Market Trends

If there is one word to describe the automotive finance market in Q4 2019, it’s stable. By nearly every measure, the automotive finance market continued to move along at a good pace.

In the past 10 years, consumers begin purchasing convertibles as early as March.

Update: After closely monitoring updates from the WHO, CDC, and other relevant sources related to COVID-19, we have decided to cancel our 2020 Vision Conference. If you had the chance to experience tomorrow, today, would you take it? What if it meant you could get a glimpse into the future technology and trends that would take your organization to the next level? If you’re looking for a competitive edge – this is it. For more than 38 years, Experian’s premier conference has connected business leaders to data-driven ideas and solutions, fueling them to target new markets, grow existing customer bases, improve response rates, reduce fraud and increase profits. What’s in it for you? Everything to gain and nothing to lose. Are you a marketer? These sessions were made to drive your conversion rates to new heights: Know your customers via omnichannel marketing: Your customers are everywhere, but can you reach them? Learn how to drive business-expansion strategy, brand affinity and customer engagement across multiple channels. Plus, gain insight into connecting with customers via one-to-one messaging. By invitation only, the future of ITA marketing: An evolving landscape means marketers face new challenges in effectively targeting consumers while staying compliant. In this session, we’ll explore how you can leverage fair lending-friendly marketing data for targeting, analysis and measurement. Want the latest in technology trends? Dive into discussions to transform your customer experience: Credit in the age of technology transformation: Machine learning and artificial intelligence are the current darlings of big data, but the platform that drives the success of any big data endeavor is crucial. This session will dive into what happens behind the curtain. Put away your plastic – next-generation identity: An industry panel of experts discusses the newest digital identity and authentication capabilities – those in use today and also exciting solutions on the horizon. How about for the self-proclaimed data geeks? Analyze these: Alternative data: Listen in on an in-depth conversation about creative and impactful examples of using emerging data assets, such as alternative and consumer-permissioned data, for improved consumer inclusion, risk assessment and verification services. The next wave in open data: Experian will share their views on the potential of advanced data and models and how they benefit the global value chain – from consumer scores to business opportunities – regardless of local regulations. And the risk masters? Join us as we kick fraud to the curb: Understanding and tackling synthetic ID fraud: Synthetic IDs present a serious challenge for our entire industry. This expert panel will explore the current landscape – what’s working and what’s not, the expected impact of the next generation SSA eCBSV service, and best practice prevention methods. You are your ID – the new reality of biometrics: Consumers are becoming increasingly comfortable with biometrics. Just as CLEAR has transformed how we use our biometric identity to move through airports, sports venues and more, financial transactions can also be made friction-free. The point is, there’s something for everyone at Vision 2020. It’s not just another conference. Trade in stuffy tradeshow halls and another tri-fold brochure for the insights and connections you need to take your career and organization to the next level. Like technology itself, Vision 2020 promises to connect us, unify us and enable us all to create a better tomorrow. Join us for unique networking opportunities, one-on-one conversations with subject-matter experts and more than 50 breakout sessions with the industry’s most sought-after thought leaders.    

Do you have 20/20 vision when it comes to the readiness of your organization? How financially healthy are your customers today? They are likely facing some challenges and difficult choices. Based on a study by the Center for Financial Services Innovation (CFSI), almost half of the US adult population - that’s 112.5 million - say they do not have enough savings to cover at least three months of living expenses. With debt rising and a possible recession on the horizon, it’s crucial to have a solid strategy in place for your organization. Here are three easy steps to help you prepare: Anticipate the recession before it arrives Gathering a complete view of your customers can be difficult if you have multiple systems, which can result in subjective, costly and inefficient processes. If you don’t have a full picture of your customers, it’s hard to understand their risk, behavior and ability to pay and to determine the most effective treatment decisions. Having the right data is only the first step. Using analytics to make sense of the data helps you better understand your customers at an individual level, which will increase recovery rates and improve the customer experience. Analytics can provide early-warning indicators that identify customers most likely to miss payments, predict future behavior, and deliver the best treatment option based on a customer’s specific situation or behavior. With a deeper understanding of at-risk customers, you can apply more targeted interventions that are specific to each customer, so you can be confident your collections process is individualized, efficient and fair. The result? A cost-effective, compliant process focused on retaining valuable customers and reducing losses.   What to look for: ✔ Know when customers are experiencing negative credit events ✔ View consumer credit trends that may not yet be visible on your own account base ✔ Watch for payment stress – understand the actual payment consumers are making. Is it changing? ✔ See individual trends and take action – are your customers sliding down to a lower score band? ✔ Understand how your client-base is performing within your own portfolio and with other organizations   Take immediate and impactful actions around risk mitigation and staffing Every interaction with consumers needs optimizing, from target marketing through to collections and recovery. Organizations that proactively modernize their business to scale and increase effectiveness before the next economic downturn may avoid struggling to address rising delinquencies when the economy corrects itself. This may improve portfolio performance and collection capabilities — significantly increasing recoveries, containing costs and sustaining returns. Identify underperforming products and inefficient processes by staff. Consider reassessing the data used and the manual processes required for making decisions. Optimize product pricing and areas where organizations or staff could automate the decision processes.   Areas to focus: ✔ Identity theft protection and account takeover awareness ✔ Improve underwriting strategy and automation ✔ Maximize profitability — drive spend, optimize approvals, line assignment and pricing ✔ Evaluate collection risk strategies and operational efficiencies   Design and deploy a strategy to be organizationally and technologically ready for change Communication is key in debt recovery. Failing to contact customers via their preferred channel can cause frustration and reduce the likelihood of recovery. Your customers are looking for a convenient and discreet way to negotiate or repay debt, and if you aren’t providing one, you’re incurring higher collections costs and lower recovery rates. With developments in the digital world, consumer interactions have changed. Most people prefer to communicate via mobile or online, with little to no human interaction. Behavioral analytics help to automate and decide the next best action, so you contact the right customer at the right time through the right channel. In addition, offering a convenient, discreet way to negotiate or repay debt can result in customers who are more engaged and more likely to pay. Online and self-service portals along with AI-powered chatbots use the latest technology to provide a safe and customer-centric experience, creating less time-consuming interactions and higher customer satisfaction. Your digital collections process is more convenient and less stressful for consumers and more profitable and compliant for you. Visualize the future... ✔ Superior customer service is embraced at the end of the customer life cycle as it is in the beginning ✔ Leverage data, analytics, software, and industry expertise to drive an automated collections process with fewer manual interventions ✔ Meet the growing expectation for digital consumer self-service by providing the ability to proactively negotiate and manage debt through preferred contact channels ✔ When economy and market conditions change for the worst, have the right data, analytics, software in place and be prepared to implement relevant collections strategies to remain competitive in the market   Don’t wait until the next recession hits. Our collaborative approach to problem solving ensures you have the right solution in place to solve your most complex problems and are ready for market changes. The combination of our data, analytics, fraud tools, decisioning software and consulting services will help you proactively manage your portfolio to minimize the flow of accounts into collections and modernize your collections and recovery processes. Learn More

It may be a new decade of disruption, but one thing remains constant – the consumer is king. As such, customer experience (and continually evolving digital transformations necessary to keep up), digital expansion and all things identity will also reign supreme as we enter this new set of Roaring 20s. Here are seven of the top trends to keep tabs of through 2020 and beyond. 1. Data that does more – 100 million borrowers and counting Traditional, alternative, public record, consumer-permissioned, small business, big business, big, bigger, best – data has a lot of adjectives preceding it. But no matter how we define, categorize and collate data, the truth is there’s a lot of it that’s untapped, which is keeping financial institutions from operating at their max efficiency levels. Looking for ways to be bigger and bolder? Start with data to engage your credit-worthy consumer universe and beyond. Across the entire lending lifecycle, data offers endless opportunities – from prospecting and acquisitions to fraud and risk management. It fuels any technology solution you have or may want to implement over the coming year. Additionally, Experian is doing their part to create a more holistic picture of consumer creditworthiness with the launch of Experian LiftTM in November. The new suite of credit score products combines exclusive traditional credit, alternative credit and trended data assets, intended to help credit invisible and thin-file consumers gain access to fair and affordable credit. "We're committed to improving financial access while helping lenders make more informed decisions. Experian Lift is our latest example of this commitment brought to life,” said Greg Wright, Executive Vice President and Chief Product Officer for Experian Consumer Information Services. “Through Experian Boost, we're empowering consumers to play an active role in building their credit histories. And, with Experian Lift, we're empowering lenders to identify consumers who may otherwise be excluded from the traditional credit ecosystem,” he said. 2. Identity boom for the next generation Increasingly digital lifestyles have put personalization and frictionless transactions on hyperdrive. They are the expectation, not a nice-to-have. Having customer intelligence will become a necessary survival strategy for those in the market wanting to compete. Identity is not just for marketing purposes; it must be leveraged across the lending lifecycle and every customer interaction. Fragmented customer identities are more than flawed for decisioning purposes, which could potentially lead to losses. And, of course, the conversation around identity would be incomplete without a nod to privacy and security considerations. With the roll-out of the California Consumer Privacy Act (CCPA) earlier this month, we will wait to see if the other states follow suit. Regardless, consumers will continue to demand security and trust. 3. All about artificial intelligence and machine learning We get it – we all want the fastest, smartest, most efficient processes on limited – and/or shrinking – budgets. But implementing advanced analytics for your financial institution doesn’t have to break the bank. And, when it comes to delivering services and messaging to customers the way they want it, how to do that means digital transformation – specifically, leveraging big data and actionable analytics to evaluate risk, uncover industry intel and improve decisioning. One thing’s for certain, financial institutions looking to compete, gain traction and pull away from the competition in this next decade will need to do so by leveraging a future-facing partner’s expertise, platforms and data. AI and machine learning model development will go into hyperdrive to add accuracy, efficiency, and all-out speed. Real-time transactional processing is where it’s at. 4. Customer experience drives decisioning and everything Faster, better, more frictionless. 2020 and the decade will be all about making better decisions faster, catering to the continually quickening pace of consumer attention and need. Platforms and computing language aside, how do you increase processing speed at the same time as increasing risk mitigation? Implementing decisioning environments that cater to consumer preferences, coupled with best-in-class data are the first two steps to making this happen. This can facilitate instant decisioning within financial institutions. Looking beyond digital transformation, the next frontier is digital expansion. Open platforms enable financial institutions to readily add solutions from numerous providers so that they can connect, access and orchestrate decisions across multiple systems. Flexible APIs, single integrations and better strategy and design build the foundation of the framework to be implemented to enhance and elevate customer experience as it’s known today. 5. Credit marketing that keeps up with the digital, instant-gratification age Know your customer may be a common acronym for the financial services industry, but it should also be a baseline for determining whether to send a specific message to clients and prospects. From the basics, like prescreen, to omni-channel marketing campaigns, financial institutions need to leverage the communication channels that consumers prefer. From point of sale to mobile – there are endless possibilities to fit into your consumers’ credit journey. Marketing is clearly not a one-and-done tactic, and therefore multi-channel prequalification offers and other strategies will light the path for acquisitions and cross-sell/up-sell opportunities to come. By developing insights from customer data, financial institutions have a clear line of sight into determining optimal strategies for customer acquisition and increasing customer lifetime value. And, at the pinnacle, the modern customer acquisition engine will continue to help financial institutions best build, test and optimize their customer channel targeting strategies faster than ever before. From segmentation to deployment, and the right data across it all, today and tomorrow’s technology can solve many of financial organizations’ age-old customer acquisition challenges. 6. Three Rs: Recession, regulatory and residents of the White House Last March, the yield curve inverted for the first time since 2007. Though the timing of the next economic correction is debated, messaging is consistent around making a plan of action now. Whether it’s arming your collections department, building new systems, updating existing systems, or adjusting rules and strategy, there are gaps every organization needs to fill. By leveraging the stability of the economy now, financial institutions can put strategies in place to maximize profitability, manage risk, reduce bad debt/charge-offs, and ensure regulatory compliance among their list of to-do’s, ultimately resulting in a more efficient, better-performing program. Also, as we near the election later this year, the regulatory landscape will likely change more than the usual amount. Additionally, we will witness the first accounts of what CECL looks like for SEC-filing financial institutions (and if that will suggest anything for how non-SEC-filing institutions may fare as their deadline inches closer), as well as see the initial implications of the CCPA roll out and whether it will pave a path for other states to follow. As system sophistication continues to evolve, so do the risks (like security breaches) and new regulatory standards (like GDPR and CCPA) which provide reasons for organizations to transform. 7. Focus on fraud (in all forms) With evolving technology, comes evolved fraudsters. Whether it’s loyalty and rewards programs, account openings, breaches, there are so many angles and entry points. Synthetic identity fraud is the fastest-growing type of financial crime in the United States. The cost to businesses is estimated to grow to $1.2 billion by 2020, according to the Aite Group. To ensure the best protection for your business and your customers, a layered, risk-based approach to fraud management provides the highest levels of confidence in the industry. Balance is key – while being compliant with regulatory requirements and conscious of user experience, ensuring consumers’ peace of mind is priority one. Not a new trend, but recognizing fraud and recognizing good consumers will save continue to save financial institutions money and reputational harm, driving significant improvement in key performance indicators. Using the right data (and aggregating multiple data sets) and digital device intelligence tools is the one-two punch to protect your bottom line. For all your needs in 2020 and throughout the next decade, Experian has you covered. Learn more

As consumers prepare for the next decade, we look at how we’re rounding out this year. The results? The average American credit score is 682, an eight-year high. Experian released the 10th annual state of credit report, which provides a comprehensive look at the credit performance of consumers across America by highlighting consumer credit scores and borrowing behaviors. And while the data is spliced to show men vs. women, as well as provides commentary at the state and generational level, the overarching trend is up. Even with the next anticipated economic correction often top of mind for financial institutions, businesses and consumers alike, 2019 was a year marked by more access, more spending and decreasing delinquencies. Things are looking up. “We are seeing a promising trend in terms of how Americans are managing their credit as we head into a new decade with average credit scores increasing two points since 2018 to 682 – the highest we’ve seen since 2011,” said Shannon Lois, Senior Vice President and Head of EAS, Analytics, Consulting & Operations for Experian Decision Analytics. “Average credit card balances and debt are up year over year, yet utilization rates remain consistent at 30 percent, indicating consumers are using credit as a financial tool and managing their debts responsibly.”   Highlights of Experian’s State of Credit report: 3-year comparison 2017 2018 2019   Average number of credit cards 3.06 3.04 3.07 Average credit card balances $6,354 $6,506 $6,629 Average number of retail credit cards 2.48 2.59 2.51 Average retail credit card balances $1,841 $1,901 $1,942 Average VantageScore® credit score[1, 2] 675 680 682 Average revolving utilization 30% 30% 30% Average nonmortgage debt[3] $24,706 $25,104 $25,386 Average mortgage debt $201,811 $208,180 $231,599 Average 30 days past due delinquency rates 4.0% 3.9% 3.9% Average 60 days past due delinquency rates 1.9% 1.9% 1.9% Average 90+ days past due delinquency rates 7.3% 6.7% 6.8%   In the scope of the credit score battle of the sexes, women have a four-point lead over men with an average credit score of 686 compared to 682. Their lead is a continued trend since 2017 where they’ve bested their male counterparts. According to the report, while men carry more non-mortgage and mortgage debt than women, women have more credit cards and retail cards (albeit they carry lower balances). Generationally, Generations X, Y and Z tend to carry more debt, including mortgage, non-mortgage, credit card and retail card, than older generations with higher delinquency and utilization rates. Segmented by state and gender, Minnesota had the highest credit scores for both men and women, while Mississippi was the state with the lowest average credit score for females and Louisiana was the lowest average credit score state for males.     As we round out the decade and head full-force into 2020, we can reflect on the changes in the past year alone that are helping consumers improve their financial health. Just to name a few: Experian launched Experian BoostTM in March, allowing millions of consumers to add positive payment history directly to their credit file for an opportunity to instantly increase their credit score. Since then, there has been over 13 million points boosted across America. Experian LiftTM was launched in November, designed to help credit invisible and thin-file consumers gain access to fair and affordable credit. Long-standing commitments to consumer education, including the Ask Experian Blog and volunteer work by Experian’s Education Ambassadors, continue to offer assistance to the community and help consumers better understand their financial actions. From what we can tell, this is just the beginning. “Understanding the factors that influence their overall credit profile can help consumers improve and maintain their financial health,” said Rod Griffin, Experian’s director of consumer education and awareness. “Credit can be used as a financial tool. Through this report, we hope to provide insights that will help consumers make more informed decisions about credit use as we prepare to head into a new decade.” Learn more 1 VantageScore® is a registered trademark of VantageScore Solutions, LLC. 2 VantageScore® credit score range is 300 to 850. 3 Average debt for this study includes all credit cards, auto loans and personal loans/student loans.

Article written by Melanie Smith, Senior Copywriter, Experian Clarity Services, Inc. It’s been almost a decade since the Great Recession in the United States ended, but consumers continue to feel its effects. During the recession, millions of Americans lost their jobs, retirement savings decreased, real estate reduced in value and credit scores plummeted. Consumers that found themselves impacted by the financial crisis often turned to alternative financial services (AFS). Since the end of the recession, customer loyalty and retention has been a focus for lenders, given that there are more options than ever before for AFS borrowers. To determine what this looks like in the current climate, we examined today’s non-prime consumers, what their traditional scores look like and if they are migrating to traditional lending. What are alternative financial services (AFS)? Alternative financial services (AFS) is a term often used to describe the array of financial services offered by providers that operate outside of traditional financial institutions. In contrast to traditional banks and credit unions, alternative service providers often make it easier for consumers to apply and qualify for lines of credit but may charge higher interest rates and fees. More than 50% of new online AFS borrowers were first seen in 2018 To determine customer loyalty and fluidity, we looked extensively at the borrowing behavior of AFS consumers in the online marketplace. We found half of all online borrowers were new to the space as of 2018, which could be happening for a few different reasons. Over the last five years, there has been a growing preference to the online space over storefront. For example, in our trends report from 2018, we found that 17% of new online customers migrated from the storefront single pay channel in 2017, with more than one-third of these borrowers from 2013 and 2014 moving to online overall. There was also an increase in AFS utilization by all generations in 2018. Additionally, customers who used AFS in previous years are now moving towards traditional credit sources. 2017 AFS borrowers are migrating to traditional credit As we examined the borrowing behavior of AFS consumers in relation to customer loyalty, we found less than half of consumers who used AFS in 2017 borrowed from an AFS lender again in 2018. Looking into this further, about 35% applied for a loan but did not move forward with securing the loan and nearly 24% had no AFS activity in 2018. We furthered our research to determine why these consumers dropped off. After analyzing the national credit database to see if any of these consumers were borrowing in the traditional credit space, we found that 34% of 2017 borrowers who had no AFS activity in 2018 used traditional credit services, meaning 7% of 2017 borrowers migrated to traditional lending in 2018. Traditional credit scores of non-prime borrowers are growing After discovering that 7% of 2017 online borrowers used traditional credit services in 2018 instead of AFS, we wanted to find out if there had also been an improvement in their credit scores. Historically, if someone is considered non-prime, they don’t have the same access to traditional credit services as their prime counterparts. A traditional credit score for non-prime consumers is less than 600. Using the VantageScore® credit score, we examined the credit scores of consumers who used and did not use AFS in 2018. We found about 23% of consumers who switched to traditional lending had a near-prime credit score, while only 8% of those who continued in the AFS space were classified as near-prime. Close to 10% of consumers who switched to traditional lending in 2018 were classified in the prime category. Considering it takes much longer to improve a traditional credit rating, it’s likely that some of these borrowers may have been directly impacted by the recession and improved their scores enough to utilize traditional credit sources again. Key takeaways AFS remains a viable option for consumers who do not use traditional credit or have a credit score that doesn’t allow them to utilize traditional credit services. New AFS borrowers continue to appear even though some borrowers from previous years have improved their credit scores enough to migrate to traditional credit services. Customers who are considered non-prime still use AFS, as well as some near-prime and prime customers, which indicates customer loyalty and retention in this space. For more information about customer loyalty and other recently identified trends, download our recent reports. State of Alternative Data 2019 Lending Report

Fintech is quickly changing. The word itself is synonymous with constant innovation, agile technology structures and being on the cusp of the future of finance. The rapid rate at which fintech challengers are becoming established, is in turn, allowing for greater consumer awareness and adoption of fintech platforms. It would be easy to assume that fintech adoption is predominately driven by millennials. However, according to a recent market trend analysis by Experian, adoption is happening across multiple generational segments. That said, it’s important to note the generational segments that represent the largest adoption rates and growth opportunities for fintechs. Here are a few key stats: Members of Gen Y (between 24-37 years old) account for 34.9% of all fintech personal loans, compared to just 24.9% for traditional financial institutions. A similar trend is seen for Gen Z (between 18-23 years old). This group accounts for 5% of all fintech personal loans as compared to 3.1% for traditional Let’s take a closer look at these generational segments… Gen Y represents approximately 19% of the U.S. population. These consumers, often referred to as “millennials,” can be described as digital-centric, raised on the web and luxury shoppers. In total, millennials spend about $600 billion a year. This group has shown a strong desire to improve their credit standing and are continuously increasing their credit utilization. Gen Z represents approximately 26% of the U.S. population. These consumers can be described as digital centric, raised on the social web and frugal. The Gen Z credit universe is growing, presenting a large opportunity to lenders, as the youngest Gen Zers become credit eligible and the oldest start to enter homeownership. What about the underbanked as a fintech opportunity? The CFPB estimates that up to 45 million people, or 24.2 million households, are “thin-filed” or underbanked, meaning they manage their finances through cash transactions and not through financial services such as checking and savings accounts, credit cards or loans. According to Angela Strange, a general partner at Andreessen Horowitz, traditional financial institutions have done a poor job at serving underbanked consumers affordable products. This has, in turn, created a trillion-dollar market opportunity for fintechs offering low-cost, high-tech financial services. Why does all this matter? Fintechs have a unique opportunity to engage, nurture and grow these market segments early on. As the fintech marketplace heats up and the overall economy begins to soften, diversifying revenue streams, building loyalty and tapping into new markets is a strategic move. But what are the best practices for fintechs looking to build trust, engage and retain these unique consumer groups? Join us for a live webinar on November 12 at 10:00 a.m. PST to hear Experian experts discuss financial inclusion trends shaping the fintech industry and tactical tips to create, convert and extend the value of your ideal customers. Register now

Retailers are already starting to display their Christmas decorations in stores and it’s only early November. Some might think they are putting the cart ahead of the horse, but as I see this happening, I’m reminded of the quote by the New York Yankee’s Yogi Berra who famously said, “It gets late early out there.” It may never be too early to get ready for the next big thing, especially when what’s coming might set the course for years to come. As 2019 comes to an end and we prepare for the excitement and challenges of a new decade, the same can be true for all of us working in the lending and credit space, especially when it comes to how we will approach the use of alternative data in the next decade. Over the last year, alternative data has been a hot topic of discussion. If you typed “alternative data and credit” into a Google search today, you would get more than 200 million results. That’s a lot of conversations, but while nearly everyone seems to be talking about alternative data, we may not have a clear view of how alternative data will be used in the credit economy. How we approach the use of alternative data in the coming decade is going to be one of the most important decisions the lending industry makes. Inaction is not an option, and the time for testing new approaches is starting to run out – as Yogi said, it’s getting late early. And here’s why: millennials. We already know that millennials tend to make up a significant percentage of consumers with so-called “thin-file” credit reports. They “grew up” during the Great Recession and that has had a profound impact on their financial behavior. Unlike their parents, they tend to have only one or two credit cards, they keep a majority of their savings in cash and, in general, they distrust financial institutions. However, they currently account for more than 21 percent of discretionary spend in the U.S. economy, and that percentage is going to expand exponentially in the coming decade. The recession fundamentally changed how lending happens, resulting in more regulation and a snowball effect of other economic challenges. As a result, millennials must work harder to catch up financially and are putting off major life milestones that past generations have historically done earlier in life, such as homeownership. They more often choose to rent and, while they pay their bills, rent and other factors such as utility and phone bill payments are traditionally not calculated in credit scores, ultimately leaving this generation thin-filed or worse, credit invisible. This is not a sustainable scenario as we enter the next decade. One of the biggest market dynamics we can expect to see over the next decade is consumer control. Consumers, especially millennials, want to be in the driver’s seat of their “credit journey” and play an active role in improving their financial situations. We are seeing a greater openness to providing data, which in turn enables lenders to make more informed decisions. This change is disrupting the status quo and bringing new, innovative solutions to the table. At Experian, we have been testing how advanced analytics and machine learning can help accelerate the use of alternative data in credit and lending decisions. And we continue to work to make the process of analyzing this data as simple as possible, making it available to all lenders in all verticals. To help credit invisible and thin-file consumers gain access to fair and affordable credit, we’ve recently announced Experian Lift, a new suite of credit score products that combines exclusive traditional credit, alternative credit and trended data assets to create a more holistic picture of consumer creditworthiness that will be available to lenders in early 2020. This new Experian credit score may improve access to credit for more than 40 million credit invisibles. There are more than 100 million consumers who are restricted by the traditional scoring methods used today. Experian Lift is another step in our commitment to helping improve financial health of consumers everywhere and empowers lenders to identify consumers who may otherwise be excluded from the traditional credit ecosystem. This isn’t just a trend in the United States. Brazil is using positive data to help drive financial inclusion, as are others around the world. As I said, it’s getting late early. Things are moving fast. Already we are seeing technology companies playing a bigger role in the push for alternative data – often powered by fintech startups. At the same time, there also has been a strong uptick in tech companies entering the banking space. Have you signed up for your Apple credit card yet? It will take all of 15 seconds to apply, and that’s expected to continue over the next decade. All of this is changing how the lending and credit industry must approach decision making, while also creating real-time frictionless experiences that empower the consumer. We saw this with the launch of Experian Boost earlier this year. The results speak for themselves: hundreds of thousands of previously thin-file consumers have seen their credit scores instantly increase. We have also empowered millions of consumers to get more control of their credit by using Experian Boost to contribute new, positive phone, cable and utility payment histories. Through Experian Boost, we’re empowering consumers to play an active role in building their credit histories. And, with Experian Lift, we’re empowering lenders to identify consumers who may otherwise be excluded from the traditional credit ecosystem. That’s game-changing. Disruptions like Experian Boost and newly announced Experian Lift are going to define the coming decade in credit and lending. Our industry needs to be ready because while it may seem early, it’s getting late.

It seems like artificial intelligence (AI) has been scaring the general public for years – think Terminator and SkyNet. It’s been a topic that’s all the more confounding and downright worrisome to financial institutions. But for the 30% of financial institutions that have successfully deployed AI into their operations, according to Deloitte, the results have been anything but intimidating. Not only are they seeing improved performance but also a more enhanced, positive customer experience and ultimately strong financial returns. For the 70% of financial institutions who haven’t started, are just beginning their journey or are in the middle of implementing AI into their operations, the task can be daunting. AI, machine learning, deep learning, neural networks—what do they all mean? How do they apply to you and how can they be useful to your business? It’s important to demystify the technology and explain how it can present opportunities to the financial industry as a whole. While AI seems to have only crept into mainstream culture and business vernacular in the last decade, it was first coined by John McCarthy in 1956. A researcher at Dartmouth, McCarthy thought that any aspect of learning or intelligence could be taught to a machine. Broadly, AI can be defined as a machine’s ability to perform cognitive functions we associate with humans, i.e. interacting with an environment, perceiving, learning and solving problems. Machine learning vs. AI Machine learning is not the same thing as AI. Machine learning is the application of systems or algorithms to AI to complete various tasks or solve problems. Machine learning algorithms can process data inputs and new experiences to detect patterns and learn how to make the best predictions and recommendations based on that learning, without explicit programming or directives. Moreover, the algorithms can take that learning and adapt and evolve responses and recommendations based on new inputs to improve performance over time. These algorithms provide organizations with a more efficient path to leveraging advanced analytics. Descriptive, predictive, and prescriptive analytics vary in complexity, sophistication, and their resulting capability. In simplistic terms, descriptive algorithms describe what happened, predictive algorithms anticipate what will happen, and prescriptive algorithms can provide recommendations on what to do based on set goals. The last two are the focus of machine learning initiatives used today. Machine learning components - supervised, unsupervised and reinforcement learning Machine learning can be broken down further into three main categories, in order of complexity: supervised, unsupervised and reinforcement learning. As the name might suggest, supervised learning involves human interaction, where data is loaded and defined and the relationship to inputs and outputs is defined. The algorithm is trained to find the relationship of the input data to the output variable. Once it delivers accurately, training is complete, and the algorithm is then applied to new data. In financial services, supervised learning algorithms have a litany of uses, from predicting likelihood of loan repayment to detecting customer churn. With unsupervised learning, there is no human engagement or defined output variable. The algorithm takes the input data and structures it by grouping it based on similar characteristics or behaviors, without a defined output variable. Unsupervised learning models (like K-means and hierarchical clustering) can be used to better segment or group customers by common characteristics, i.e. age, annual income or card loyalty program. Reinforcement learning allows the algorithm more autonomy in the environment. The algorithm learns to perform a task, i.e. optimizing a credit portfolio strategy, by trying to maximize available rewards. It makes decisions and receives a reward if those actions bring the machine closer to achieving the total available rewards, i.e. the highest acquisition rate in a customer category. Over time, the algorithm optimizes itself by correcting actions for the best outcomes. Even more sophisticated, deep learning is a category of machine learning that involves much more complex architecture where software-based calculators (called neurons) are layered together in a network, called a neural network. This framework allows for much broader, complex data ingestion where each layer of the neural network can learn progressively more complex elements of the data. Object classification is a classic example, where the machine ‘learns’ what a duck looks like and then is able to automatically identify and group images of ducks. As you might imagine, deep learning models have proved to be much more efficient and accurate at facial and voice recognition than traditional machine learning methods. Whether your financial institution is already seeing the returns for its AI transformation or is one of the 61% of companies investing in this data initiative in 2019, having a clear picture of what is available and how it can impact your business is imperative. How do you see AI and machine learning impacting your customer acquisition, underwriting and overall customer experience?

It’s Halloween time – time for trick or treating, costume parties and monsters lurking in the background. But this year, the monsters aren’t just in the background. They’re in your portfolio.  This year, “Frankenstein” has another meaning. Much more ominous than the neighbor kid in the costume.   “Frankenstein IDs” refer to synthetic identities — a type of fraud carried out by criminals that have created fictitious identities. Just as Dr. Frankenstein’s monster was stitched together from parts, synthetic IDs are stitched together pieces of mismatched identities — some fake, some real, some even deceased.   It typically takes fraudsters 12 to 18 months to create and nurture a synthetic identity before it’s ready to "bust out" – the act of building a credit history with the intent of maxing out all available credit and eventually disappearing. That means fraudsters are investing money and time to build numerous tradelines, ensure these "fake" identities are in good credit standing, and ultimately steal the largest amount of money possible.   “Wait Master, it might be dangerous . . . you go, first.” — Igor   Synthetic identities are a notable challenge for many financial institutions and retail organizations. According to the recently released Federal Reserve Board White Paper, synthetic identity fraud accounts for roughly 20% of all credit losses, and cost U.S. businesses roughly $6 billion in 2016 with an estimated 41% growth over 2 years. 85-95% of applicants identified as potential synthetic are not even flagged by traditional fraud models.   The Social Security Administration recently announced plans for the electronic Consent Based Social Security Number Verification service – pilot program scheduled for June 2020. This service is designed to bring efficiency to the process for verifying Social Security numbers directly with the government agency. Once available, this verification could be an important tool in the fight against the elusive “Frankenstein” identity monster.   But with the Social Security Administration's pilot program not scheduled for launch until the middle of next year, how can financial institutions and other organizations bridge the gap and adequately prepare for a potential uptick in synthetic identity fraud attacks? It comes down to a multilayered approach that relies on advanced data, analytics, and technology — and focuses on identity.   Any significant progress in making synthetic identities easier to detect could cost fraudsters significant time and money.   Far too many financial institutions and other organizations depend solely on basic demographic information and snapshots in time to confirm the legitimacy of an identity. These organizations need to think beyond those capabilities. The real value of data in many cases lies between the data points. We have seen this with synthetic identity — where a seemingly legitimate identity only shows risk when we can analyze its connections and relationships to other individuals and characteristics.   In addition to our High Risk Fraud Score, we now have a Synthetic Fraud Risk Level Indicator available on credit profiles. These advanced detection capabilities are delivered via the simplicity of a straightforward indicator returned on the credit profile which lenders can use to trigger additional identity verification processes.   While there are programs and initiatives in the works to help financial institutions and other organizations combat synthetic identity fraud, it's important to keep in mind there's no silver bullet, or stake to the heart, to completely keep these Frankenstein IDs out.   Oh, and don’t forget… “It’s pronounced ‘Fronkensteen.’ ” — Dr. Frankenstein

To provide consumers with clear-cut protections against disturbance by debt collectors, the Consumer Financial Protection Bureau (CFPB) issued a Notice of Proposed Rulemaking (NPRM) to implement the Fair Debt Collection Practices Act (FDCPA) earlier this year. Among many other things, the proposal would set strict limits on the number of calls debt collectors may place to reach consumers weekly and clarify requirements for consumer-facing debt collection disclosures. A bigger discussion Deliberation of the debt collection proposal was originally scheduled to begin on August 18, 2019. However, to allow commenters to further consider the issues raised in the NPRM and gather data, the comment period was extended by 20 days to September 18, 2019. It is currently still being debated, as many argue that the proposed rule does not account for modern consumer preferences and hinders the free flow of information used to help consumers access credit and services. The Association of Credit and Collection Professionals (ACA International) and US House lawmakers continue to challenge the proposal, stating that it doesn’t ensure that debt collectors’ calls to consumers are warranted, nor does it do enough to protect consumers’ privacy. Many consumer advocates have expressed doubts about how effective the proposed measures will be in protecting debtors from debt collector harassment and see the seven-calls-a-week limit on phone contact as being too high. In fact, it’s difficult to find a group of people in full support of the proposal, despite the CFPB stating that it will help clarify the FDCPA, protect lenders from litigation and bring consumer protection regulation into the 21st century. What does this mean? Although we don’t know when, or if, the proposed rule will go into effect, it’s important to prepare. According to the Federal Register, there are key ways that the new regulation would affect debt collection through the use of newer technologies, required disclosures and limited consumer contact. Not only will the proposed rules apply to debt collectors, but its provisions will also impact creditors and servicers, making it imperative for everyone in the financial services space to keep watch on the regulation’s status and carefully analyze its proposed rules. At Experian, our debt collection solutions automate and moderate dialogues and negotiations between consumers and collectors, making it easier for collection agencies to connect with consumers while staying compliant. Our best-in-class data and analytics will play a key role in helping you reach the right consumer, in the right place, at the right time. Learn more

Retail banking leaders in a variety of industries (including risk management, credit, information technology and other departments) want to incorporate more data into their business strategies. By doing so, consumer banks and other financial companies benefit by expanding their markets, controlling risk, improving compliance and the customer experience. However, many companies don’t know how or where to start. The challenges? There’s just too much data – and it’s overwhelming. Technical integration issues Maintaining regulatory data and attribute governance and compliance The slow speed of adoption Join Jim Bander, PhD, analytics and optimization leader at Experian, in an upcoming webinar with the Consumer Bankers Association on Tuesday, Oct. 1, 2019 at 9:00-10:00 a.m. PT. The webinar will discuss how some of the country’s best banks – big and small – are making better, faster and more profitable decisions by using the right set of data sources, while avoiding data overload. Key topics will include: Technology Trends: Discover how the latest technology, including the cloud and machine learning, makes it easier than ever to access data, define and manage attributes throughout the enterprise and perform complex calculations in real time. Time to Market: Discover how consumer banks and other financial companies that have mastered data and attribute management are able to integrate data and attributes quickly and seamlessly. Business Benefits: Understand how advanced analytics helps financial institutions of all sizes make better business decisions. This includes growing their portfolios, mitigating fraud and credit risk, controlling operating expenses, improving compliance and enhancing the customer experience. Critical Success Factors: Learn how to stay ahead of ever-evolving business and data requirements and continuously improve your lending operations. Join us as we unveil the secrets to avoiding data overload in consumer banking. Special Offer For non-current CBA members, this webinar costs $95 to attend. However, with special discount code: EX1001, non-CBA members can attend for FREE. Register Now

The average new vehicle loan hit $32,119 in Q2 2019. Average used vehicle loan amounts reached $20,156 in Q2 2019.

The future is, factually speaking, uncertain. We don't know if we'll find a cure for cancer, the economic outlook, if we'll be living in an algorithmic world or if our work cubical mate will soon be replaced by a robot. While futurists can dish out some exciting and downright scary visions for the future of technology and science, there are no future facts. However, the uncertainty presents opportunity. Technology in today's world From the moment you wake up, to the moment you go back to sleep, technology is everywhere. The highly digital life we live and the development of our technological world have become the new normal. According to The International Telecommunication Union (ITU), almost 50% of the world's population uses the internet, leading to over 3.5 billion daily searches on Google and more than 570 new websites being launched each minute. And even more mind-boggling? Over 90% of the world's data has been created in just the last couple of years. With data growing faster than ever before, the future of technology is even more interesting than what is happening now. We're just at the beginning of a revolution that will touch every business and every life on this planet. By 2020, at least a third of all data will pass through the cloud, and within five years, there will be over 50 billion smart connected devices in the world. Keeping pace with digital transformation At the rate at which data and our ability to analyze it are growing, businesses of all sizes will be forced to modify how they operate. Businesses that digitally transform, will be able to offer customers a seamless and frictionless experience, and as a result, claim a greater share of profit in their sectors. Take, for example, the financial services industry - specifically banking. Whereas most banking used to be done at a local branch, recent reports show that 40% of Americans have not stepped through the door of a bank or credit union within the last six months, largely due to the rise of online and mobile banking. According to Citi's 2018 Mobile Banking Study, mobile banking is one of the top three most-used apps by Americans. Similarly, the Federal Reserve reported that more than half of U.S. adults with bank accounts have used a mobile app to access their accounts in the last year, presenting forward-looking banks with an incredible opportunity to increase the number of relationship touchpoints they have with their customers by introducing a wider array of banking products via mobile. Be part of the movement Rather than viewing digital disruption as worrisome and challenging, embrace the uncertainty and potential that advances in new technologies, data analytics and artificial intelligence will bring. The pressure to innovate amid technological progress poses an opportunity for us all to rethink the work we do and the way we do it. Are you ready? Learn more about powering your digital transformation in our latest eBook. Download eBook Are you an innovation junkie? Join us at Vision 2020 for future-facing sessions like:  -  Cloud and beyond - transforming technologies - ML and AI - real-world expandability and compliance