Digital Technology

This article was updated on February 21, 2024. With the rise of technology and data analytics in the financial industry today, it's no longer enough for companies to rely solely on traditional marketing methods. Data-driven marketing insights provide a more sophisticated and comprehensive view of shifting customer preferences and behaviors. With this in mind, this blog post will highlight the importance of data-driven marketing insights, particularly for financial institutions. The importance of data-driven marketing insights 30% of companies say poor data quality is a key challenge to delivering excellent customer experiences. Today’s consumers want personalized experiences built around their individual needs and preferences. Data-driven marketing insights can help marketers meet this demand, but only if it is fresh and accurate. When extending firm credit offers to consumers, lenders must ensure they reach individuals who are both creditworthy and likely to respond. Additionally, their message must be relevant and delivered at the right time and place. Without comprehensive data insights, it can be difficult to gauge whether a consumer is in the market for credit or determine how to best approach them. READ: Case study: Deliver timely and personalized credit offers The benefits of data-driven marketing insights By drawing data-driven marketing insights, you can reach and engage the best customers for your business. This means: Better understanding current and potential customers To increase response and conversion rates, organizations must identify high-propensity consumers and create personalized messaging that resonates. By leveraging customer data that is valid, fresh, and regularly updated, you’ll gain deeper insights into who your customers are, what they’re looking for and how to effectively communicate with them. Additionally, you can analyze the performance of your campaigns and better predict future behaviors. Utilizing technology to manage your customer data With different sources of information, it’s imperative to consolidate and optimize your data to create a single customer view. Using a data-driven technology platform, you can break down data silos by collecting and connecting consumer information across multiple sources and platforms. This way, you can make data available and accessible when and where needed while providing consumers with a cohesive experience across channels and devices. Monitoring the accuracy of your data over time Data is constantly changing, so implementing processes to effectively monitor and control quality over time is crucial. This means leveraging data quality tools that perform regular data cleanses, spot incomplete or duplicated data, and address common data errors. By monitoring the accuracy of your data over time, you can make confident decisions and improve the customer experience. Turning insights into action With data-driven marketing insights, you can level up your campaigns to find the best customers while decreasing time and dollars wasted on unqualified prospects. Visit us to learn more about how data-driven insights can power your marketing initiatives. Learn more Enhance your marketing strategies today This article includes content created by an AI language model and is intended to provide general information.

This article was updated on February 12, 2024. The Buy Now, Pay Later (BNPL) space has grown massively over the last few years. But with rapid growth comes an increased risk of fraud, making "Buy Now, Pay Never" a crucial fraud threat to watch out for in 2024 and beyond. What is BNPL? BNPL, a type of short-term financing, has been around for decades in different forms. It's attractive to consumers because it offers the option to split up a specific purchase into installments rather than paying the full total upfront. The modern form of BNPL typically offers four installments, with the first payment at the time of purchase, as well as 0% APR and no hidden fees. According to an Experian survey, consumers cited managing spending (34%), convenience (31%), and avoiding interest payments (23%) as main reasons for choosing BNPL. Participating retailers generally offer BNPL at point-of-sale, making it easy for customers to opt-in and get instantly approved. The customer then makes a down payment and pays off the installments from their preferred account. BNPL is on the rise The fintech and online-payment-driven world is seeing a rise in the popularity of BNPL. According to Experian research, 3 in 4 consumers have used BNPL in 2023, with 11% using BNPL weekly to make purchases. The interest in BNPL also spans generations — 36% of Gen Z, 43% of Millennials, 32% of Gen X, and 12% of Baby Boomers have used this payment method. The risks of BNPL While BNPL is a convenient, easy way for consumers to plan for their purchases, experts warn that with lax checkout and identity verification processes it is a target for digital fraud. Experian predicts an uptick in three primary risks for BNPL providers and their customers: identity theft, first-party fraud, and synthetic identity fraud. WATCH: Fraud and Identity Challenges for Fintechs Victims of identity theft can be hit with charges from BNPL providers for products they have never purchased. First-party and synthetic identity risks will emerge as a shopper's buying power grows and the temptation to abandon repayment increases. Fraudsters may use their own or fabricated identities to make purchases with no intent to repay. This leaves the BNPL provider at the risk of unrecoverable monetary losses and can impact the business' risk tolerance, causing them to narrow their lending band and miss out on properly verified consumers. An additional risk lies with fraudsters who may leverage account takeover to gain access to a legitimate user's account and payment information to make unauthorized purchases. READ: Payment Fraud Detection and Prevention: What You Need to Know Mitigating BNPL risks Luckily, there are predictive credit, identity verification, and fraud prevention tools available to help businesses minimize the risks associated with BNPL. Paired with the right data, these tools can give businesses a comprehensive view of consumer payments, including the number of outstanding BNPL loans, total BNPL loan amounts, and BNPL payment status, as well as helping to detect and apply the relevant treatment to different types of fraud. By accurately identifying customers and assessing risk in real-time, businesses can make confident lending and fraud prevention decisions. To learn more about how Experian is enabling the protection of consumer credit scores, better risk assessments, and more inclusive lending, visit us or request a call. And keep an eye out for additional in-depth explorations of our Future of Fraud Forecast. Learn more Future of Fraud Forecast

This article was updated on February 6, 2024. Lenders looking to gain a competitive edge need to improve their credit underwriting process in the coming years. The most obvious developments are the advances in artificial intelligence (AI) — machine learning in particular — the increased available computing capacity, and access to vast amounts of data. But when it comes to credit underwriting models, those are tools you can use to reach your goals, not a strategy for success. The evolution of credit underwriting Credit underwriters have had the same goal for millennia — assess the creditworthiness of a borrower to determine whether to offer them a loan. But the process has changed immensely, and the pace of change has recently increased. Fewer than 50 years ago, an underwriter might consider an applicant's income, occupation, marital status, and sex to make a decision. The Equal Credit Opportunity Act didn't pass until 1974. And it wasn't expanded to prohibit lending discrimination based on other factors, such as color, age, and national origin, until two years later. Regulatory changes can have an immediate and immense impact on credit underwriting, but there were also slower changes developing. As credit bureaus centralized and computers became more readily available, credit decisioning systems offered new insights. The systems could segment groups and help lenders make more complex and profitable decisions at scale, such as setting risk-appropriate credit limits and terms. INFOGRAPHIC: Data-driven decisioning journey map With access to more data and computing power, lenders get a more complete picture of applicants and their current customers. Technological advances also lead to automated decisions, which can improve lenders' workflows and customer satisfaction. In the late 2000s, fintech lenders entered the scene and disrupted the ecosystem with a completely online underwriting and funding process. More recently, AI and machine learning started as buzzwords, but quickly became business necessities. In fact, 66% of businesses believe advanced analytics, including machine learning and artificial intelligence, are going to rapidly change the way they do business.1 The latest explainable machine learning models can increase automation and efficiency while outperforming traditional modeling approaches. Access to increased computing power is, once again, helping power this shift.2 But it's also only possible because of the lenders access to alternative credit data.* WATCH: Why Advanced Analytics is Now Available for All Future-proofing your credit underwriting strategy Today's leading lenders use innovative technology and comprehensive data to improve their credit decisioning — including fraud detection, underwriting, account management, and collections. To avoid getting left behind, you need to consider how you can incorporate new tools and processes into your strategy. Get comfortable with machine learning models Although machine learning models have repeatedly shown they can offer performance improvements, lenders may hesitate to adopt them if they can't explain how the models work. It's smart to be cautious as so-called “black box" models generally don't pass regulatory muster — even if they can offer a greater lift. But there is a middle ground, and credit modelers use machine learning techniques to develop more effective models that are fully explainable. READ MORE: Explainability: ML and AI in credit decisioning Explore new data sources Machine learning models are great at recognizing patterns, but you need to train them on large data sets if you want to unlock their full potential. Lenders' internal data can be important, especially if they're developing custom models. But lenders should also try leveraging various types of alternative credit data to train models and more accurately assess an applicant's creditworthiness. This can include data from public records, rental payments, alternative financial services, and consumer-permissioned data. READ MORE: 2023 State of Alternative Credit Data Report Focus on financial inclusion Using new data sources can also help you more accurately understand the risk of an applicant who isn't scorable with traditional models. For example, Lift Premium™ uses machine learning and a combination of traditional consumer bureau credit data and alternative credit data to score 96 percent of U.S. consumers — 15 percent more than conventional scores.3 As a result, lenders can expand their lending universe and offer right-sized terms to people and groups who might otherwise be overlooked. Use AI to fuel automation Artificial intelligence can accelerate automation throughout the credit life cycle. Machine learning models do this within underwriting by more precisely estimating the creditworthiness of applicants. The more accurate a model is, the better it will be at identifying applicants who lenders want to approve or deny. Consider your decisioning strategy Although a machine learning model might offer more precise insight, lenders still need to set their decisioning strategy and business rules, including the cutoff points. Credit decisioning software can help lenders implement these decisions with speed, accuracy, and scalability. CASE STUDY: Experian partnered with OneAZ Credit Union to upgrade to an advanced credit decisioning platform and automate its underwriting strategy. The credit union increased load funding rates by 26 percent within one month and reduced manual reviews by 25 percent. Use underwriting as a component of strategic optimization Advanced analytics allow companies to move away from simpler rule-based decisions and toward strategies that take the business's overall goals into account. For example, lenders may be able to optimize decisions that involve competing goals — such as targets for volume and bad debt — to help the business reach its goals. Test and benchmark Underwriting is an iterative process. Lenders can use machine learning techniques to build and test challenger models and see how well they perform. You can also compare the results to industry benchmarks to see if there's likely room for more improvement. Why lenders choose Experian Lenders have used Experian's consumer and business credit data to underwrite loans for decades, but Experian is also a leader in advanced analytics. As lenders try to figure out how they'll approach underwriting in the coming years, they can partner with Experian's data scientists, who understand how to develop and deploy the latest types of compliant and explainable credit underwriting models. Experian also offers credit underwriting software and cloud-based and integrated decisioning platforms, along with modular solutions, such as access to alternative credit data, predictive attributes and scores. And lenders can explore collaborative approaches to developing ML-aided models that incorporate internal and third-party data. If you're not sure where to start, a business review can help you identify a few quick wins and create a road map for future improvements. Explore our credit decisioning solutions. * 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. 1Experian (2022). Explainability: ML and AI in credit decisioning2Experian (2022). Webinar: Driving Growth During Economic Uncertainty with AI/ML Strategies 3Experian (2022). Lift Premium

This article was updated on January 30, 2024. Income verification is a critical step in determining a consumer’s ability to pay. The challenge is verifying income in a way that’s seamless for both lenders and consumers. While many businesses have already implemented automated solutions to streamline operations, some are still relying on manual processes built on older technology. Let’s take a closer look at the drawbacks of traditional verification processes and how Experian can help businesses deliver frictionless verification experiences. The drawbacks of traditional income verification Employment and income verification provides lenders with greater visibility into consumers’ financial stability. But it often results in high-touch, high-friction experiences when done manually. This can be frustrating for both lenders and potential borrowers: For lenders: Manual verification processes are extremely tedious and time-consuming for lenders as it requires physically collecting and reviewing documents. Additionally, without reliable income data, it can be difficult for lenders to accurately determine a consumer’s ability to pay, leading to higher origination risk. For borrowers: Today’s consumers have grown accustomed to digital experiences that are fast, simple, and convenient. A verification process that is slow and manual may cause consumers to drop off altogether. How can this process be optimized? To accelerate the verification process and gain a more complete view of consumers’ financial stability, lenders must look to automated solutions. With automated income verification, lenders obtain timely income reports to accurately verify consumers’ income in minutes rather than days or weeks. Not only does this allow lenders to approve more applicants quickly, but it also enables them to devote more time and resources toward improving their strategies and enhancing the customer experience. The right verification solution can also capture a wider variety of income scenarios. With the click of a button, consumers can give lenders permission to access their financial accounts, including checking, savings, 401k, and brokerage accounts. This creates a frictionless verification experience for consumers as their income information is quickly extracted and reviewed. Retrieving data directly from financial accounts also provides lenders with a fuller financial picture of consumers, including those with thin or no credit files. This helps increase the chances of approval for underserved communities and allows lenders to expand their customer base without taking on additional risk.1 Learn more 1 Experian Income Verification Product Sheet (2017).

This article was updated on January 23, 2024. Sometimes you have to break from tradition and look to modern solutions to address modern problems. As consumers increasingly expect fast-paced digital experiences, lenders are tapping into advances in computing power to enhance their operations. According to a 2022 Experian study, 66% of businesses believe advanced analytics, including machine learning and artificial intelligence, are going to rapidly change the way they do business.1 While some may feel wary about trusting automated systems, remember that you're in control of the strategy. Automation comes in after to help take over monotonous and complex or error-prone tasks. As a result, you can free up resources for work that isn't as well-suited for automation, such as analyzing results and revising strategies. The benefits of automation within loan origination From initial screenings to determining a final decision or credit limit, automation can offer benefits throughout the loan origination process. And lenders of all sizes are exploring opportunities for automation to help them: Manage an overwhelming number of applications:  Lenders may be struggling to respond to an increased demand for credit, particularly if they're also dealing with staffing shortages and rely on manual inputs and reviews. Automation can remove some of the burden from employees and lead to faster decisions. Increase consistency and accuracy:  Transposing information from applications and making calculations by hand can result in errors or inconsistent results. Modern automated systems can help ensure information is accurate, uniform and up to date. Create scalable processes:  Automated processes are easier to scale than a strategy that relies on consistent manual reviews and frequent back-and-forth with customers. Improve customers' experiences:  Fast, accurate and fair decisions make for happy customers. However, 58% don't feel that businesses completely meet their expectations for their online experience.2 What's more, 91% of online applications are abandoned before completion.3 More loans, a consistent scalable process and happy customers can all drive revenue growth. When integrated throughout the underwriting journey, automation can also help you increase conversion rates and expand your lending universe without taking on more risk. What does an optimized and automated loan origination process look like? Modern loan origination software offers flexibility, security, speed and robust integrations. These can be cloud-based systems that vendors create and manage on your behalf, or lenders that have the resources and capabilities may be able to bring (or build) them in house. Strategy first Automating parts of your origination process can save you time and money, but you have to start with a specific strategy. For example, you might consider your model's outputs and decide on denial and approval cut-off points — you can then automate those approvals and denials. You can also test, revise, and optimize strategies based on your desired results. Digital applications Let consumers apply when and how they want, even if it means pausing part-way through and continuing on a different device later. Remove potentially time-consuming steps by letting consumers upload and sign documents digitally, and use AI-driven automated systems to review the documents for accuracy.4 Integration with various data sources You need good data—and lots of it—to get the most out of an automated system. Some platforms can automatically connect and use internal data alongside third-party data sources, such as alternative data, credit bureau data and credit attributes. Identity, income and fraud checks Automated platforms can work with verification tools to quickly confirm the applicant's employment and income, confirm their identity and perform fraud checks. The process can take minutes rather than days or weeks, letting you quickly move applicants through to the next stage of the process. Decisions based on optimized models Automated decision engines use your strategy and the available data to quickly return a decision. Machine learning models can score consumers who aren't scorable by traditional credit models, expanding your potential customer base while furthering financial inclusion goals. They can also more accurately score applicants and narrow the band (and potentially the number of applications) that requires manual reviews.5 Automation in action:  Atlas Credit, a small-dollar lender, wanted to modernize its lending with customized and automated systems. Experian helped them build a custom machine learning credit risk model and optimized their decision strategy and cutoffs. The results exceeded Atlas Credit's goals, and the company  nearly doubled their loan approval rates  while decreasing risk losses by 15 to 20 percent. Explainable results Automated, fast decisions based on machine learning and AI analytics might raise some compliance flags—but we've moved beyond black box models. You need to be aware of and follow all the applicable regulations, and you can use AI and machine learning in precise ways to increase your efficiency while having fully explainable and compliant results. Experian's automated offerings build on a history of success Experian has decades of experience helping lenders make accurate and timely credit decisions, and our flexible loan origination system can help you automate originations while managing risk. It starts with good data. While we're known for our consumer credit database that has information on over 245 million consumers, Experian can also give lenders access to alternative data, including alternative financial services, rental payment data and consumer-permission data. And we know how to incorporate your internal data to create strategies that will further your specific goals. From marketing to collections, our integrated offerings can help you use the data to automate and optimize decisions across the entire customer life cycle. And whether you want to take the reins or tap our data scientists for their expertise, there are options to fit your needs. Learn more about our suite of loan origination software solutions and PowerCurve® Originations Essentials, our automated decision engine. Learn more 1Experian (2022). Explainability: ML and AI in credit decisioning2Experian (2022). North America findings from the 2022 Decisioning Survey 3Experian (2023). eBook: The Ultimate Guide to Competitive Growth 4Ibid.5Experian (2022). Driving Growth During Economic Uncertainty with AI/ML Strategies

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

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.

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

In today’s age, where speed and convenience are paramount, lenders must transform their digital income verification experience to meet customer expectations. Leveraging the benefits of instant verification is crucial to delivering a seamless experience. However, there are situations where instant verification may not be available or unable to verify customers. This is where the value of incorporating user-permissioned verification into your workflow becomes evident.   Let’s explore the advantages of using a combination of instant and permissioned verification and how they can synergistically enhance coverage, reduce costs, improve efficiency, and deliver an exceptional customer experience.  Instant verification: The epitome of efficiency and experience  Instant verification technology enables lenders to access real-time customer data, making it the pinnacle of verification efficiency. Its ability to deliver immediate insights facilitates quick decision-making, ensuring a seamless and frictionless experience for lenders and customers. There are several benefits to streamlining your verification process, including:   Speed and efficiency: Eliminate the time-consuming process of manually gathering and analyzing data to expedite loan approvals and reduce customer waiting times.  Enhanced user experience: With real-time results, customers can complete their applications quickly and effortlessly, leading to increased satisfaction and higher conversion rates.  Reduced risk: Assess applicant information promptly, maintaining the security and integrity of lending processes.  Permissioned verification: Expanding coverage and engaging customers  While instant verification technology offers numerous advantages, it may not always be available or suitable for every customer. This is where permissioned verification plays a vital role. By integrating permissioned verification into the verification workflow, lenders can expand coverage and keep customers engaged in a digital channel, reducing abandonment rates. The benefits of leveraging permissioned verification include:  Convenience and speed: By granting permissioned access, customers avoid the hassle of uploading or submitting documents manually. This saves time and effort, resulting in a faster verification process.  Increased coverage and reduced abandonment: Permissioned verification ensures a higher coverage rate by minimizing the potential for customer abandonment during the application process. Since the information is retrieved seamlessly, customers are more likely to complete the application without frustration.  Privacy and control: Customers retain control over their data by explicitly granting permission for access. This enhances transparency and empowers individuals to manage their financial information securely.  Creating a verification "waterfall" for optimal results  To harness the combined power of instant and permissioned verification, lenders can establish a verification "waterfall" approach. This approach involves a cascading verification process where instant verification is the first step, followed by permissioned verification if instant verification is not available or unable to verify the customer.                                              Example of Experian Verify’s automated verification waterfall.  There are numerous advantages to adopting a “waterfall” approach, including:   Cost efficiency: Lenders who prioritize instant verification save on operational costs associated with manual verification processes. The seamless transition to permissioned verification reduces the need for manual intervention, minimizing expenses and improving efficiency.  Improved verification success rate: A verification waterfall ensures that alternative verification methods are readily available if the initial instant verification is unsuccessful. This increases the overall success rate of verifying customer data and reduces the likelihood of losing potential borrowers.  Enhanced customer experience: The combination of instant and permissioned verification creates a streamlined and frictionless customer experience. Customers can progress seamlessly through the verification process, reducing frustration and increasing satisfaction levels.  Propelling your business forward  In the dynamic landscape of lending, a combination of instant and permissioned verification technologies provides significant value to lenders and customers. While instant verification delivers unparalleled efficiency and experience, incorporating permissioned verification ensures expanded coverage, reduced abandonment rates, and a seamless digital journey for customers. By implementing a verification "waterfall" approach, lenders can optimize verification processes, reduce costs, improve efficiency, and ultimately deliver an exceptional customer experience.  Learn more about our solutions The advantages of instant and permissioned verification *This article leverages/includes content created by an AI language model and is intended to provide general information.

Are you looking for ways to make your financial institution more secure without adding unnecessary friction to the customer experience? Automated identity verification is an essential part of this process, safeguarding sensitive consumer information and helping to prevent fraud. This blog post will serve as the ultimate guide to automated identity verification so that you can understand why it's important and how it works. We'll cover all the details, like what automated ID verification is, how authentication software works with identifying documents, why automated identification technology is preferred over manual processes, and tips on implementing automation identity verification solutions into your business practices.   What is automated identity verification?  Automated identity verification is a secure, efficient process for verifying the identity of individuals or entities. This process is integral in various industries, especially the financial sector, to curb identity theft and fraudulent activities. It operates by using advanced analytics and authentication software that cross-references the provided data with a set of stored information. This technology eliminates  manual ID verification, saving time and improving accuracy. ID verification automation uses artificial intelligence and machine learning to compare identifying credentials against various authenticating sources.   Automated identity verification also comes into play for employment and income verification. Experian VerifyTM enables businesses through precise, real-time employment and income verification, ultimately helping businesses reduce risk, accelerate conversion and remove friction.   For a more comprehensive understanding of automated identity verification, you can visit Experian's Identity Verification Solutions webpage, which provides a deep dive into the intricacies of identity verification, including insights on its importance in modern business operations and how it keeps your business secure.  Benefits of automated identity verification for businesses and consumers   Automated ID verification has revolutionized the way businesses conduct their operations and interact with customers. For businesses, AIV offers a range of benefits such as:  Improved efficiency – businesses can automate the time-consuming process of identity verification, freeing up resources (staff) to focus on other critical tasks.  Enhanced security – the technology ensures that customer data is secure and accurate, minimizing fraud risks and/or data breaches.  Reduced costs – with the process being faster and more secure, costs are reduced as a byproduct.  On the other hand, consumers enjoy a hassle-free experience as they can verify their identity within seconds, without  physical documentation. This is essential for today’s consumers who expect frictionless experiences that keep them and their information safe.   Data from Experian’s annual U.S. Identity and Fraud Report reflects these sentiments: 37% of consumers moved a new account opening process to another organization because of a poor experience; 95% of consumers say it's important to be repeatedly recognized online by businesses; and 60% of consumers are concerned about their online privacy. With automated identity verification, businesses can build trust, streamline their processes, and ultimately improve their bottom line.  Furthermore, automated identity verification is a necessary component for businesses to minimize fraud risks in our evolving digital landscape. Living in an era where cybercrime is rampant, AIV safeguards businesses from potential fraudulent attempts and data breaches that could cause significant financial and reputational damage.   From a compliance standpoint, automated identity verification ensures regulatory compliance, which is critical, considering the stringent regulations regarding customer data protection. Non-compliance can lead to severe legal repercussions and financial penalties. For financial institutions, Know Your Customer (KYC) policies must include Customer Identification Programs. Experian can help across the entire customer journey, from onboarding through portfolio management, while reducing risk of non-compliance and providing seamless authentication.  Common challenges of automated identity verification   As more companies turn to artificial intelligence and automation to deliver superior customer service experiences, the challenges businesses face have multiplied. One of the most common issues is ensuring identity proofing and accurate information protection within their networks. Although account takeover prevention has become more advanced, fraudsters still use increasingly sophisticated methods to circumvent it. As such, businesses must continuously develop new strategies to overcome these challenges, ensuring that their AI-powered solutions continue to provide reliable and secure user experiences.  Types of identity verification solutions   As the digital world continues to evolve, automated identity verification solutions have become a crucial part of online interactions. These solutions not only enhance security measures, but also provide faster and more efficient ways of identifying individuals.   For instance, facial recognition is one example. Experian’s CrossCore® Doc Capture enables confident identity verification via facial recognition, which scans a person's face and compares it to their identification documents. Another type is voice recognition, which uses speech patterns to verify an identity. Additionally, document verification scans and validates various identification documents, such as driver's licenses and passports. It's essential to choose the most suitable AIV solution for your organization to ensure robust and reliable security measures.  How to implement an automated ID verification solution   It’s not new news that identity theft and fraud continue to be major concerns, particularly in an increasingly digital-only world.  Implementing automated identity verification solutions to safeguard against such threats can seem daunting, particularly for businesses with limited IT resources. However, the benefits of automated ID verification, such as increased accuracy and efficiency, make it a worthwhile investment. When choosing a solution,  consider factors such as the level of security provided, ease of implementation and integration with existing systems, and the ability to customize rules and settings. With careful planning and the right solution, , organizations can take a significant step towards improving their security posture and protecting their customers.  Best Practices for automated identity verification  Automated identity verification presents one way that financial institutions can increase automation. In doing so, organizations can improve accuracy, speed, and security in the verification process. One technique that has proven effective is the use of biometric technology, such as facial recognition and fingerprint scanning, to verify a person's identity. Additionally, utilizing various data sources, such as credit bureaus like Experian and government agencies, can increase the accuracy of verification. Implementing these best practices can not only save time and resources but also enhance customer experience by providing a seamless and secure verification process.  In summary, automated identity verification is a vital tool for businesses and consumers to enhance their safety and security when engaging with customers. Automated identity verification streamlines customer processes across the lifecycle by eliminating manual checks and lengthy delays. As technology continues to evolve, it’s important for organizations to remain mindful that the methodologies used within automated identity verification will rapidly change as well. The key is to stay ahead. Automated identity verification solutions offer many advantages for businesses who want to maintain their trustworthiness while staying competitive in an ever-changing market.  To learn more about Experian’s automated identity verification solutions, visit our website.    Learn More *This article includes content created by an AI language model and is intended to provide general information. 

The state of digital banking is a story of fragmentation and technology that's often outdated or poorly integrated. Customer journeys are often suboptimal, and multiple layers of technological solutions often translate to problems like poor data hygiene, lack of regulatory compliance and missed opportunities. In addition, the use of legacy software can make it challenging to integrate up-to-date methods such as AI analytics solutions. However, demand on both the front and back ends for better digital services and more-efficient processes is driving banks to take on digital transformations that will help them stay competitive in an evolving technological landscape. Customers expect a frictionless, personalized and highly functional digital experience. To match strength with digital-native competitors, banks and lenders must transform how their organizations do business. What is digital transformation, and what does it mean for banks and lenders? A comprehensive digital transformation strategy is more than just investing in new digital tools. It's about rebuilding the structure and infrastructure of your business so that online and digital services and processes form the core of your competencies and offerings. Digital transformation is an ongoing journey rather than an end goal. It's a continuous process that iterates as you steadily improve and streamline operations and integrate new and improved technologies. One of the key aspects of digital transformation in banking is better gathering and leveraging of data. Banks, especially larger ones with a longer business history, possess large quantities of data that may be siloed or poorly utilized. By improving how they collect, analyze and make use of data, banks and financial institutions can enhance their decision-making abilities and engage with consumers in a more authentic, personalized way. Perhaps most important, digital transformation is customer-centric. While upgrading, merging and integrating back-end technologies and data solutions is a key component of the process, it's all done with the customer experience top of mind. Centralizing, streamlining and modernizing digital operations help to create a seamless, secure and highly targeted customer journey. The core pillars of digital transformation Multiple core pillars are involved in undergoing a successful digital transformation. Each of these should be integrated into a comprehensive strategy that considers the transformation as an integrated process, rather than a series of individual projects. In fact, one common error banks make when upgrading their digital infrastructure and offerings is failing to coordinate digital initiatives. A true digital transformation is holistic, resulting in apps, infrastructure, digital systems and customer experience platforms that are all part of one coherent, consistent approach. Data: Data is at the heart of digital transformation. It's through maximizing and optimizing usable data that financial institutions can truly make an impact on their ability to reach and connect with target consumers. Using data the right way means prioritizing security and privacy while taking advantage of opportunities to improve consumer targeting and engagement and personalization of offers. Analytics: Data can't do its job if it's not interpreted in a way that makes sense for your business. Quality analytics software and comprehensive analysis are what turn a set of disparate data points into usable information that informs smart decision-making and improves KPIs. Automation: Machine learning is improving by leaps and bounds, and it's only going to get more useful for businesses looking to increase the efficiency of their sales, marketing and engagement efforts. AI solutions are no longer a fringe tool but are quickly becoming part of the mainstream and a key component of digital strategies. Customers: With the array of digital tools available today, it's easy to lose sight of the main purpose of your business — connecting with people. Customers today expect digital engagement experiences that feel personalized and real, which is why a consistent, appealing digital customer journey should be top of mind in any digital transformation strategy. How can banks benefit? New, digitally native fintech solutions abound in the contemporary landscape. Overall, they tend to be highly competent when it comes to making the most of state-of-the-art tools like artificial intelligence, mobile apps and blockchain. By combining their brand longevity with a well-executed digital transformation, traditional banks can capitalize on their established reputations by reaching consumers with compelling offerings that utilize and are based on best-in-class digital tools and data analysis. Digital transformation in banking can have numerous benefits. For one, operations will be more streamlined. For another, enhanced security will make customers feel more secure while minimizing losses from fraud. In addition, integrating top-of-the-line data and analysis will result in better overall decision-making. The ultimate goal? Boosting lead generation and conversion rates and improving customer onboarding while reducing churn, thereby maximizing the efficiency of budget spend across multiple departments, from marketing to customer service. Get started with Experian Implementing a digital transformation that truly improves your business can be a daunting task, but it's achievable with the right partner. Experian's connectable and configurable solutions and technology can help drive your digital transformation. With offerings like our cloud platform solutions, you'll be well-positioned to move forward and take advantage of up-to-date technologies to serve your customers better. Learn more about how you can benefit from the digital transformation in banking. Start your digital transformation journey

Americans swipe, tap or insert their debit and credit cards at supermarkets, gas stations, restaurants, hotels and ATMs, conducting more than 74 million daily transactions.¹ Despite the volume of transactions, just 23% of banking customers give their bank high marks for its range of products, services and financial advice.² A hyper-digital, ever-changing banking industry means that there are more choices for financial service providers than ever before — and customers are taking full advantage of the options. On average, consumers have more than six different financial products and 82% of consumers between the ages of 18 and 24 acquired financial services products from new providers in the past 12 months.² Digital transformation for banks is more crucial than ever, with some studies showing that 78% of bank customers prefer to access their accounts via a website or mobile app (with less than half of those surveyed ranking branch access as an important feature when shopping for a new checking account).³ Banks must embrace innovative strategies to elevate the banking customer experience in a competitive market. Here are some ways to boost customer retention and drive profitable growth. Rethink processes Complex processes and excessive paperwork needed to open accounts, approve credit cards and process loan applications can frustrate customers. In 2022, up to 60% of consumers said they would abandon the onboarding process to open a digital bank account if the process took longer than five minutes,4 which in turn, can lead to lost revenue.5 Digital transformation initiatives can resolve these issues to improve the customer experience. Banks that leverage solutions, like artificial intelligence and automated data-driven decisioning solutions, to facilitate faster, more streamlined services can reduce friction, expedite processes and decrease wait times, resulting in improved customer satisfaction and retention. Reduce fragmentation Financial services are more fragmented than ever. Retail banking customers often use different providers for their checking and savings accounts, credit cards, investments, mortgages and other banking products. The options to access those accounts are also diverse, with customers choosing from brick-and-mortar branches, websites and mobile devices. Increased fragmentation means that the need to create an omnichannel experience should be top of mind for lenders. One survey found that 70% of consumers rated a consistent experience across channels as “extremely important" or “very important" when selecting their primary bank.6 Additionally, the current retail banking landscape often fails to reward consumers for loyalty. Fewer than 15% of banks provide comprehensive rewards to those who use a single bank for multiple products or services, even though reducing fragmentation and taking a holistic approach to meeting customer needs can provide a competitive advantage.² Personalize the digital experience While digital banking has reduced face-to-face interaction between banks and customers,² consumers still expect a personalized banking experience. Their top demands for personalization tools are ones that can help them avoid fees and deliver automatic account alerts.7 Experian has shown that using data analytics can lead to an improved understanding of customer needs and preferences, while customer segmentation enables the creation of targeted marketing campaigns, customized product offerings and tailored financial advice. These efforts towards a more personalized banking experience help increase customer satisfaction and loyalty. Provide more touchpoints An increasing number of branch closures and greater demand for digital banking services mean that just 3% of banking transactions are conducted in person.² Customers are more willing to use digital channels for services like opening accounts and applying for loans.8 Banks can promote credit offers and product recommendations via email, social media and mobile banking applications while providing real-time digital customer experiences and prioritizing consistency across channels. Embracing a multichannel approach to marketing can help banks achieve better results, making it easier to cross-sell customers, amplify offers and meet consumer expectations for a personalized digital experience. Go beyond banking Experian research found that 80% of customers felt their relationships with financial institutions were “purely transactional," but the customer experience in banking is about more than deposits, withdrawals and interest payments. Customers want resources and information to improve their financial well-being — and providing it can build trust, improve customer retention and boost revenue. Although more than two-thirds of customers expect companies to understand their needs and expectations, just three in 10 banking customers felt their financial providers met their demands.9 Using digital channels to provide education might be more effective than encouraging appointments with customer service representatives, especially for the 29% of consumers who don't feel comfortable asking about financial products.10 These tactics can help you: Leverage artificial intelligence to provide educational resources and personalized financial advice. Monitor user transactions for unusual activities and push information about online security or fraud protection. Employ chatbots to provide investment information and credit score monitoring and respond to questions about products ranging from mortgages to credit cards. Enhance your customer retention strategies by focusing on credit education and helping customers at every stage of their financial lives. Foster a customer-centric culture Globally, banks have invested $124 billion in artificial intelligence, machine learning and other technologies to make retail banking services more efficient and effective.² Personalization is still imperative, and putting the customer first must remain the highest priority. For large, multichannel banks, a mere one-point improvement in the customer experience score can lead to an incremental $123 million in revenue; the same one-point increase in the customer experience score can generate $92 million in revenue for a direct bank.11 Achieving those results requires a solid strategy for an improved banking customer experience. Experian leverages customer-level analytics and provides comprehensive solutions to expand digital transformation efforts, drive acquisition and improve customer retention. To learn more about solutions, visit us online. 1Federal Reserve (2023). Commercial Automated Clearinghouse Transactions Processed by the Federal Reserve 2Accenture (2023). Global Banking Customer Study 3Forbes Advisor (2023). U.S. Consumer Banking Statistics 4Digital Banking Report (2022). Best Practices for Successful Digital Account Opening 5Abbyy (2022). State of Intelligent Automation Report, Customer Onboarding Pain Points and Drivers Q4-2022 6Deloitte Insights (2018). Accelerating digital transformation in banking 7D. Power (2022). U.S. Retail Banks Struggle to Differentiate, Deliver Meaningful Customer Experience as Economy Sours, J.D. Power Finds 8McKinsey & Company (2022). Best of both worlds: Balancing digital and physical channels in retail banking 9Experian (2022). Building customer loyalty through financial education 10Milken Institute (2021). Financial Literacy in the United States 11Forrester (2022). Who Does it Well and Why it Matters  

This article was updated on August 24, 2023. The continuous shift to digital has made a tremendous impact on consumer preferences and behaviors, with 81% thinking more highly of brands that offer multiple digital touchpoints. As a result, major credit card issuers are making creative pivots to their credit marketing strategies, from amplifying digital features in their card positioning to promoting partnerships and incentives on digital channels. But as effective as it is to reach consumers where they most frequent, credit card marketing will need to be more customer-centric to truly captivate and motivate audiences to engage.  So, what does this innovative period of credit marketing mean for financial institutions? How can these institutions stand out in a competitive, ever-changing market?  To target and acquire the right consumers, here are three credit card marketing strategies financial institutions should consider:  Maximize share of voice through targeted approaches  About half of consumers say personalization is the most important aspect of their online experience. Because today’s consumers are now expecting to engage digitally with brands, it’s important for financial institutions to not only be seen and mentioned on the right digital channels, but to deliver content that will resonate with their specific audiences. To do this, lenders must leverage fresh, comprehensive data sets to gain a more holistic view of consumers. This way, they can create targeted, customer-centric prescreen campaigns, allowing for enhanced personalization and increased response rates.  Seek new opportunities to provide value to customers  77% of Gen Zers believe having an established credit history is important to being less financially dependent on their parents. Changes in consumer needs and lifestyles provide great opportunities to deliver value to customers. For example, younger consumers starting their credit journeys may look for brands that offer financial education or tools to help them build credit. Financial institutions that are open to pivoting their strategies to adapt to these needs and behaviors are those that will succeed in attracting new customers and maintaining long-lasting relationships with existing ones.  Amplify points of differentiation in their products and marketing  Before buying a product, consumers likely want to know more about the items they are purchasing and how they compare to different players in the market. To help set their products apart from other offerings, financial institutions should clearly define their product’s key differentiators and convey them in a personalized and compelling manner.  Enhance your credit card marketing campaigns  From identifying the right prospects to saturating your targeting criteria with data-rich insights, Experian offers credit marketing solutions to help you level up your campaigns and stand out from the competition. Learn more

This article was originally published on multifamilyinsiders.com One of the challenges currently facing the rental housing industry is the amount of lease application fraud. An Entrata study found a 111% increase in lease application fraud between 2019 and 2020. In the same study, 55% of surveyed apartment managers and rental operators said their properties experience fraudulent lease application attempts every few months, and 15% said their communities were subjected to multiple attempts each month. One-third of respondents described themselves as "very concerned" about application fraud. Just as alarming as the rise in attempts is the apparent likelihood of success. In the study, 65% of apartment managers said they are not confident in their current fraud prevention efforts. Some applicants can use a range of tools to commit fraud such as fake pay stubs, bank statements, employment records, and other falsified documents. Unfortunately, readily available computer technology makes it all too easy for applicants to produce these falsified documents. Tools to fight against fraud Apartment communities that rely on an overly manual screening process may find themselves at a disadvantage in the current landscape. Relying on associates to manually verify things like income and employment history can increase the risk of a deceitful applicant being successful. In addition, these processes can be extraordinarily time-consuming, which means leasing associates have less bandwidth for their many other important duties and responsibilities. Not to mention, the units stay unoccupied while these time-consuming verifications are being done manually. Among the general screening technologies that operators should consider: Automated verification of income, assets and employment — These solutions eliminate the need for operators to collect this kind of documentation from applicants. Furthermore, it eliminates the opportunity for applicants to supply falsified supporting documentation. Frictionless authentication — A multi-layered identity verification process for those applying for rental housing, frictionless authentication detects the subtle and not-so-subtle signs that an applicant is, to one degree or another, using a false identity. By highlighting discrepancies, the process assigns a “score” to quantify the likelihood that misrepresentation is taking place. Additional confirmation of the applicant’s identity can be completed using a one-time passcode (OTP) or knowledge-based authentication (KBA). This technology also uses device intelligence to recognize the risks associated with the physical devices (such as computers, tablets, and smartphones) that consumers use for online applications to identify potential imposters. In today's landscape, apartment owners and operators need to make sure they're protecting themselves against fraudulent applicants, who may not fulfill their financial obligations as outlined in their leases. By embracing the ever-growing array of advanced screening tools and technologies, owners and operators can achieve that protection and reduce their risk significantly — and save their associates time and energy.

Investing in a strong customer acquisition strategy is critical to attracting leads and converting them into high-value customers. In this blog post, we’ll be focusing on one of the first stages of the customer acquisition process: the application stage. Challenges with online customer application processes When it comes to the customer application stage, speed, ease, and convenience are no longer nice-to-haves — they are musts. But various challenges exist for lenders and consumers in terms of online credit or account application processes, including: Limited digital capabilities. Consumers have grown more reliant on digital channels, with 52% preferring to use digital banking options over banking at branches. That said, financial institutions should prioritize the digital customer experience or risk falling behind the competition. The length of applications. Whether it’s a physical or digital application, requiring consumers to provide a substantial amount of information about themselves and their past can be frustrating. In fact, 67% of consumers will abandon an application if they experience complications. Potential human error. Because longer, drawn-out applications require various steps and data inputs, consumers may leave fields blank or make errors along the way. This can create more friction and delays as consumers may potentially be driven offline and into branches to get their applications sorted out. Improve the speed and accuracy of online credit applications Given that consumers are more likely to abandon their applications if their experience is friction-filled, financial institutions will need an automated, data-driven solution to simplify and streamline the online form completion process. Some of the benefits of leveraging an automated solution include: Improved customer experiences. Shortening time-to-value starts with faster decisioning. By using accurate consumer data and automation to prefill parts of the online credit application, you can reduce the amount of information applicants are required to enter, leading to lower abandonment rates, less potential for manual error, and enhanced user experiences. Fraud prevention. Safeguarding consumer information throughout the credit application process is crucial. By leveraging intelligent identity verification solutions, you can securely and compliantly identify consumer identities while ensuring data isn’t released in risky situations. Then by using identity management solutions, you can gain a connected, validated customer view, resulting in minimized end-user friction. Faster approvals. With automated data prefill and identity verification, you can process applications more efficiently, leading to faster approvals and increased conversions. Choosing the right partner Experian can help optimize your customer application process, making it faster, more efficient, and less error prone. This way, you can win more customers and improve digital experiences. Learn more about Experian’s customer acquisition solutions.