Whenever someone checks in for a flight, airport security needs to establish their identity. Prior to boarding the plane, passengers are required to show a government-issued ID. Agents check IDs for validity and compare the ID picture to the face of the person standing in front of them. This identity proofing is about making sure that would-be flyers really are who they claim to be. But what about online identity proofing? That’s much more challenging. Online banks certainly want to make sure they know a person’s identity before giving them access to their account. But for other online services, it’s fine to remain anonymous. The amount of risk involved in the engagement directly ties to the amount of verification and assurance needed for the individual. Government agencies care very much about identity. They won’t — and shouldn’t — issue a tax refund, provide a driver’s license or allow someone to sign up for Social Security benefits before they’re certain that the claimant’s identity is verified. Since we increasingly expect the same online user experience from government service providers as from online banks, hotel websites and retailers, this poses a challenge. How do government agencies establish a sufficient level of assurance for an online identity without sending their customers to a government office for face-to-face identity verification? To answer this challenge, the National Institute of Standards and Technology (NIST) has developed Digital Identity Guidelines. In its latest publication, SP 800-63-3, NIST helps government agencies implement their digital services while still mitigating the identity risks that come with online service provision. The ability to safely sign up, transact and interact with a government agency online has many benefits. Applying for something like unemployment insurance online is faster, cheaper and more convenient than using paper and waiting in line at a government field office. And for government agencies themselves, providing online services means that they can improve customer satisfaction levels while reducing their costs and subsequent bureaucracy. CrossCore®, was recently recognized by the independent Kantara Initiative for its conformance with NIST’s Digital Identity Guidelines for Identity Assurance (IAL2). Our document verification solution combines authoritative sources, machine learning and facial recognition technology to identify people accurately using photo-based government identification like a driver’s license or passport. The best part? Users can verify their identity in about 60 seconds, at whatever location they prefer, using their personal smartphone.

There’s recently been a significant amount of discussion about the stability of the automotive finance industry. Many fear the increase in the volume of delinquent U.S. automotive loans may be an early stage harbinger of the downfall of the automotive industry. But, the fact is, that’s not entirely true. While we certainly want to keep a close eye on the volume of delinquent loans, it’s important to put these trends into context. We’ve seen a steady increase in the volume of outstanding loan balances for the past several years – though the growth has slowed the past few quarters. And while much of the increase is driven by higher loan amounts, it also means there’s been an overall higher volume of vehicle buyers leaning on automotive lenders to finance vehicles. In fact, findings from our Q4 2018 State of the Automotive Finance Market Report show 85.1 percent of all new vehicle purchases were financed in Q4 2018 – compare that to 81.4 percent in Q4 2010 and 78.2 percent in Q4 2006. Suffice it to say, more financed vehicles will undoubtedly lead to more delinquent loans. But that also means, there is a high volume of car buyers who continue to pay their automotive loans in a timely manner. Through Q4 2018, there were nearly 86 million automotive loans and leases that were in good standing. With a higher volume of automotive loans than in the past, we should pay close attention to the percentage of delinquent loans compared to the overall market and compare that to previous years. And when we examine findings from our report, the percentage of automotive loans and leases that were 30-days past due dropped from 2.36 percent to 2.32 percent compared to a year ago. When we look at loans and leases that were 60-days past due, the percentages are relatively stable (up slightly from 0.76 percent to 0.78 percent compared to a year ago). It’s worth noting, these percentages are well below the high-water mark set during Q4 2009 when 3.30 percent of loans were 30-days delinquent and 0.94 percent of loans were 60-days delinquent. But, while the rate of delinquency is down and/or relatively stable year-over-year, it has trended upward since Q4 2015 – we’ll want to stay close to these trends. That said, much of the increase in the percentage of 60-day delinquent automotive loans is a result of a higher percentage of deep subprime loans from previous years – high-risk originations that become delinquent often occur more than 16 months after the origination. Additionally, the percentage of deep subprime originations has steadily decreased over the past two years, which could lead to a positive impact on the percentage of delinquent automotive loans. Despite rising automotive loan amounts and monthly payments, the data shows consumers appear to be making their payments on-time – an encouraging sign for automotive lenders. That said, lenders will want to continue to keep a close eye on all facets of car buyers’ payment performance moving forward – but it is important to put it into context. A clear understanding of these trends will better position lenders to make the right decisions when analyzing risk and provide consumers with comprehensive automotive financing options. To learn more about the State of the Automotive Finance Market report, or to watch the webinar, click here.    

Although half of businesses globally report an increase in fraud management over the past 12 months, many still experience fraud losses and attacks. To help address these challenges, Experian held its first-ever Fintech Fraud & Identity Meetup on February 5 in San Francisco, Calif. The half-day event was aimed at offering insights on the main business drivers of fraud, market trends, challenges and technology advancements that impact identity management and fraud risk strategy operations. “We understand the digital landscape is changing – inevitably, with technology enhancements come increased fraud risk for businesses operating in the online space,” said Jon Bailey, Experian’s Vice President of Fintech. “Our focus today is on fraud and identity, and providing our fintech customers with the tools and insights needed to grow and thrive.” The meetup was attended by number of large fintech companies with services spanning across a broad spectrum of fintech offerings. To kick off the event, Tony Hadley, Experian’s Senior Vice President of Government & Regulatory Affairs, provided an update on the latest regulatory news and trends impacting data and the fintech space. Next followed a fraud and identity expert panel, which engaged seasoned professionals in an in-depth discussion around two main themes 1) fraud trends and risk mitigation; and 2) customer experience, convenience, and trust. Expert panelists included: David Britton, Experian’s Vice President of Industry Solutions; Travis Jarae, One World Identity’s Founder & CEO; George Kurtyka, Joust’s Co-Founder & COO; and Filip Verley, Airbnb’s Product Manager. “The pace of fraud is so fast, by the time companies implement solutions, the shelf-life may already be old,” Britton said. “That is the crux – how to stay ahead. The goal is to future-proof your fraud strategy and capabilities.” At the close of the expert panel, Kathleen Peters, Experian’s Senior Vice President Head of Fraud and Identity, demoed Experian’s CrossCore™ solution – the first smart, open, plug-and-play platform for fraud and identity services. Peters began by stating, “Fraud is constant. Over 60% of businesses report an increase in fraud-related losses over the past year, with the US leading the greatest level of concern. The best way to mitigate risk is to create a layered approach; that’s why Experian invented CrossCore.” With the sophistication of fraudsters, it’s no surprise that many businesses are not confident with the effectiveness of their fraud strategy. Learn more about how you can stay one step ahead of fraudsters and position yourself for success in the ever-changing fraud landscape; download Experian’s 2019 Global Identity and Fraud Report here. For an inside look at Experian’s Fintech Fraud & Identity Meetup, watch our video below.

2018 was a whirlwind of a year – though it was not surprising when Google’s 2018 “most-searched” list showed Fornite GIFs ruled the internet, Black Panther was the most-Googled movie, and the Keto diet was trending (particularly in late December and early January, go figure). But, while Google’s most-searched terms of 2018 present pure pop-culture entertainment, they miss the mark on the trends we find most meaningful being principals of the financial services industry. What about the latest news in fintech? According to Business Insider, fintech companies secured $57.9 billion in funding in the first half of 2018 alone, nearing the previous annual record of $62.5 billion set in 2015. Taking it a step further, CBInsights reports that 24 of 39 fintech unicorns are based in North America. We won’t blame Google for this oversight. Faced with the harsh reality that the “most-searched” results are based on raw-data, perhaps it’s possible that people really do find Fortnite more exciting than financial services trends – but not us at Experian. We have been closely following disruption in the financial services space all while leading the charge in data innovation. When competing in environments where financial institutions vie for customer acquisition and brand loyalty, digital experience is not enough. Today’s world demands finance redefined – and fintechs have answered the call. Fintechs are, by far, among the most innovative technology and data-driven companies in the financial services industry. That’s why we built a team of seasoned consultants, veteran account executives and other support staff that are 100% dedicated to supporting our fintech partners. With our expert team and a data accuracy rate of 99.9%, there isn’t a more reliable fintech source. Perhaps this is one financial services trend that Google can’t ignore (we see you Google)! For more information regarding Experian’s fintech solutions, check out our video below and visit Experian.com/fintech.

When it comes to relationships and significant others, debt is topping lists of what people look for - or don't look for - in their partner. Where looks, pedigree, or career trajectory were previous motivation drivers for mate selection (or at least companionship), recent studies indicate debt is a deal-breaker for many looking for love. Late payments from lifestyles past, less-than-stellar credit scores, and cancelled credit cards are all exhibits of debt and destruction influencing personal relationships, not to mention the relationship financial institutions have with these consumers. Are certain relationships – or rather, specific partners – more likely to carry debt? Women were found to be more financially vulnerable, according to the Survey of Consumer Finances, conducted by the Federal Reserve, that examined how men and women who had never been married felt about debt. Recent Experian data found that while both men and women share the same amount of revolving utilization at 30%, men carry more debt than women, $27,067 compared to $23,881 for women. Men are also more likely to have larger mortgage debt at $214,908 compared to $198,622 for women. Women have more credit cards and more retail cards but lower balances than men on both. From a generational viewpoint, Gen X and Boomer generations have a higher than average number of credit cards and higher than average number of retail cards (and the highest average balance on credit cards and retail cards). Gen X also has the highest average debt by generation for both non-mortgage and mortgage debt. While Boomer and Silent Generations have lower than average mortgage debt, the boomer generation still has higher than average non-mortgage debt. With nearly 3 in 4 American adults saying they would reconsider their romantic relationship because of their partner’s debt, consumers should consider revamping their balance sheets before updating their online dating profiles. For the hopeless romantics, the star-crossed lovers, and those instead celebrating Singles Awareness Day whose finances could use a little love, perhaps a digital collections portal or personalized options to consolidate debt might speak to their love language. Or, in the meantime, maybe a list of the top cities for singles with the best credit scores could be a start.

Like every other industry, the automotive market is driven by consumer preferences and behavior. While there are a myriad of options to choose from, fuel-type seems to dominate media headlines as a hot topic of conversation among industry pundits and consumers, alike. Little surprise then that alternative fuel vehicles, which include diesels and hybrids, have maintained a steady demand over the past few years. But, there’s a specific segment that’s beginning to emerge. As we detailed in our earlier blog series, electric vehicles (EVs) are began to stand out as a prominent alternative fuel vehicle. And during Q3 2018, we saw more of the same. EVs held 1.8 percent share of total vehicle registrations. While that number may seem small, consider this.  Just two years ago, in 2016, EVs comprised only 0.5 percent of registrations, growing at a much slower pace since 2014, when it was 0.4 percent. It’s worth noting that gasoline-powered cars still dominate the market, making up 92.9 percent of registered vehicles through Q3 2018. But, the demand for alternative fuel type options should not be underestimated. Alternative fuel vehicles are becoming a significant segment in today’s auto market, and the large growth in EVs are a testament to that growth. While EVs are proving to be a popular option compared to other alternative fuel types, other options remained steady. Diesel vehicles maintained 2.8 percent of the market year-over-year, while hybrid vehicles saw a slight increase since 2017, growing from 2.6 to 2.8 percent of the market. A picture of the alternative fuel buyer So, who’s investing in these alternative fuel vehicles? We see that most buyers tend to be married, single family home owners with a college education, and belong to either the Baby Boomer generation or Gen X. It’s interesting to note that EVs make up a notable percentage of registrations of alternative fuel type preferences across generational car buyers, according to Q3 registration data. Among Baby Boomers, EVs fall second to hybrids, accounting for 1.0 percent of registered alternative fuel type vehicles compared to 1.2 percent respectively. But, EVs made up the biggest share of alternative fuel type registrations among Millennials (1.1 percent) and Gen X’ers (1.2 percent). With the number of vehicle options available on the market today, EVs stand out as a segment to watch within the auto industry. There’s a greater story beyond the numbers and understanding how to leverage the data at hand can provide the industry with a greater understanding of the EV market and its potential. To learn more about the electric vehicle market and other alternative fuel type vehicles, view the full Q3 2018 Automotive Market Trends Analysis webinar.

How can fintech companies ensure they’re one step ahead of fraudsters? Kathleen Peters discusses how fintechs can prepare for success in fraud prevention.

From a capricious economic environment to increased competition from new market entrants and a customer base that expects a seamless, customized experience, there are a host of evolving factors that are changing the way financial institutions operate. Now more than ever, financial institutions are turning to their data for insights into their customers and market opportunities. But to be effective, this data must be accurate and fresh; otherwise, the resulting strategies and decisions become stale and less effective. This was the challenge facing OneMain Financial, a large provider of personal installment loans serving 10 million total customers across more than 1,700 branches—creating accurate, timely and robust insights, models and strategies to manage their credit portfolios. Traditionally, the archive process had been an expensive, time-consuming, and labor-intensive process; it can take months from start to finish. OneMain Financial needed a solution to reduce expenses and the time involved in order to improve their core risk modeling.   In this recent IDC Customer Spotlight, sponsored by Experian, "Improving Core Risk Modeling with Better Data Analysis," Steven D’Alfonso, Research Director spoke with the Senior Managing Director and head of model development at OneMain Financial who turned to Experian’s Ascend Analytical Sandbox to improve its core risk modeling through reject inferencing. But OneMain Financial also realized additional benefits and opportunities with the solution including compliance and economic stress testing. Read the customer spotlight to learn more about the explore how OneMain Financial: Reduced expense and effort associated with its archive process Improved risk model development timing from several months to 1-2 weeks Used Sandbox to gain additional market insight including: market share, benchmarking and trends, etc. Read the Case Study

A closer look at the data shows GM’s losses might not be particularly significant, despite the announcement of discontinued models.

Perhaps more than ever before, technology is changing how companies operate, produce and deliver products and services to their customers. Similarly, technology is also driving a shift in customer expectation in how, when and where they consume products and services. But these changes aren’t just relegated to the arenas where tech giants with household names, like Amazon and Google, play. Likewise, financial institutions of every size are also fielding the changes brought on by innovations to the industry in recent years. According to this report by PWC, 77% of firms plan on dedicating time and budgets to increase innovation. But what areas make the most sense for your business? With a seemingly constant shift in consumer and corporate focus, it can be difficult to know which technological advancements are imperative to your company’s success and which are just the latest fizzling buzzword. As you evaluate innovation investments for your organization in 2019 and beyond, here’s a list of four technology innovations that are already changing the financial sector or will change the banking landscape in the near future. The APIs of Open Banking Ok, it’s not a singular innovation, so I’m cheating a bit here, but it’s a great place to begin the conversation because it comprises and sets the stage for many of the innovations and technologies that are in use today or will be implemented in the future. Created in 2015, the Open Banking Standard defined how a bank’s system data or consumer-permissioned financial data should be created, accessed and shared through the use of application programming interfaces or APIs. When financial institutions open their systems up to third-party developer partners, they can respond to the global trends driving change within the industry while greatly improving the customer experience. With the ability to securely share their financial data with other lenders, greater transparency into the banking process, and more opportunities to compare product offerings, consumers get the frictionless experience they’ve come to expect in just about every aspect of life – just not necessarily one that lenders are known for. But the benefits of open banking are not solely consumer-centric. Financial institutions are able to digitize their product offerings and thus expand their market and more easily share data with partners, all while meeting clients’ individualized needs in the most cost-effective way. Biometrically speaking…and smiling Verifying the identity of a customer is perhaps one of the most fundamental elements to a financial transaction. This ‘Know Your Customer’ (KYC) process is integral to preventing fraud, identity theft, money laundering, etc., but it’s also time-consuming and inconvenient to customers. Technology is changing that. From thumbprint and, now, facial recognition through Apple Pay, consumers have been using biometrics to engage with and authorize financial transactions for some time now. As such, the use of biometrics to authenticate identity and remove friction from the financial process is becoming more mainstream, moving from smartphones to more direct interaction. Chase has now implemented voice biometrics to verify a consumer’s identity in customer service situations, allowing the company to more quickly meet a customer’s needs. Meanwhile, in the US and Europe, Visa is testing biometric credit cards that have a fingerprint reader embedded in the card that stores his or her fingerprint in order to authenticate their identity during a financial transaction. In China, companies like Alipay are taking this to the next level by allowing customers to bypass the phone entirely with its ‘pay with a smile’ service. First launched in KFC restaurants in China, the service  is now being offered at hospitals as well. How, when and where a consumer accesses their financial institution data actually creates a digital fingerprint that can be verified. While facial and vocal matching are key components to identity verification and protecting the consumer, behavioral biometrics have also become an important part of the fraud prevention arsenal for many financial institutions. These are key components of Experian’s CrossCore solution, the first open fraud and identity platform partners with a variety of companies, through open APIs discussed above. Not so New Kid on the Block(chain) The first Bitcoin transaction took place on January 12, 2009. And for a number of years, all was quiet. Then in 2017, Bitcoin started to blow up, creating a scene reminiscent of the 1850s California gold rush. Growing at a seemingly exponential rate, the cryptocurrency topped out at a per unit price of more than $20,000. By design cryptocurrencies are decentralized, meaning they are not controlled or regulated by a single entity, reducing the need for central third-party institutions, i.e. banks and other financial institutions to function as central authorities of trust. Volatility and regulation aside, it’s understandable why financial institutions were uneasy, if not skeptical of the innovation. But perhaps the most unique characteristic of cryptocurrencies is the technology on which they are built: blockchain. Essentially, a blockchain is just a special kind of database. The database stores, validates, transfers and keeps a ledger of transfers of encrypted data—records of financial transfers in the case of Bitcoin. But these records aren’t stored on one computer as is the case with traditional databases. Blockchain leverages a distributed ledger or distributed trust approach where a full copy of the database is stored across many distributed processing nodes and the system is constantly checking and validating the contents of the database. But a blockchain can store any type of data, making it useful in a wide variety of applications including tracking the ownership digital or physical assets or the provenance of documents, etc. From clearing and settlements, payments, trade finance, identity and fraud prevention, we’re already seeing financial institutions explore and/or utilize the technology. Santander was the first UK bank to utilize blockchain for their international payments app One Pay FX. Similarly, other banks and industry groups are forming consortiums to test the technology for other various uses. With all this activity, it’s clear that blockchain will become an integral part of financial institutions technology and operations on some level in the coming years. Robot Uprising Rise in Robots While Artificial Intelligence seems to have only recently crept into pop-culture and business vernacular, it was actually coined in 1956 by John McCarthy, a researcher at Dartmouth who thought that any aspect of learning or intelligence could essentially be taught to a machine. AI allows machines to learn from experience, adjust to new inputs and carry out human-like tasks. It’s the result of becoming ‘human-like’ or the potential to become superior to humans that creeps out people like my father, and also worries others like Elon Musk. Doomsday scenarios a la Terminator aside, it’s easy to see how the tech can and is useful to society. In fact, much of the AI development done today uses human-style reasoning as a model, but not necessarily the ultimate aim, to deliver better products and services. It’s this subset of AI, machine learning, that allows companies like Amazon to provide everything from services like automatic encryption in AWS to products like Amazon Echo. While it’s much more complex, a simple way to think about AI is that it functions like billions of conditional if-then-else statements working in a random, varied environment typically towards a set goal. Whereas in the past, programmers would have to code these statements and input reference data themselves, machine learning systems learn, modify and map between inputs and outputs to create new actions based on their learning. It works by combining the large amounts of data created on a daily basis with fast, iterative processing and intelligent algorithms, allowing the program to learn from patterns in the data and make decisions. It’s this type of machine learning that banks are already using to automate routine, rule-based tasks like fraud monitoring and also drive the analytical environments used in their risk modeling and other predictive analytics. Whether or not you’ve implemented AI, machine learning or bot technology into your operations, it’s highly likely your customers are already leveraging AI in their home lives, with smart home devices like Amazon Echo and Google Home. Conversational AI is the next juncture in how people interface with each other, companies and life in general. We’re already seeing previews of what’s possible with technologies like Google Duplex. This has huge implication for the financial services industry, from removing friction at a transaction level to creating a stickier, more engaging customer experience. To that end, according to this report from Accenture, AI may begin to provide in-the-moment, holistic financial advice that is in a customer’s best interest.   It goes without saying that the market will continue to evolve, competition will only grow more fierce, consumer expectation will continue to shift, and regulation will likely become more complex. It’s clear technology can be a mitigating factor, even a competitive differentiator, with these changing industry variables. Financial institutions must evolve corporate mindsets in their approach to prioritize innovations that will have the greatest enterprise-wide impact. By putting together an intelligent mix of people, process, and the right technology, financial institutions can better predict consumer need and expectation while modernizing their business models.

Alternative credit data and trended data each have advantages to lenders and financial institutions. Is there such a thing as the MVD (Most Valuable Data)? Get Started Today When it comes to the big game, we can all agree the score is the last thing standing; however, how the two teams arrived at that score is arguably the more important part of the story. The same goes for consumers’ credit scores. The teams’ past records and highlight reels give insight into their actual past performance, while game day factors beyond the stat sheets – think weather, injury rehab and personal lives – also play a part. Similarly, consumers’ credit scores according to the traditional credit file may be the dependable source for determining credit worthiness. But, while the traditional credit file is extensive, there is a playbook of other, additional information you can arm yourself with for easier, faster and better lending decisions. We’ve outlined what you need to create a win-win data strategy: Alternative credit data and trended data each have unique advantages over traditional credit data for both lenders and consumers alike. How do you formulate a winning strategy? By making sure you have both powerhouses on your roster. The results? Better than that game-winning touchdown and hoisting the trophy above your head – universe expansion and the ability to lend deeper. Get Started Today

Are You #TeamTrended or #TeamAlternative? There’s no such thing as too much data, but when put head to head, differences between the data sets are apparent. Which team are you on? Here’s what we know: With the entry and incorporation of alternative credit data into the data arena, traditional credit data is no longer the sole determinant for credit worthiness, granting more people credit access. Built for the factors influencing financial health today, alternative credit data essentially fills the gaps of the traditional credit file, including alternative financial services data, rental payments, asset ownership, utility payments, full file public records, and consumer-permissioned data – all FCRA-regulated data. Watch this video to see more:    Trended data, on the other hand shows actual, historical credit data. It provides key balance and payment data for the previous 24 months to allow lenders to leverage behavior trends to determine how individuals are utilizing their credit. Different splices of that information reveal particular behavior patterns, empowering lenders to then act on that behavior. Insights include a consumer’s spend on all general purpose credit and charge cards and predictive metrics that identify consumers who will be in the market for a specific type of credit product. In the head-to-head between alternative credit data and trended data, both have clear advantages. You need both on your roster to supplement traditional credit data and elevate your game to the next level when it comes to your data universe. Compared to the traditional credit file, alternative credit data can reveal information differentiating two consumers. In the examples below, both consumers have moderate limits and have making timely credit card payments according to their traditional credit reports. However, alternative data gives insight into their alternative financial services information. In Example 1, Robert Smith is currently past due on his personal loan, whereas Michelle Lee in Example 2 is current on her personal loan, indicating she may be the consumer with stronger creditworthiness.   Similarly, trended data reveals that all credit scores are not created equal. Here is an example of how trended data can differentiate two consumers with the same score. Different historical trends can show completely different trajectories between seemingly similar consumers.   While the traditional credit score is a reliable indication of a consumer’s creditworthiness, it does not offer the full picture. What insights are you missing out on? Go to Infographic Get Started Today

Experian Boost gives consumers greater control over their credit profiles by allowing them to add non-traditional credit information to their Experian credit file.

From the time we wake up to the minute our head hits the pillow, we make about 35,000 conscious and unconscious decisions a day. That’s a lot of processing in a 24-hour period. As part of that process, some decisions are intuitive: we’ve been in a situation before and know what to expect. Our minds make shortcuts to save time for the tasks that take a lot more brainpower. As for new decisions, it might take some time to adjust, weigh all the information and decide on a course of action. But after the new situation presents itself over and over again, it becomes easier and easier to process. Similarly, using traditional data is intuitive. Lenders have been using the same types of data in consumer credit worthiness decisions for decades. Throwing in a new data asset might take some getting used to. For those who are wondering whether to use alternative credit data, specifically alternative financial services (AFS) data, here are some facts to make that decision easier. In a recent webinar, Experian’s Vice President of Analytics, Michele Raneri, and Data Scientist, Clara Gharibian, shed some light on AFS data from the leading source in this data asset, Clarity Services. Here are some insights and takeaways from that event. What is Alternative Financial Services? A financial service provided outside of traditional banking institutions which include online and storefront, short-term unsecured, short-term installment, marketplace, car title and rent-to-own. As part of the digital age, many non-traditional loans are also moving online where consumers can access credit with a few clicks on a website or in an app. AFS data provides insight into each segment of thick to thin-file credit history of consumers. This data set, which holds information on more than 62 million consumers nationwide, is also meaningful and predictive, which is a direct answer to lenders who are looking for more information on the consumer. In fact, in a recent State of Alternative Credit Data whitepaper, Experian found that 60 percent of lenders report that they decline more than 5 percent of applications because they have insufficient information to make a loan decision. The implications of having more information on that 5 percent would make a measurable impact to the lender and consumer. AFS data is also meaningful and predictive. For example, inquiry data is useful in that it provides insight into the alternative financial services industry. There are also more stability indicators in this data such as number of employers, unique home phone, and zip codes. These interaction points indicate the stability or volatility of a consumer which may be helpful in decision making during the underwriting stage. AFS consumers tend to be younger and less likely to be married compared to the U.S. average and traditional credit data on File OneSM . These consumers also tend to have lower VantageScore® credit scores, lower debt, higher bad rates and much lower spend. These statistics lend themselves to seeing the emerging consumer; millennials, immigrants with little to no credit history and also those who may have been subprime or near prime consumers who are demonstrating better credit management. There also may be older consumers who may have not engaged in traditional credit history in a while or those who have hit a major life circumstance who had nowhere else to turn. Still others who have turned to nontraditional lending may have preferred the experience of online lending and did not realize that many of these trades do not impact their traditional credit file. Regardless of their individual circumstances, consumers who leverage alternative financial services have historically had one thing in common: their performance in these products did nothing to further their access to traditional, and often lower cost, sources of credit. Through Experian’s acquisition and integration of Clarity Services, the nation’s largest alternative finance credit bureau, lenders can gain access to powerful and predictive supplemental credit data that better detect risk while benefiting consumers with a more complete credit history. Alternative finance data can be used across the lending cycle from prospecting to decisioning and account review to collections. Alternative data gives lenders an expanded view of consumer behavior which enables more complete and confident lending decisions. Find out more about Experian’s alternative credit data: www.experian.com/alternativedata.

We’ve popped the bottles at midnight, now it’s time to burst the reality bubble. Countdown: t-minus less than 90 days until what is for many the dreaded April 15 tax deadline. Tax Season - Get Started Coupled with debt consolidation post-holidays, January is a harsh contrast to all the feasting and festivities of the holiday season. However, the tax season doesn’t necessarily have to be synonymous with doom and gloom – many Americans look forward to receiving a tax refund. And of those people expecting a tax refund, 35% of consumers said they would use it to pay down debt, according to the National Retail Federation. Lenders and financial institutions can help their consumers get off on the right financial foot for 2019 by helping them to pay down their debt. Here are 5 tools you need to have this tax season to make the most of your collections efforts:   1. Identify your target market – Tax Season Payment IndicatorTM Did you know the average tax refund in 2016 and 2017 was over $2,760, according to the IRS? Also, during the 2017 tax season, 45 million consumers paid at least $500 and 10% or more of a tradeline balance(s), according to Experian data. Tax Season Payment Indicator examines payment behavior over the past two years to determine whether a consumer has made a large payment to a tradeline balance – or balances – during tax season. 2. Keep up-to-date on consumer information – Clear ProfileTM Skip tracing just got easier. Narrow in on the right contact information for your past-due consumer using Clear Profile. Leveraging Clarity Service’s database, Clear Profile provides the most recent and historical demographic elements associated with your consumer’s previous applications including addresses, phone numbers, employers, emails and banks. 3. Know the right time to collect – Collection TriggersSM Take the guesswork out of how to manage your collections efforts. Track your accounts to notify you of a new contact information and changes that indicate your past-due consumers’ ability to pay. 4. Stay ahead of fraudsters – CrossCoreTM Fraudsters are everywhere, so protect your customers and your organization by monitoring your portfolio to keep fraudulent accounts from being opened.     Still wondering how to get tax season ready? Get Your Collections Tax Season Ready