fraud for organizations?   "Fraud hurts in a number of ways," Ryan explains. "There are direct losses, which is the money that criminals take from our financial system. Under most circumstances, the financial institution replaces the money, so the consumer doesn’t absorb the loss, but the money is still gone. That takes money away from lending, community engagement and other investments we want banks to make. The direct losses are what most people focus on."  But there are even more repercussions for institutions beyond losing money, and this can include the attempts that institutions put into place to stop the fraud. "Preventing fraud requires some friction for the end consumer," Ryan says. "The volume of fraudulent attempts is overwhelmingly large in the DDA space. This forces institutions to apply more friction. The friction is costly, and it often drives would-be-customers away. The results include high costs for the institutions and low booking rates. At the same time, institutions are hungry for deposit money right now. So, it's kind of a perfect storm."  Q: What is the impact of DDA fraud on customer experience?  Experian’s 2023 Identity and Fraud Report revealed that up to 37 percent of U.S. adults in the survey had abandoned a new account entirely in the previous six months because of the friction they encountered during onboarding. And 51 percent reported considering abandoning the process because of problems they encountered. Unfortunately, fraud mitigation and deposit fraud detection efforts can end up driving customers away. "People can be impatient," Ryan says, "and in the online world, a competing product is a mouse-click away. So, while it is tempting to ask new applicants for more information, or further proof of identity, that conflicts with their need for convenience and can impact their experience.” Companies looking for cheap and fast mitigation can end up impeding customers trying to onboard to sweep out the bad actors, Ryan explains. "How do you get the bad people without interrupting the good people?" Ryan asks. "That's the million-dollar question."  Q: What are some other problems with how organizations traditionally combat DDA fraud?   Unfortunately, traditional attempts to combat DDA fraud are inefficient due to the fragmentation of technology. Ryan says this was revealed by Liminal, an industry analyst think tank.  "Nearly half of institutions use four-or-more-point solutions to manage identity and fraud-related risk," Ryan explains. "But all of those point solutions were meant to work on their own. They weren't developed to work together. So, there's a lot of overlap. And in the case of fraud, there's a high likelihood that the multiple solutions are going to find the same fraud. So, you create a huge inefficiency."   To solve this challenge, institutions need to shift to integrated identity platforms, such as Experian CrossCore®.  Q: How is Experian trying to change the way organizations approach DDA fraud?   Experian is pushing a paradigm shift for institutions that will increase fraud detection efficiency and accuracy, without sacrificing customer experience. "Organizations need to start thinking of identity through a different lens," Ryan says.   Experian has developed an identity graph that aggregates consumer information in a manner that reaches far beyond what an institution can create on its own. "Experian is able to bring the entire breadth of every identity presentation we see into an identity graph," Ryan says. "It's a cross-industry view of identity behavior." This is important because people who commit fraud manipulate data, and those manipulations can get lost in a busy marketplace.   For example, Ryan explains, if you're newly married, you may have recently presented your identity using two different surnames: one under your maiden name and one under your married name. Traditional data sources may show that your identity was presented twice, but they won’t accurately reflect the underlying details; like the fact that different surnames were used. The same holds true for thousands of other details seen at each presentation but not captured in a way that enables changes over time to be visible, such as information related to IP addresses, email accounts, online devices, or phone numbers.   "Our identity graph is unlocking the details behind those identity presentations," Ryan says. "This way, when a customer comes to us with a DDA application, we can say, 'That's Chris's identity, and he's consistently presenting the same information, and all that underlying data remains very stable.'"   This identity graph, part of Experian's suite of fraud management solutions — also connects unique identity details to known instances of fraud, helping catch fraudulent attempts much faster than traditional methods. "Let's say you and your spouse share an address, phone numbers, all the identity details that married couples typically share," Ryan explains. "If an identity thief steals your identity and uses it along with a brand-new email and IP address not associated with your spouse, that might be concerning. However, perhaps you started a new job, and the email/IP data is legitimate. Or maybe it’s a personal email using a risky internet service provider that shares a format commonly used by a known ring of identity thieves. Traditional data might flag the email and IP information as new, but our identity graph would go several layers deeper to confirm the possible risks that the new information brings.  Q: Why is this approach superior to traditional methods of fraud detection?  "Historically, organizations were interested in whether an identity was real,” Ryan says. "The next question was if the provided data (I.e., addresses, date of birth, Social Security numbers, etc.) have been historically associated with the identity. Last, the question would be whether there’s known risk associated with any of the identity components.” The identity graph turns that approach upside down.   "The identity graph allows us to pull in insights from past identity presentations, " Ryan says. "Maybe the current presentation doesn’t include a phone number. Our identity graph should still recognize previously provided phone numbers and the risks associated with them. Instead of looking at identity as a small handful of pieces of data that were given at the time of the presentation, we use the data given to us to get to the identity graph and see the whole picture."  Q: How are businesses applying this new paradigm?  The identity graph is part of Experian's Ascend Fraud Platform™ and a full suite of fraud management solutions. Experian's approach allows companies to clean out fraud that already occurred and stop new fraudulent actors before they're onboarded. "Ideally, you want to start with cleaning up the house, and then figure out how to protect the front door," Ryan says.  In other words, institutions can start by applying this view to recently opened accounts to identify problematic identities that they missed. The next step would be to bring these insights into the new account onboarding process.  Q: Is this new fraud platform accessible to both small and large businesses?  The Ascend Fraud Platform will support several use cases that will bring value to a broad range of businesses, Ryan explains. It can not only enable Experian experts to build and deliver better tools but can enable self-serve analytical development too. "Larger organizations that have robust, internal data science capabilities will find that it’s an ideal environment for them to work in," Ryan says. "They can add their own internal data assets to ours, and then have a better place to develop analytics. Today, organizations spend months assembling data to develop analytics internally. Our Ascend Fraud Platform will reduce the timeline of the data assembly and analytical development process to weeks, and speed to market is critical when confronting continually changing fraud threats. "But for customers who have less robust analytical teams, we're able to do that on their behalf and bring solutions out to the marketplace for them," Ryan explains.   Q: What type of return on investment (ROI) are businesses experiencing?  "Some customers recover their investment in days," Ryan says. "Part of this is from mitigating fraud risks among recently opened accounts that slipped through existing defenses.”     "In addition to reducing losses, institutions we're working with are also seeing potentially millions of dollars a month in additional bookings, as well as significant cost savings in their account opening processes," Ryan says.  "We're able to help clients go back and audit the people who had fallen out of their process, to figure out how to fine-tune their tools to keep those people in," Ryan says.   “By reducing risks among existing accounts, better protecting the front door against future fraud, and growing more efficiently, we’re helping clients  Q: What are Experian's plans for this service?   "We're working with top-tier financial institutions on the do-it-yourself techniques," Ryan says. "In parallel, we're launching our first offerings that are created for the broader marketplace. That will start with the portfolio review capability, along with making the most predictive attributes available through our integrated identity resolution platform. And while the Ascend Fraud Platform has a strong use case for DDA fraud, its uses extend beyond that to small business lending and other products. In fact, Experian offers an entire suite of fraud management solutions to help keep your DDA accounts secure and your customers happy.   Experian can help optimize your DDA fraud detection  Experian is revolutionizing the approach to combating DDA fraud, helping institutions create a faster onboarding process that retains more customers, while also stopping more bad actors from gaining access. It's a win-win for everyone.   Experian's full suite of fraud management solutions can optimize your business's DDA fraud detection, from scrubbing your current portfolio to gatekeeping bad actors before they're onboarded.  Learn more Speak with a specialist About our expert: Chris Ryan has over 20 years of experience in fraud prevention and uses this knowledge to identify the most critical fraud issues facing individuals and businesses in North America, and he guides Experian’s application of technology to mitigate fraud risk.

In today's fast-paced digital world, the risk of fraud across all industries is a constant threat. The traditional methods of fraud detection are no longer sufficient, as fraudsters become increasingly sophisticated in their attacks. However, with artificial intelligence (AI) and machine learning (ML) solutions, financial institutions can stay one step ahead of fraudsters. AI and machine learning-equipped fraud detection tools have the ability to identify suspicious activity and patterns of fraud that are imperceptible to the human brain. In this blog post, we’ll dive into the significance of AI and machine learning in fraud detection and how these solutions are uniquely equipped to handle the demands of modern-day risk management. Understanding artificial intelligence and machine learning AI and machine learning solutions are transformative technologies that are reshaping the landscape of many industries. AI, at its core, is a field of computer science that simulates human intelligence in machines, enabling them to learn from experience and perform tasks that normally require human intellect. Machine learning, a subset of AI, is the science of getting computers to learn and act like humans do, but with minimal human intervention. They can analyze vast amounts of data within seconds, identifying patterns and trends that would be impossible for a human to recognize. When it comes to fraud detection, this ability is invaluable.  Advantages of fraud detection using machine learning AI and machine learning have several benefits that make them valuable in fraud detection. One significant advantage is that these technologies can recognize patterns that are too complex for humans to identify. By running through a vast set of data points, these solutions can pinpoint anomalous behavior, and thereby prevent financial losses. AI analytics tools are adept at monitoring complex networks, detecting the dispersion of attacks that may involve multiple individuals and entities, and correlating activity patterns that would otherwise be hidden. Machine learning algorithms can take these patterns and turn them into mathematical models that help identify instances of fraud before the damage takes place. Secondly, they continuously learn from new data, which allows them to become more efficient in identifying fraud as they process more data. Thirdly, they automate fraud mitigation processes, which significantly reduces the need for manual interventions that may consume valuable time and resources. Another significant benefit of machine learning is its analytics capabilities, which allow organizations to gain valuable insights into customer behavior and fraud patterns. With AI analytics, they can detect and investigate fraudulent activities in real-time, and combine it with other tools to help detect and mitigate fraud risk. For example, in financial services, AI fraud detection can help banks and financial service providers detect and prevent fraud in their systems, add value to their services and improve customer satisfaction. The future of fraud detection and machine learning The rate at which technology is evolving means that machine learning and AI fraud detection will become increasingly important in the future. In the next few years, we can expect a more sophisticated level of fraud detection using unmanned machine systems, robotics process automation, and more. Ultimately, this will improve the efficiency and effectiveness of fraud detection.AI-based fraud management solutions are taking center stage. Organizations must leverage advanced machine learning and AI analytics solutions to prevent and mitigate cyber risks and comply with regulatory mandates. The benefits extend far beyond the financial bottom line to improving the safety and security of customers. AI and machine learning solutions offer accurate, efficient and proactive routes to managing the risk of fraud in an ever-changing environment. How can Experian® help Integrating machine learning for fraud detection represents a significant advancement in cybersecurity. Fraud management solutions detect, prevent and manage fraud across all industries, including financial services, healthcare and telecommunications. With the advancement of technology, fraud management solutions now integrate machine learning to improve their processes. Experian® provides fraud prevention solutions, including machine learning models and AI analytics, which can help more effectively mitigate fraud risk, streamline fraud investigations and create a more secure digital environment for all. With Experian’s AI analytics, risk mitigation tools and fraud management solutions, organizations can stay one step ahead of fraudsters and protect their brand reputation, customer trustworthiness and corporate data. Embracing these solutions can save organizations from significant losses, reputational damage and regulatory scrutiny. To learn more about how to future-proof your business and safeguard your customers from fraud, check out Experian’s robust suite of fraud prevention solutions. Want to hear what our industry experts think? Check out this on-demand webinar on artificial intelligence and machine learning strategies. *This article includes content created by an AI language model and is intended to provide general information.

Today's lenders use expanded data sources and advanced analytics to predict credit risk more accurately and optimize their lending and operations. The result may be a win-win for lenders and customers. What is credit risk? Credit risk is the possibility that a borrower will not repay a debt as agreed. Credit risk management encompasses the policies, tools and systems that lenders use to understand this risk. These can be important throughout the customer lifecycle, from marketing and sending preapproved offers to underwriting and portfolio management. Poor risk management can lead to unnecessary losses and missed opportunities, especially because risk departments need to manage risk with their organization's budgetary, technical and regulatory constraints in mind. How is it assessed?  Credit risk is often assessed with credit risk analytics — statistical modeling that predicts the risk involved with credit lending. Lenders may create and use credit risk models to help drive decisions. Additionally (or alternatively), they rely on generic or custom credit risk scores: Generic scores: Analytics companies create predictive models that rank order consumers based on the likelihood that a person will fall 90 or more days past due on any credit obligation in the next 24 months. Lenders can purchase these risk scores to help them evaluate risk. Custom scores: Custom credit risk modeling solutions help organizations tailor risk scores for particular products, markets, and customers. Custom scores can incorporate generic risk scores, traditional credit data, alternative credit data* (or expanded FCRA-regulated data), and a lender's proprietary data to increase their effectiveness. About 41 percent of consumer lending organizations use a model-first approach, and 55 percent use a score-first approach to credit decisioning.1 However, these aren't entirely exclusive groupings. For example, a credit score may be an input in a lender's credit risk model — almost every lender (99 percent) that uses credit risk models for decisioning also uses credit scores.2 Similarly, lenders that primarily rely on credit scores may also have business policies that affect their decisions. What are the current challenges? Risk departments and teams are facing several overarching challenges today: Staying flexible: Volatile market conditions and changing consumer preferences can lead to unexpected shifts in risk. Organizations need to actively monitor customer accounts and larger economic trends to understand when, if, and how they should adjust their risk policies. Digesting an overwhelming amount of data: More data can be beneficial, but only if it offers real insights and the organization has the resources to understand and use it efficiently. Artificial intelligence (AI) and machine learning (ML) are often important for turning raw data into actionable insights. Retaining IT talent: Many organizations are trying to figure out how to use vast amounts of data and AI/ML effectively. However, 82 percent of lenders have trouble hiring and retaining data scientists and analysts.3 Separating fraud and credit losses: Understanding a portfolio's credit losses can be important for improving credit risk models and performance. But some organizations struggle to properly distinguish between the two, particularly when synthetic identity fraud is involved. Best practices for credit risk management Leading financial institutions have moved on from legacy systems and outdated risk models or scores. And they're looking at the current challenges as an opportunity to pull away from the competition. Here's how they're doing it: Using additional data to gain a holistic picture: Lenders have an opportunity to access more data sources, including credit data from alternative financial services and consumer-permissioned data. When combined with traditional credit data, credit scores, and internal data, the outcome can be a more complete picture of a consumer's credit risk. Implementing AI/ML-driven models: Lenders can leverage AI/ML to analyze large amounts of data to improve organizational efficiency and credit risk assessments. 16 percent of consumer lending organizations expect to solely use ML algorithms for credit decisioning, while two-thirds expect to use both traditional and ML models going forward.4 Increasing model velocity: On average, it takes about 15 months to go from model development to deployment. But some organizations can do it in less than six.5 Increasing model velocity can help organizations quickly respond to changing consumer and economic conditions. Even if rapid model creation and deployment isn't an option, monitoring model health and recalibrating for drift is important. Nearly half (49 percent) of lenders check for model drift monthly or quarterly — one out of ten get automated alerts when their models start to drift.6 WATCH: Accelerating Model Velocity in Financial Institutions Improving automation and customer experience Lenders are using AI to automate their application, underwriting, and approval processes. Often, automation and ML-driven risk models go hand-in-hand. Lenders can use the models to measure the credit risk of consumers who don't qualify for traditional credit scores and automation to expedite the review process, leading to an improved customer experience. Learn more by exploring Experian's credit risk solutions. Learn more * When we refer to “Alternative Credit Data," this refers to the use of alternative data and its appropriate use in consumer credit lending decisions as regulated by the Fair Credit Reporting Act (FCRA). Hence, the term “Expanded FCRA Data" may also apply in this instance and both can be used interchangeably. 1-6. Experian (2023). Accelerating Model Velocity in Financial Institutions

Well-designed underwriting strategies are critical to creating more value out of your member relationships and driving growth for your business. But what makes an advanced underwriting strategy? It’s all about the data, analytics, and the people behind it. How a credit union achieved record loan growth Educational Federal Credit Union (EdFed) is a member-owned cooperative dedicated to serving the financial needs of school employees, students, and parents within the education community. After migrating to a new loan origination system, the credit union wanted to design a more profitable underwriting strategy to increase efficiency and grow their business. EdFed partnered with Experian to design an advanced underwriting strategy using our vast data sources, advanced analytics, and recommendations for greater automation. After 30 months of implementing the new loan origination system and underwriting strategies, the credit union increased their loans by 32% and automated approvals by 21%. “The partnership provided by Experian, backed by analytics, makes them the dream resource for our growth as a credit union. It isn’t just the data… it’s the people.” – Michael Aubrey, SVP Lending at Educational Federal Credit Union Learn more about how Experian can help you enhance your underwriting strategy. Learn more

It's that magical time of the year! The holiday season is fast approaching, and folks everywhere are gearing up for festive travels and family reunions. Unfortunately, holiday travel can sometimes lead to unforeseen circumstances, such as fraudulent activities orchestrated by scammers who impersonate property owners on well-known vacation rental platforms. These fraudsters employ schemes designed to deceive unsuspecting travelers into making payments through unsecured channels, resulting in significant financial losses for the gullible victims.  Digital identity and hotel fraud Airline and hotel fraud encompasses illicit activities aimed at airlines, hotels, booking platforms, and other travel accommodation services, including car rentals and excursions. These services often utilize loyalty programs to incentivize repeat patronage through point-based rewards. The widespread adoption of such loyalty programs has extended their appeal beyond the travel and hospitality sectors, consequently attracting fraudulent activities. Perpetrators of airline and hospitality fraud employ a range of tactics and different techniques to execute their schemes, leveraging various online forums, marketplaces, shops, and public messaging platforms. Hotels are custodians of valuable guest data, encompassing contact information and payment details. Their operational model involves serving a large pool of potential customers who are making limited visits. Consequently, compromising a hospitality employee's account could grant an identity thief access to millions of consumer records. Moreover, hotel employees are frequent targets of foreign governments aiming to procure confidential travel records to facilitate the tracking of specific individuals and groups. In contrast, restaurants primarily store transaction records with fewer customer details. However, the landscape is evolving as more establishments adopt online ordering capabilities and loyalty programs. At present, cybercriminals typically focus on the high volume of point-of-sale transactions.  As travel booms, fraudsters find new paths According to a recent Deloitte survey, Intent to travel between Thanksgiving and mid-January is up across all age and income groups. While reconnecting with friends and family remains paramount to travel during the holidays, fewer Americans are restricting their travel to visiting loved ones. The share of travelers planning to stay in hotels surged to 56%. Fraudsters will always take advantage of current circumstances, and with more people traveling again, they have taken notice — and action. The following techniques have been identified as the most employed by cybercriminals to target customers of airlines, hotels, and hospitality-related organizations:  Travel-themed phishing and fraudulent travel agency operations, sales, and advertisements of travel fraud-related tutorials.  Sales of compromised networks, user accounts, and databases containing reward/loyalty points and personally identifiable information (PII) that could be utilized for social engineering, money laundering, and other attack vectors.  Since the emergence of cyber-enabled crime, services and activities facilitating travel fraud have been extensively promoted and sought after by threat actors. Cybercriminals mainly leverage stolen card-not-present (CNP) data and reward/loyalty points obtained from compromised bank accounts to procure flights, accommodations, and other travel-related services.  Furthermore, threat actors persistently refine their strategies for harvesting reward/loyalty points through compromised accounts, deceiving victims into disclosing their travel-related documentation and data and circulating updated guidelines for circumventing hotel and airline reservation services, amongst other activities.  Protecting travelers and improving the customer experience   Combatting hospitality and hotel fraud requires collaboration between industry stakeholders, government entities, and financial institutions. Travel professionals should focus on: Enhancing data security: Invest in robust cybersecurity measures to protect guest information, payment systems for CNP, and loyalty programs.  Implementing identity verification: Utilize advanced technologies, such as biometric authentication and behavioral analytics, to verify guests' identities and prevent account fraud.  Educating staff and guests: Provide comprehensive training to employees on recognizing and reporting suspicious activities. Educate guests about potential scams and advise them to book directly through official channels.  Sharing information: Establish platforms to share intelligence and best practices to stay ahead of evolving fraud techniques.  Acting with the right solution As the travel and hospitality industry continues to thrive, so does the risk of hospitality fraud. Travelers and hoteliers alike must remain vigilant to protect their finances from various fraud schemes prevalent today. By staying informed, taking proactive measures, and fostering collaborative efforts, we can create a safer and more secure environment within the travel industry.  Experian’s identity verification solutions power advanced capabilities across the travel lifecycle. With trusted data and advanced analytics, you can gain a complete view of your future guest to improve risk management and offer an enhanced, frictionless customer experience.   Learn more *This article leverages/includes content created by an AI language model and is intended to provide general information.

If you’re a manager at a business that lends to consumers or otherwise extends credit, you certainly are aware that 10-15% of your current customers and prospective future customers are among the approximately 27 million consumers who are now – or will soon be -- fitting another bill into their monthly budgets. Early in the COVID-19 pandemic, the government issued a pause on federal student loan payments and interest. Now that the payment pause has expired, millions of Americans face a new bill averaging more than $200. Will they pay you first? If this is your concern, you aren’t alone: Experian recently held a webinar that discussed how the end of the student loan pause might affect businesses. When we surveyed the webinar attendees,  nearly 3 out of 4 responses included Risk Management as a main concerns now. Another top concern is about credit scores. Lenders and investors use credit scores – bureau scores such FICO® or VantageScore® credit score or custom credit scores proprietary to their institution – to predict credit default risk. The risk managers at those companies want to know to what extent they can continue to rely on those scores as Federal student loan payments come due and consumers experience payment shock. I’ve analyzed a large and statistically meaningful sample (10% of the US consumer population in Experian’s Ascend Sandbox) to shed some light on that question. As background information, the average consumer with student loans had lower scores before the pandemic than the average of the general population. One of my Experian colleagues has explored some of the reasons at https://www.experian.com/blogs/ask-experian/research/average-student-loan-payments). Here are some of the things we can learn from comparing the credit data of the two groups of people. I looked at a period from 2019 and from 2023 to see how things have changed: Average credit scores increased during the pandemic, continuing a long-term trend during which more Americans have been willing and able to meet all their obligations. During the COVID Public Health Emergency, consumers with student loans brought up their scores by an average of 25 points; that was 7 points more than consumers without student loans. Another way to look at it: in 2019, consumers with student loans had credit scores 23 points lower than consumers without. By 2023, that difference had shrunk to 16 points. Experian research shows that there will be little immediate impact on credit scores when the new bills come due. Time will tell whether these increased credit scores accurately reflect a reduction in the risk that consumers will default on other bills such as auto loans or bankcards soon, even as some people fit student loan bills into their budgets. It is well-known that many people saved money during the public health emergency. Since then, the personal savings rate has fallen from a pandemic high of 32% to levels between 3% and 5% this year – lower than at any point since the 2009 recession. In an October 2023 Experian survey, only 36% of borrowers said they either set aside funds or they planned using other financial strategies specifically for the resumption of their student loan payments. Additional findings from that study can be found here. Furthermore, there are changes in the way your customers have used their credit cards over the last four years:   Consumers’ credit card balances have increased over the last four years. Consumers with student loans have balances that are on average $282 (4%) more now than in 2019. That is a significantly smaller increase than for consumers without student loans, whose total credit card debt increased by an average of $1,932 (26%). Although their balances increased, the ratio of consumers’ total revolving debt balances to their credit limits (utilization) changed by less than 1% for both consumers with student loans and consumers without. In 2019, the utilization ratio was 9.8 percentage points lower for consumers with student loans than consumers without. Four years later, the difference is nearly the same (9.6 points). We can conclude that many student loan borrowers have been very responsible with credit during the Public Health Emergency. They may have been more mindful of their credit situation, and some may have planned for the day when their student loan payments will be due. As the student loan pause come to an end, there are a few things that lenders and other businesses should be doing to be ready: Even if you are not a student loan lender, it is important to stay on top of the rapidly evolving student loan environment. It affects many of your customers, and your business with them needs to adapt. Anticipate that fraudsters and abusers of credit will be creative now: periods of change create opportunities for them and you should be one step ahead. Build optimized strategies in marketing, account opening, and servicing. Consider using machine learning to make more accurate predictions. Those strategies should reflect trends in payments, balances, and utilization; older credit scores look at a single point in time. Continually refresh data about your customers—including their credit scores and important attributes related to payments, balances, and utilization patterns. Look for alternative data that will give you a leg up on the competition. In the coming weeks and months, Experian’s data scientists will monitor measures of performance of the scores and attributes that you depend on in your data-driven strategies — particularly focusing on the Kolmogorov-Smirnov (KS) statistics that will show changes in the predictive power of each score and attribute. (If you are a data-driven business, your data science team or a trusted partner should be doing the same thing with a more specific look at your customer base and business strategies.) In future reports and blog posts, we’ll shed light on the impact student loans are having on your customers and on your business. In the meantime, for more information about how to use data and advanced analytics to grow while controlling costs and risks, all while staying in compliance and providing a good customer experience, visit our website.

Over the past few decades, the financial industry has gone through significant changes. One of the most notable changes is the use of alternative credit data1 for lending. This type of data is becoming increasingly essential in consumer and small business lending. In this blog post, we’ll explore the importance of alternative credit data and the insights you can gain from our new 2023 State of Alternative Credit Data Report. Benefits and uses of alternative credit data and alternative lending Alternative credit data and alternative financial services offer substantial benefits to lenders, borrowers, and society as a whole. The primary advantage of alternative credit data is that it provides a more comprehensive and accurate credit history of the borrower. Unlike traditional credit data that focuses on a borrower’s financial past, alternative credit data includes information from non-traditional sources like rent payments, full-file public records, utility bills, and income and employment data. This additional data allows you to gain a better understanding of financial behavior and assess creditworthiness more accurately.Alternative credit data can be used throughout the loan lifecycle, from underwriting to servicing. In the underwriting phase, alternative credit data can help lenders expand their pool of potential borrowers, especially those who lack or have limited traditional credit history. Additionally, alternative credit data can help lenders identify risks and minimize fraud. In the servicing phase, alternative credit data can help lenders monitor financial health and provide relevant services and an enhanced customer experience.Alternative lending is critical for driving financial inclusion and profitability. Traditional credit models often exclude individuals who have limited or no access to credit, causing them to turn to high-cost alternatives like payday loans. Alternative credit data can provide a more accurate assessment of their ability to pay, making it easier for them to access affordable credit. This increased accessibility improves the borrower's financial health and creates new opportunities to expand your customer base. “Lenders can access credit data and real-time information about consumers’ incomes, employment statuses, and how they are managing their finances and get a more accurate view of a consumer’s financial situation than previously possible.”— Scott Brown, President of Consumer Information Services, Experian State of alternative credit data Our new 2023 State of Alternative Credit Data Report provides exclusive insight into the alternative lending market, new data sources, inclusive finance opportunities and innovations in credit attributes and scoring that are making credit scoring more accurate, transparent and inclusive. For instance, the use of machine learning algorithms and artificial intelligence is enabling lenders to develop more predictive alternative credit scoring models and enhance risk assessment.  Findings from the report include: 54% of Gen Z and 52% of millennials feel more comfortable using alternative financing options rather than traditional forms of credit.2 62% of financial institution firms are using alternative data to improve risk profiling and credit decisioning capabilities.3 Modern credit scoring methods could allow lenders to grow their pool of new customers by almost 20%.4 By understanding the power of alternative credit data and staying on top of the latest industry trends, you can widen your pool of borrowers, drive financial inclusion, and grow sustainably. Download now 1When we refer to “Alternative Credit Data,” this refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term “Expanded FCRA Data” may also apply in this instance and both can be used interchangeably.2Experian commissioned Atomik Research to conduct an online survey of 2,001 adults throughout the United States. Researchers controlled for demographic variables such as gender, age, geographic region, race and ethnicity in order to achieve similar demographic characteristics reported in the U.S. census. The margin of error of the overall sample is +/-2 percentage points with a confidence level of 95 percent. Fieldwork took place between August 22 and August 28, 2023. Atomik Research is a creative market research agency. 3Experian (2022). Reaching New Heights with Financial Inclusion 4Oliver Wyman (2022). Financial Inclusion and Access to Credit

The gig economy — also called the sharing economy or access economy — is an activity where people earn income by providing on-demand work, services, or goods. Often, it is through a digital platform like an application (app) or website. The gig economy seamlessly connects individuals with a diverse range of services, whether it be a skilled handyman for those long-awaited office shelves, or an experienced chauffeur to quickly drive you to the airport to not miss your flight. However, there are instances when these arrangements fall short of expectations. The hired handyman may send a substitute who’s ill-equipped for the task, or the experienced driver takes the wrong shortcut leaving you scrambling to make your flight on time. On the flip side, there are numerous risks faced by those working in the gig/sharing economy, from irritable customers to dangerous situations. In such cases, trust takes a hit. The gig economy has witnessed a surge in recent years, as individuals gravitate towards flexible, freelance, and contract work instead of traditional full-time employment. This shift has unlocked a multitude of opportunities for both workers and businesses. Nevertheless, it has also ushered in challenges pertaining to security and trust. One such challenge revolves around the escalating significance of digital identity verification within the gig economy.  Digital identity verification and the gig economy  Digital identity verification encompasses validating a person's identity through digital means, such as biometric data, facial recognition, or document verification. Within the gig economy, this process has high importance, as it establishes trust between businesses and their pool of freelance or contract workers. With the escalating number of remote workers and the proliferation of online platforms connecting businesses with gig workers, verifying the identities of these individuals has become more vital than ever before.  Protecting gig users and improving the customer experience   One primary rationale behind the mounting importance of digital identity verification in the gig economy is its role in curbing fraud. As the gig economy gains traction, the risk of individuals misrepresenting themselves or their qualifications to secure work burgeons. This scenario can lead businesses to hire unqualified or even fraudulent workers, thereby posing severe repercussions for both the company and its customers. By adopting digital identity verification processes, businesses can ensure the legitimacy and competence of their workforce, subsequently decreasing the risk of fraudulent activities.  In the digital age, trust and safety are crucial for businesses to succeed. Consumers prioritize brands they can trust, and broken trust can lead to loss of customers.According to Experian's 2023 Fraud and Identity Report, over 52% of US consumers feel they’re more of a target for online fraud than they were a year ago. As such, online security continues to be a real concern for most consumers. Nearly 64% of consumers say that they are very or somewhat concerned with online security, with 32% saying they are very concerned. Establishing trust and safety measures not only protects your brand but also enhances the user experience, fosters loyalty, and boosts your business.    Role of a dedicated Trust and safety team  Trust and safety are the set of business practices for online platforms to follow to reduce the risk of users being exposed to harm, fraud, or other behaviors outside community guidelines. This is becoming an increasingly important function as online platforms look to protect their users while improving customer acquisition, engagement, and retention.  That team also safeguards organizations from security threats and scams. They verify customers' identities, evaluate actions and intentions, and ensure a safe environment for all platform users. This enables both organizations and customers to trust each other and have confidence in the platform. Their role has evolved from fraud prevention to encompass broader areas, such as user-generated content and the metaverse. With the rise of user-generated content, platforms face challenges like fake accounts, imitations, malicious links, and inappropriate content. As a result, trust and safety teams have expanded their focus and are involved in product engineering and customer journey design. Another noteworthy factor contributing to the growing emphasis on digital identity verification for trust and safety teams stems from the necessity to adhere to diverse regulations and laws. Many countries have implemented stringent regulations to safeguard workers and ensure the legal and ethical operations of businesses. In the United States, for instance, businesses must verify the identities and work eligibility of all employees, including freelancers and contractors, as part of the Form I-9 process. By leveraging digital identity verification tools, businesses can streamline these procedures and guarantee compliance with prevailing regulations.  Mitigating risk in online marketplaces  To mitigate risks in online marketplaces, businesses can take several steps, including creating a clear set of user guidelines, implementing identity verification during onboarding, enforcing multi-factor authentication for all accounts, leveraging reverification during high-risk moments, performing link analysis on the user base, and applying automation. Online identity verification plays a pivotal role in safeguarding gig workers themselves. With the surge of online platforms connecting businesses with freelancers and contractors, there comes an augmented risk of workers falling prey to scams or identity theft. By mandating digital identity verification as an integral part of the onboarding process, these platforms can shield workers and ensure they only engage with bona fide businesses.  While automation can be a powerful tool for fraud detection and mitigation, it is not a cure-all solution. Automated identity verification has its strengths, but it also has its weaknesses. While automation can spot risk signals that a human might miss, a human might spot risk signals that automation would have skipped. Therefore, for many companies, the goal should not be full automation but achieving the right ratio of automation to manual review. Manual review takes time, but it's necessary to ensure that all potential risks are identified and addressed. The more efficient these processes can be, the better, as it allows for a quicker response to potential threats. As the number of individuals embracing freelance and contract work surges, and businesses increasingly rely on these workers to carry out vital responsibilities, ensuring the security and trustworthiness of these individuals becomes paramount. By integrating digital identity verification processes, businesses can shield themselves against fraud, comply with regulations, and cultivate trust with their gig workers.  Finding the right partner While trust and safety are concerns for all online marketplaces, there’s no universal solution that will apply to all businesses and in all cases. Your trust and safety policies need to be tailored to the realities of your business. The industries you serve, regions you operate in, regulations you are subject to, and expectations of your users should all inform your processes. Experian’s comprehensive suite of customizable identity verification solutions can help you solve the problem of trust and safety once and for all.  Learn more *This article leverages/includes content created by an AI language model and is intended to provide general information.

Growing deposits from existing customers and members is an ongoing priority for banks and credit unions. However, it can be challenging to identify the best candidates. Who among our customer base has significant deposit growth potential? Who among our member base has the financial capacity to take advantage of special offers? With an effective deposit growth strategy, you can find the best customers and members to engage.  What does an effective deposit growth strategy look like?  An effective bank and credit union deposit growth strategy is powered by differentiated data and digital engagement. Let’s take a closer look at each element:  Data: A comprehensive measurement of consumers’ income and insights into their banking behaviors can help you identify those with the greatest deposit growth potential. You can then use supplemental data, such as lifestyle and demographic data, to customize deposit offers based on your customers or members’ unique needs.  Digital engagement: To further personalize this experience, consider sending deposit offers through your mobile or online banking platforms when there are triggering events on their account. Not only does this optimize the digital experience, but it also helps boost the chances of your customers or members responding.  Finding the right partner  Experian’s solutions can help your business secure deposits and customer relationships in today’s crowded market, including Banking InsightsTM. Banking Insights provide greater visibility into integrated demand deposit account activity, such as checking and saving account inquiries, to help you better assess consumers’ financial stability. By using these insights to power your banking growth strategies, you can identify those with the financial capacity to bring in more deposits.  Read our e-book to learn about other solutions that can help you boost deposits, strengthen existing relationships, and provide seamless digital experiences. Read e-book

This article was updated on November 9, 2023. Automation, artificial intelligence and machine learning are at the forefront of the continued digital transformation within the world of collections. And organizations from across industries — including healthcare, financial services and the public sector — are learning how automation can improve their workflows and collection efforts. When implemented well, automation can ease pressure from call center agents, which can be especially important when there's a tight labor market and retention is at the forefront of every employer's mind. Automated systems can also help improve recovery rates while minimizing the risk of human error and the corresponding liability. These same systems can increase long-term customer satisfaction and lifetime value. Deeper insights into consumers' financial situations and preferences allow you to avoid wasting resources and making contact when consumers are truly unable to pay. Instead, monitoring and following up with their preferred contact method can be a more successful approach — and a better experience for consumers. The end of pandemic assistance programs and policies, along with new compliance requirements, are making automation more important than ever before. Three tips when automating debt collections Automation and artificial intelligence (AI) aren't new to collections. You may have heard about or tried automated dialing systems, chatbots, text message services and virtual negotiators. But the following three points can be important to consider as the technology and compliance landscapes change.1 1. Good automation depends on good data Whether you're using static automated systems to improve efficiencies or using a machine learning model that will adapt over time, the data you feed into the system needs to be accurate. The data can be internal, from call center agents and your customers, and external sources can help verify and expand on what you know. With your internal systems, consider how you can automate processes to limit human errors. For example, you may be able to auto-fill contact information for customers and agents — saving them time and avoiding typos that can cause issues later. External data sources can be helpful in several ways. You can also use third-party data as a complementary resource to help determine the best address, phone number or email address to increase right-party contact (RPC) rates. External sources can also validate your internal data and automatically highlight errors or potentially outdated information, which can be important for maintaining compliance.2 Robust and frequently updated datasets can make your collection efforts more efficient and effective. An automated system could be notified when a debtor resurfaces or gets a new job, triggering new reminders or requests for payment. And if you're using the right tools, you can automatically route the account to internal or external servicing and prioritize accounts based on the consumer's propensity to pay or the expected recovery amount. 2. Expand consumers' communication options and choices Your automated systems can suggest when and who to contact, but you'll also want them to recommend the best way to contact consumers. An omnichannel strategy and digital-first approach is increasingly the preferred method by consumers, who have become more accustomed to online communications and services throughout the pandemic. The Experian 2022 Global Insights Report highlights that 81 percent of consumers say they think more highly of brands when they have a positive experience with the brand online, including when there are multiple digital touchpoints. Additionally, 59 percent of consumers trust organizations that use AI.3 Organizations can benefit by using alternative communication methods, such as push notifications, as part of an AI-driven automated process. These can be unobtrusive reminders that gently nudge customers without bothering them, and send them to self-cure portals. Many consumers may need to review the payment options before committing — perhaps they need to check their account balances or ask friends or family for help. Self-service options through an app or web portal can give them choices, such as a single payment or payment plan, without having to involve a live agent. 3. Maintaining compliance must be a priority As the pandemic responses made clear, you need to be ready to adjust to a rapidly changing compliance environment. Over the last few years, organizations have also had to react to changes that can impact Telephone Consumer Protection Act (TCPA) compliance. And the first part of the debt collection final rule from the Consumer Financial Protection Bureau (CFPB), which impacts collectors' use of electronic communications and increases consumers' control over communication.4 The automated systems you use should be nimble enough to comply with required changes, and they should be able to support your overall operation's compliance. In particular, you may want to focus on how automated systems collect, verify, safeguard and send consumers' personal information. Watch more: Webinar: Keeping pace with collections compliance changes Why partner with Experian? Whether you're looking to explore or expand your use of automated systems in your collection efforts, you want to make sure you're taking the right approach. Experian helps clients balance effective collections and a great customer experience within their given constraints, including limited budgets and regulatory compliance. The Experian Ascend Intelligence Platform and award-winning PowerCurve® Collections solutions are also making AI-driven automated systems accessible to more lenders and collectors than ever before. Taking a closer look at Experian's offerings, we can focus on three particular areas: Industry-leading data sources Experian's data sources go well beyond the consumer credit database, which has information on over 245 million consumers. Clients can also benefit from alternative financial services data, rental payment data, modeled income estimates, information on collateral and skip tracing data. And real-time access to information from over 5,000 local exchange carriers, which can help you validate phone ownership and phone type.5 Tools for maximizing recovery rates Experian helps clients turn data into insights and decisions to determine the best next step. Some of Experian's offerings include: PriorityScore for CollectionsSM: Over 60 industry-specific debt recovery scores that can help you prioritize accounts based on the likelihood to pay or expected recovery amount.6 RecoveryScore 2.0: Helps you prioritize charged-off accounts based on collectability. TrueTrace™ and TrueTrace Live™: Find consumers based on real-time contact information. We've seen a 10 percent lift in RPC with clients who use Experian's locating tools, TrueTrace or TrueTrace Live. Collection Triggers℠: Sometimes, waiting is the best option. And with an account monitoring tool like Collection Triggers℠, you'll automatically get notified when it makes sense to reach out. RPC contact scores: Tools like Phone Number ID™ and Contact Monitor™ can track phone numbers, ownership and line type to determine how to contact consumers. Real-time data can also increase your RPC rates while limiting your risk. You can use these, and other, tools to prioritize collection efforts. Experian clients also use different types of scores that aren't always associated with collections to segment and prioritize their collection efforts, including bankruptcy and traditional credit-based scores. Custom models based on internal and external scores can also be beneficial, which Experian can help you build, improve and house. Prioritize collections activities with confidence Collections optimization comes down to making the right contact at the right time via the right channel. Equally important is making sure you're not running afoul of regulations by making the wrong contact. Experian's data standards and hygiene measures can help you: Identify consumers who require special handling Validate email addresses and identify work email addresses Get notified when a line type or phone ownership changes Append new contact information to a consumer's file Know when to reach out to consumers to update contact information and permissions Recommend the best way to reach consumers Automated tools can make these efforts easier and more accurate, leading to a better consumer experience that increases the customer's lifetime value and maximizes your recovery efforts. Learn more 1Consumer Financial Protection Bureau Issues Final Rule to Implement the Fair Debt Collection Practices Act, October 2020. 2Collections After Compliance, Experian August 2019 3"Experian 2022 Global Insights Report," Experian April 2022 4Consumer Financial Protection Bureau Issues Final Rule to Implement the Fair Debt Collection Practices Act, October 2020 5Phone Number ID with Contact Monitor, Experian, August 2020 6PriorityScore for Collections Product Sheet, Experian 2020

This article was updated on April 23, 2024. Keeping your organization and consumers safe can be challenging as cybercriminals test new attack vectors and data breaches continually expose credentials. Instead of relying solely on usernames and passwords for user identity verification, adding extra security measures like multi-factor authentication can strengthen your defense. What is multi-factor authentication? Multi-factor authentication, or MFA, is a method of authenticating people using more than one type of identifier. Generally, you can put these identifiers into three categories based on the type of information: Something a person knows: Usernames, passwords, and personal information are common examples of identifiers from this category. Something a person has: These could include a phone, computer, card, badge, security key, or another type of physical device that someone possesses. Something a person is: Also called the inherence factor, these are intrinsic behaviors or qualities, such as a person's voice pattern, retina, or fingerprint. The key to MFA is it requires someone to use identifiers from different categories. For example, when you withdraw money from an ATM, you're using something you have (your ATM card or phone), and something you know (your PIN) or are (biometric data) to authenticate yourself. Common types of authenticators Organizations that want to implement multi-factor authentication can use different combinations of identifiers and authenticators. Some authenticator options include: One-time passwords: One-time passwords (OTPs) can be generated and sent to someone's mobile phone via text to confirm the person has the phone or via email. There are also security tokens and apps that can generate OTPs for authentication. (Something you know.) Knowledge-based authentication: Knowledge-based authentication (KBA) identity verification leverages the ability to verify account information or a payment card, “something you have,” by confirming some sequence of numbers from the account. (Something you know.) Security tokens: Devices that users plug into their phone or computer, or hold near the device, to authenticate themselves. (Something you have.) Biometric scans: These can include fingerprint and face scans from a mobile device, computer, or security token. (Something you are.) Why MFA is important It can be challenging to keep your users and employees from using weak passwords. And even if you enforce strict password requirements, you can't be sure they're not using the same password somewhere else or accidentally falling for a phishing attack. In short, if you want to protect users' data and your business from various types of attacks, such as account takeover fraud, synthetic identity fraud, and credential stuffing, you’ll need to require more than a username and password to authenticate users. That’s where MFA comes in. Because it uses a combination of elements to verify a consumer’s identity, if one of the required components in a transaction is missing or supplied incorrectly, the transaction won’t proceed. As a result, you can ensure you’re interacting with legitimate consumers and protect your organization from risk. LEARN MORE: Explore our fraud prevention solutions. How to provide a frictionless MFA experience While crucial to your organization, in-person and online identity verification shouldn’t create so much friction that legitimate consumers are driven away. Experian's 2023 U.S. Identity and Fraud Report found that 96 percent of consumers view OTPs as convenient identity verification solutions when opening a new account. An increasing number of consumers also view physical and behavioral biometrics as some of the most trustworthy recognition methods — 81 and 76 percent, respectively. To create a low friction MFA experience that consumers trust, you could let users choose from different MFA authentication options to secure their accounts. You can also create step-up rules that limit MFA requests to riskier situations — such as when a user logs in from a new device or places an unusually large order. To make the MFA experience even more seamless for consumers, consider adding automated identity verification (AIV) to your processes. Because AIV operates on advanced analytics and artificial intelligence, consumers can verify their identities within seconds without physical documentation, allowing for a quick, hassle-free verification experience. How Experian powers multi-factor authentication Experian offers various identity verification and risk-based authentication solutions that organizations can leverage to streamline and secure their operations, including: Experian’s CrossCore® Doc Capture confidently verifies identities using a fully supported end-to-end document verification service where consumers upload an image of a driver’s license, passport, or similar directly from their smartphone. Experian’s CrossCore Doc Capture adds another layer of security to document capture with a biometric component that enables the individual to upload a “selfie” that’s compared to the document image. Experian's OTP service uses additional verification checks and identity scoring to help prevent fraudsters from using a SIM swapping attack to get past an MFA check. Before sending the OTP, we verify that the number is linked to the consumer's name. We also review additional attributes, such as whether the number was recently ported and the account's tenure. Experian's Knowledge IQSM offers KBA with over 70 credit- and noncredit-based questions to help you engage in additional authentication for consumers when sufficiently robust data can be used to prompt a response that proves the person has something specific in their possession. You can even configure it to ask questions based on your internal data and phrase questions to match your brand's language. Learn more about how our multi-factor authentication solutions can help your organization verify consumer identities and mitigate fraud. Learn about our MFA solutions

  Managing digital identities is a necessity, responsibility and privilege. When done right, digital identity management solutions can help consumers feel recognized and safe. In turn, companies can build strong and personalized relationships with their customers while complying with regulatory requirements and combating hydra-like fraud attacks. What is digital identity? The concept and definition of a digital identity have expanded as everyday interactions increasingly happen in digital realms. Today, a digital identity is more than an online account. Identities can be created and depend on all the digital information associated with a unique entity, which may be a person, business or device. A person's digital identity often includes online and offline attributes that fall into one of three categories: Something a user knows, such as a username, password or PIN. Something a user has, such as a mobile phone or security token. Something that's part of the user, such as a fingerprint, iris, voice pattern, behavior or preferences. People are increasingly open to sharing this type of personal information if it serves a purpose. Our Global Identity and Fraud Report found that 57 percent of consumers are willing to share data if it ensures greater security or prevents fraud, and 63 percent of consumers think sharing data is beneficial (up from 51 percent in 2021).1 People can also use these identifiers to verify their identity at a later point. But digital identity verification tools should rely on more than user-provided verification alone. A person may have hundreds or thousands of digital interactions every day, and these can leave digital footprints that you can use to create or expand digital identities. These types of identifiers — such as search queries, geotags, behaviors and device information — can also help you authenticate a user and offer a more customized and seamless experience. However, when focusing on consumers' digital identities, it's important to remember that their identity is more than the sum of data points. A person's digital identity is unique and personal, and it should be managed accordingly. The business side's challenges A discussion of what makes up an identity can quickly turn philosophical. For instance, you can't authenticate identical twins based on a face scan or DNA test, so what is it that makes them unique? In some ways, the example gets to the heart of businesses' challenges today. To create a safe and enjoyable online identity verification experience, you need to be able to distinguish between a real person and an imitator, even when the two look nearly identical. Access to more information can make this easier, but you then need to ensure that you can keep this information secure. It can be a tricky balance, but if you get it right, your efforts will be rewarded. People want to be recognized as they move across channels and devices, and organizations want to be able to quickly and accurately identify users with a friction-right experience that also helps prevent fraud. However, while 84 percent of businesses say recognizing customers is "very" or "extremely" important, only about 33 percent of consumers are confident that they'll be repeatedly recognized online.1 There's a clear gap — and an opportunity to better meet customers' desires. Organizations across industries know they need a customer recognition strategy and 82% already have one in place.2 Some businesses address this challenge with identity platforms that are standardized and interoperable. Standardization allows the platform to gather and store the growing influx of data that it can use as part of a digital identity strategy. Interoperability allows the platform to match different types of data, including physical data, with a person to verify their digital identity and avoid the creation of duplicate identities. In short, the platforms can make sense of increasingly large amounts of internal and external data and easily incorporate new data sources as they become available. Regulatory compliance and digital identity Navigating the regulatory landscape is a significant challenge for organizations dealing with digital identities. Compliance is not only necessary for legal reasons but also critical to maintaining customer trust and safeguarding institutional reputation. Organizations must stay informed about the regulatory frameworks that affect digital identity, such as the General Data Protection Regulation (GDPR) in the European Union, the California Consumer Privacy Act (CCPA), and other pertinent laws in jurisdictions they operate. These regulations dictate how personal data can be collected, stored, used and shared. Staying ahead of regulatory changes: Regulatory landscapes are dynamic, particularly concerning digital data. Organizations should engage with policymakers and participate in industry forums to  stay ahead of changes. By proactively managing compliance, organizations can avoid costly penalties, operational disruptions and reputational damage. The consumer's perspective Some organizations are adopting a consumer-centric approach to digital identity that puts consumers' needs and desires first. These can broadly be broken into four categories: Security: While people want a seamless and personalized experience, security and privacy are listed as top concerns year after year.1 That might not be surprising given that data breaches continually make headlines and there are growing concerns over identity theft. Privacy: Security is related to privacy, but privacy means more than keeping consumers' information safe from hackers. Our April 2022 Global Insight Report found that 90 percent of consumers want some or complete control over how their personal data is used. 3 Recognition: People want to be continually recognized once they share and verify their identity, even if they move between devices or channels. And nearly 70 percent of consumers say it's important for businesses to recognize them across multiple visits.1 Inclusion: Consumers may have varying levels of access to technology, comfort with technology and access to physical identifiers. Creating digital identity solutions for these potential barriers can also increase financial inclusion. While these are all areas of focus, organizations also need to find the right fit for each person and interaction. For instance, consumers may expect and even appreciate a robust verification process when they're opening a new financial account. But they could quickly be turned off by a similar process if they're making a small purchase or trying to play a new online game. What to look for in a digital identity partner Digital identity solutions and services have grown increasingly sophisticated to meet today's challenges. Identity hubs and data orchestration engines can connect with multiple services to help create, resolve, verify and authenticate identities. By moving away from a siloed approach, businesses can offer customers a better experience while minimizing their risk throughout the customer journey. When comparing potential partners, look for a company that: Has a customer-first approach: If your business is customer-first, then you need a partner who has a similar view. Uses multidimensional data: The partner should be able to offer and use offline and digital data sources to resolve, verify and authenticate digital identities. Its capabilities may become increasingly important as new data sources emerge. Isn't afraid to innovate: Look into how the partner is testing and using the latest advancements, such as artificial intelligence, in its digital identity solutions. Protects your brand: Understand how the partner helps detect and prevent fraud while creating a seamless experience for your customers and protecting their data. The right partner can increase your bottom line, help you build trust and improve your brand's reputation. Learn more about Experian Identity, an integrated approach to digital identity that builds on Experian's decades of experience managing and securing identifying information. Learn more 1“2022 Global Identity and Fraud Report: Building digital consumer trust amidst rising fraud activity and concerns," Experian, June 2022 2“2021 Global Identity and Fraud Report: Protecting and enabling customer engagements in the new digital era," Experian, April 2021. https://www.experian.com/content/dam/marketing/na/global-da/pdfs/GIDFR_2022.pdf https://www.experian.co.th/wp-content/uploads/2021/04/Experian-Global-Identity-Fraud-Report-2021.pdf 3"Global Insights Report: April 2022," Experian, April 2022. https://www.experian.com/blogs/global-insights/wp-content/uploads/2022/04/WaveReportApril2022.pdf *This article includes content created by an AI language model and is intended to provide general information.