Market Trends

You’ve Got Mail! Probably a lot of it. Birthday cards from Mom, a graduation announcement from your third cousin’s kid whose name you can’t remember and a postcard from your dentist reminding you you’re overdue for a cleaning. Adding to your pile, are the nearly 850 pieces of unsolicited mail Americans receive annually, according to Reader’s Digest. Many of these are pre-approval offers or invitations to apply for credit cards or personal loans. While many of these offers are getting to the right mailbox, they’re hitting a changing consumer at the wrong time. The digital revolution, along with the proliferation and availability of technology, has empowered consumers. They now not only have access to an abundance of choices but also a litany of new tools and channels, which results in them making faster, sometimes subconscious, decisions. Three Months Too Late The need to consistently stay in front of customers and prospects with the right message at the right time has caused a shortening of campaign cycles across industries. However, for some financial institutions, the customer acquisition process can take up to 120 days! While this timeframe is extreme, customer prospecting can still take around 45-60 days for most financial institutions and includes: Bureau processing: Regularly takes 10-15 days depending on the number of data sources and each time they are requested from a bureau. Data aggregation: Typically takes anywhere from 20-30 days. Targeting and selection: Generally, takes two to five days. Processing and campaign deployment: Usually takes anywhere from three days, if the firm handles it internally, or up to 10 days if an outside company handles the mailing. A Better Way That means for many firms, the data their customer acquisition campaigns are based off is at least 60 days old. Often, they are now dealing with a completely different consumer. With new card originations up 20% year-over-year in 2019 alone, it’s likely they’ve moved on, perhaps to one of your competitors. It’s time financial institutions make the move to a more modern form of prospecting and targeting that leverages the power of cloud technology, machine learning and artificial intelligence to accelerate and improve the marketing process. Financial marketing systems of the future will allow for advanced segmentation and targeting, dynamic campaign design and immediate deployment all based on the freshest data (no more than 24-48 hours old). These systems will allow firms to do ongoing analytics and modeling so their campaign testing and learning results can immediately influence next cycle decisions. Your customers are changing, isn’t it time the way you market to them changes as well?

The universe has been used as a metaphor for many things – vast, wide, intangible – much like the credit universe. However, while the man on the moon, a trip outside the ozone layer, and all things space from that perspective may seem out of touch, there is a new line of access to consumers. In Experian's latest 2019 State of Alternative Credit Data report, consumers and lenders alike weigh in on the growing data set and how they are leveraging the data in use cases across the lending lifecycle. While the topic of alternative credit data is no longer as unfamiliar as it may have been a year or two ago, the capabilities and benefits that can be experienced by financial institutions, small businesses and consumers are still not widely known. Did you know?: -  65% of lenders say they are using information beyond the traditional credit report to make a lending decision. -  58% of consumers agree that having the ability to contribute payment history to their credit file make them feel empowered. -  83% of lenders agree that digitally connecting financial account data will create efficiencies in the lending process. These and other consumer and lender perceptions of alternative credit data are now launched with the latest edition of the State of Alternative Credit Data whitepaper. This year’s report rounds up the different types of alternative credit data (from alternative financial services data to consumer-permissioned account data, think Experian BoostTM), as well as an overview of the regulatory landscape, and a number of use cases across consumer and small business lending.     In addition, consumers also have a lot to say about alternative credit data:   With the rise of machine learning and big data, lenders can collect more data than ever, facilitating smarter and more precise decisions. Unlock your portfolio’s growth potential by tapping into alternative credit data to expand your consumer universe. Learn more in the 2019 State of Alternative Credit Data Whitepaper. Read Full Report View our 2020 State of Alternative Credit Data Report for an updated look at how consumers and lenders are leveraging alternative credit data. 

Earlier this month, Experian joined FinovateSpring in San Francisco, CA to demonstrate innovations impacting financial health to over 1,000 attendees. The Finovate conference promotes real-world solutions while highlighting short-form demos and key insights from thought-leaders on digital lending, banking, payments, artificial intelligence and the customer experience. With more than 100 million Americans lacking fair access to credit, it's more important than ever for companies to work to improve the financial health of consumers. In addition to the show's abundance of fintech-centered content, Experian hosted an exclusive, cutting-edge breakout series demonstrating innovations that are positively impacting the financial health of consumers across the nation. Finovate Day One Overview While fintechs, banks, venture capitalist, entrepreneurs and industry analysts ascended on the general conference floor for a fast-paced day of demos, a select subset gathered for a luncheon presented by Experian North America CEO, Craig Boundy, and Group President, Alex Lintner. Attendees were given an in-depth look at new, alternative credit data streams and tools that are helping to increase financial access. Demos included: Experian Boost™: a free, groundbreaking online platform that allows consumers to instantly boost their credit scores by adding telecommunications and utility bill payments to their credit file. More than half a million consumers have leveraged Experian Boost, increasing their score by an average of 13 points. Cumulatively, Experian Boost has helped add more than 2.8 million points to consumers’ credit scores. Ascend Analytical Sandbox™: A first-of-its-kind data and analytics platform that gives companies instant access to more than 17 years of depersonalized credit data on more than 220 million U.S. consumers. It has been the most successful product launch in Experian’s history and recently earned the title of “Best Overall Analytics Platform” at this year’s Fintech Breakthrough Awards. Alternative Credit Data: Comprised of data from alternative credit sources, this data helps lenders make smarter and more informed lending decisions. Additionally, Experian’s Clear Data Platform is next-level credit data that adds supplemental FCRA-compliant credit data to enrich decisions across the entire credit spectrum. This new platform features alternative credit data, rental data, public records, consumer-permissioned data and more Upon conclusion of the luncheon, Alpa Lally, Experian’s Vice President of Data Business at Consumer Information Services, was interviewed for the HousingWire Podcast with Jacob Gaffney, HousingWire Editor in Chief, to discuss how new forms of data streams are helping improve consumers’ access to credit by giving lenders a clearer picture of their creditworthiness and risk. “Alternative credit data is different than traditional credit data and helps us paint a fuller picture of the consumer in terms of their ability to pay, willingness to pay and stability. It helps consumers get better access overall to the credit they deserve so that they can actively participate in the economy,” said Lally. Finovate Day Two Overview On the last day of the conference, expert speakers took to the main stage to analyze the latest fintech trends, opportunities and challenges. Alex Lintner and Sandeep Bhandari, Chief Strategy Officer and Chief Risk Officer at Affirm, participated in a fireside chat titled “Improving the Financial Health of America’s 100 Million Credit Underserved Consumers.” Moderated by David Penn, Finovate Analyst, the session explored the latest innovations, trends and technologies – from machine learning to alternative data – that are making a difference in positively impacting the financial health of Americans and expanding financial opportunities for underserved consumers. The panel discussed the efforts made to put financial health at the center of their business and the impact it’s had on their organizations. Following the fireside chat, Experian hosted a second lunch briefing, presented by Vijay Mehta, Chief Innovation Officer, and Greg Wright, EVP Chief Product Officer. The lunch included exclusive table discussions and open conversations to help attendees leave with a better understanding of the importance of prioritizing financial health to build trust, reach new customers and ultimately grow their business. "We are actively seeking out unresolved problems and creating products and technologies that will help transform the way businesses operate and consumers thrive in our society. But we know we can't do it alone," Experian North American CEO, Craig Boundy said in a recent blog post on Experian's fintech partnerships and Finovate participation. "That's why over the last year, we have built out an entire time of account executives and other support staff that are fully dedicated to developing and supporting partnerships with leading fintech companies. We've made significant strides that will help us pave the way for the next generation of lending while improving the financial health of more people around the world." For more information on how Experian is partnering with fintechs, visit experian.com/fintech or read our recent blog article on consumer-permissioned data for an in-depth discussion on Experian BoostTM.

Millions of consumers lack credit history and/or have difficulty obtaining credit from mainstream financial institutions. To ease access to credit for “invisible” and below prime consumers, financial institutions have sought ways to both extend and improve the methods by which they evaluate borrowers’ risk. This initiative to effectively score more consumers has involved the use of alternative credit data.1 Alternative credit data is FCRA-compliant data that is typically not included in a traditional credit report and is used to deliver a more complete view into a consumer’s creditworthiness. “Alternative credit data helps us paint a fuller picture of a consumer so they can get better access to the financial services they need and deserve,” said Alpa Lally, Vice President of Data Business at Experian. Experian recently sponsored the FinovateSpring conference in San Francisco, where Alpa had a chance to sit down with Jacob Gaffney, Editor-in-Chief of the HousingWire News Podcast, to discuss ways consumers can improve their credit scores. As an immigrant, Alpa spoke personally about the impact of having a limited credit history and how alternative credit data can help drive greater access to credit for consumers and profitable growth for lenders through more informed lending decisions. Highlights include: How alternative and traditional credit data differ Types of alternative credit data being used by lenders How “credit-invisibles” can best leverage alternative credit data Alternative credit data product solutions, including Experian BoostTM Listen now 1When we refer to “Alternative Credit Data,” this refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term “Expanded FCRA Data” may also apply in this instance and both can be used interchangeably.

Consumer credit trends and markets are constantly evolving, particularly when it comes to originations and delinquencies on mortgages, credit cards and auto loans. According to Experian research, over 2.7 million out of 89 million active automotive loans and leases are either 30 or 60 days delinquent. Triggers that signal a greater likelihood of consumers falling delinquent on loans, mortgages and credit card payments, include high-interest rates, a high utilization rate and recent derogatory trades. By tracking and forecasting consumer trends over time, you can more easily predict consumer behavior and better prepare for potential issues within each market. Join Gavin Harding, Experian Senior Business Consultant, and Alan Ikemura, Experian Data Analytics Senior Product Manager, during our live Quarterly Credit Trends webinar on May 30 at 2:00 p.m. ET. Our expert speakers will provide a view of the real estate market and share insights on the latest consumer credit trends. Highlights include: 2019 economic drivers Q1 2019 origination and delinquency trends Mortgage Home equity Bankcard Auto Register now

Day 2 at this year’s Vision conference was fueled with new technology and inspiration. The morning session opened with Robert Boxberger, Experian President, Decision Analytics, and also featured two live demos, one on Experian’s solution for the upcoming CECL compliance deadline and the second for mobile credit, including two use cases on instant issuance and lead generation, which has resulted in a 28% conversion rate of hot leads for one of Experian’s marquee clients. Keynote Speaker: Aimée Mullins "Get comfortable with the uncomfortable" was just one of the mantras shared on Tuesday morning by Aimée Mullins, an actor, Olympian, TEDTalk speaker, and one of the youngest honorees to be inducted into the National Women’s Hall of Fame, among many other accomplishments. “It is our uniqueness that’s our greatest asset that we can leverage for our greatest strength,” said Mullins during her keynote centered on achieving the “impossible.” As a bi-lateral amputee (or “double BK” also known as double below-the-knee amputee, as she referenced), Mullins had doctors and experts tell her and her parents what she would not be able to do. Instead, she encouraged Tuesday’s audience to never stop thinking like a child, to use their curiosity to find new ways where you want to go, and to practice curiosity like a sport to keep from getting comfortable, and therefore static. “It made my not knowing what I can do so much more powerful than an expert's presumption of what he thought I could do,” she said. Session Highlights – Day 2 Consumer Trust What engenders trust as consumers? And what does it take to build online trust? With 51% of new account fraud victims personally knowing the perpetrator and 3.4 billion total losses from fraudulent account openings (Javelin Feb 2019), there are five key components to building trust: digital adoption, transparency, fraud management, recognition and authentication. Today’s consumers want to use the digital channel, have both security and ease of access, be recognized, know how their personal information is being used, and engage and trust with biometrics. Artificial Intelligence – Chat Bots and Beyond According to Gartner, “'Conversational AI-first' will supersede ‘cloud-first,’ ‘mobile first’ as the most important high-level imperative for the next 10 years.” As evidenced by Google Duplex’s realistic conversations with humans, including the use of “uh” and “um,” conversational AI is positioned to redefine the next generation of human interface, aimed at achieving better customer satisfaction and elevate the customer relationship. Marketing Analytics The marketing analytics landscape is changing. Today’s marketing problems – including the always limited budget and need to produce greater ROI – require tactical strategies to target the right consumers. Enter Experian’s AscendTM marketing platform. Leveraging this tool, including its neural networks that were demonstrated Monday morning, helps gain new insights into consumer behavior. Fraud in the Digital Wild West A panel discussion featuring representatives from Merchant Risk Council, USAA and Alliance Data compared fighting fraud to herding cats. Challenges discussed included the ongoing struggle to find balance between limiting friction during the authentication process, while also protecting customers, as well as fraudsters’ tendencies to tap into victims’ emotions and curiosity (think phishing schemes). As one of the panelists offered as a piece of advice, “Fraudsters share best practices, so should we.” Visibility for the Invisibles People are more than the sum of their parts. The traditional credit score may show a consumer’s reputation, but layering trended and alternative data sets adds their character. Not only can trended data and alternative credit data – including leveraging education attributes – make invisible consumers visible, they can also reveal that a consumer with a presumably superlative credit score is actually a “credit zombie.” These data sets enable the opportunity to create first chances, drive second chances and re-evaluate risk, while also driving a strong growth strategy. CECL After reviewing the basics of CECL and the upcoming deadlines (ranging from Q1 2020 to Q1 2022), a review of CECL compliance challenges and potential product changes preceded a modeling techniques case study and a list of key impacts to businesses. Those impacts include: product profitability, loss forecasting methodology, data management and processes and capital ratios. Experian’s CECL forecasting solution leverages Experian’s extensive historical data and Ascend Analytical Sandbox. Using a best practice modeling pipeline to improve efficiency and reduce operational risks, the solution combines advanced machine learning, traditional model techniques and modeling experience to improve performance and reduce risk of overfitting. Keynote Speaker: Kobe Bryant Kobe Bryant closed out the day with stories from his highly-decorated 20-year career with the Los Angeles Lakers, some tips on trash talk and lessons in leadership. “I had to figure out how to be undeniable,” Bryant said, on competing for minutes at the start of his career. In addition to his basketball legacy, including wining five NBA championships, being named an NBA MVP, a two-time NBA Finals MVP and winning two Olympic gold medals, Bryant also launched the Kobe and Vanessa Bryant Family Foundation, hosts the Kobe Academy and has formed Kobe Inc. He’s a storyteller, an Oscar winner, and his name has become synonymous with standing for uncompromising excellence. How to be successful? “Make sure you have the right people on the team,” Bryant said. “Passionate. Borderline obsessive.” One of his key takeaways from his basketball career that translates to his leadership on and off the court happened when his pre-game and game time thinking shifted from internal to external. “You have to put yourself 2nd, 3rd, 4th…you have to put the team first,” Bryant said.   For more coverage, follow #ExperianVision on Twitter or check the Experian Insights LinkedIn page.  

“Experian is transforming our business from a traditional credit bureau to a true technology and software provider,” said Craig Boundy, CEO of Experian, North America, as part of his opening remarks Monday morning to kick off the 2019 Experian Vision Conference. “We are committed to working as a force of good.” Covering the themes of financial inclusion, giving consumers control of their lives and better outcomes, a digital-first society, and the latest trends in fraud and security, Boundy addressed a crowd of over 850. Alex Lintner, Experian’s Group President, gave a quick history of the past 3,000 years, from the first credit card, to the addition of wheels to a suitcase, to the iPhone and artificial intelligence. “Innovation is not invention,” Lintner said. He gave the example of the iPhone and how a tear down analysis revealed there were no new elements; however, it was the translation of an idea into a good or service that benefited everyone (as the entire audience raised their hand when asked who had a smart phone). Lintner’s mainstage presentation also featured three live demos, including how the Ascend Technology Platform takes complex model building and outputs from days and weeks to a few clicks, to the incorporation of Small Business Financial Exchange (SBFE) data into the Ascend Analytical Sandbox (incorporating more than 17 years of small business tradeline data and 150 predictive attributes) and lastly, Experian Boost, which according to a live tracker, has boosted consumer credit scores by a total of 3.2 million points, as of this morning, since its launch eight weeks ago. Keynote Speaker: Gary D. Cohn Gary D. Cohn, Former Director of the U.S. National Economic Council, was Monday morning’s keynote speaker. He weighed in on the domestic and global economy, policy issues, financial institutions’ responsibilities and some of his predictions. Cohn brought attention to the ever-changing financial services space, including new forms of encryption and the world of biometric security, calling the financial services industry the “tip of the spear” when it comes to the digitization of the world. Session Highlights - Day 1 Machine Learning From the building blocks of neural networks to artificial intelligence, machine learning has been used in the areas of financial services that do not have adverse actions – think fraud, ID, collections. As we look to harness machine learning for models and other spaces (including adverse action), it’s important to delineate descriptive data (what’s happening now); predictive data (what’s happening in the future); prescriptive data (what am I going to do now); and cognitive data (are we asking the right question?). In addition, it’s necessary to address the five advanced analytic drivers including customer experience, cost, risk and loss, growth and compliance. Home Equity & Lending US macroeconomic trends show consumer confidence is still on an upward trend. While investor confidence is a little volatile, the GDP remains strong (though slightly slowing down) and unemployment is low and forecasted to remain low. Since 2006, the US hasn’t returned in the HELOC space. Mortgage and personal loans are up 20% and 13% respectively, while mortgages have dropped 1% and HELOCs have dropped 2%. With an estimated market potential of over $700 billion, HELOCs may be an untapped credit line given the strength of the economy. Identity Evolution From dumpster divers, aka pulling receipts out of dumpsters behind businesses, to today’s identity-based authentication, there’s been an evolution of how identity is defined as well as its corresponding risks. According to Experian’s Global Fraud & Identity Report, 74% of consumers value security as the most important part of the online experience (over convenience and personalization). However, 74% of consumers abandoned a shopping session that required too much information, and 72% of consumers said they were willing to share more data if it meant a seamless experience. What does this mean? Consumers want it all. Identity today now includes proxies and activity, which can also mean greater risk. Because of aggregators and other associated entities acting on a consumer’s behalf, there are lots of nuances that will need to be looked through. Consumer-Permissioned Data In order to be more consumer-centric, there are four levers through which consumers are given control: data accuracy, knowing their financial profile, the ability to improve their scores (via Experian BoostTM and UltraFICOTM) and protecting consumers when they permission access to their identity credentials. Using Experian Boost, consumers have seen an average increase of 13 points for consumers with positive changes. Additionally, using alternative credit data, financial institutions can score more people and score more accurately. One hundred million consumers could gain greater access to credit with consumer-permissioned data sources.   --- Meanwhile, the tech showcase featured over 20 demos covering alternative data, digital credit marketing, consumer empowerment, fraud and identity, integrated decisioning and technology. More insights from Vision to come. Follow @ExperianVision and #ExperianVision on Twitter to see more of the action.

Beginning with the birth of stock muscle cars, like the Pontiac GTO, vehicles with powerful V8 engines permeated the roads in the 1960s. Given consumers’ “need for speed,” these vehicles were synonymous with American culture following World War II - some going as far as to call muscle cars as American as apple pie. It’s no doubt that these vehicles have made an undeniable lasting impression on the automotive industry. Today, there are still automotive enthusiasts who appreciate the style and strength of the muscle car, but most of us want practical vehicles with better fuel economy and easy maintenance. This has resulted in a dramatic increase in the volume of 4-cylinder vehicles on the road.   As seen in the graphic above, over the last 11 years, 4-cylinder engines have increased in volume over 55%, 6-cylinder have declined 4% and 8-cylinders have increased 9.8%. More power, smaller engines This trend doesn’t necessarily mean that those of us who elect for a smaller engine size aren’t able to satisfy our need for speed. Horsepower has received a significant boost over the past two decades. This has been partially driven by EPA guidelines, as manufacturers have implemented engine enhancements to increase gas mileage to meet the guidelines, resulting in higher horsepower. 4-cylinder engines have as much horsepower today as 6-cylinder engines had in 2003. That gives today’s drivers a lot more pep in engine performance. Similarly, today's 6-cylinder engines have nearly the same horsepower today that V8s had in 2009. Where does that leave true muscle car enthusiasts? Well, if you are looking for raw power, things are looking up. In 2018, V8 engines averaged a whopping 370.4 horsepower, nearly double V8 output of 204 horsepower in 1999. Those who buy V8s today have power to burn. Above chart detailing percentage of total volume count and average vehicle MAX HP over history. The automotive market is driven by consumer preferences and offers a range of engine options, which provides something for everyone. The boost in horesepower in today’s engines provides a nice mix of fuel economy and performance. While muscle cars remain an important fixture in American society and automotive culture, demand has shifted and understanding these data points in the broader industry context empowers dealers to make the right inventory decisions. To learn more about the latest automotive trends impacting the marketplace, view the full Q4 2018 Automotive Market Trends Analysis.

Experian’s 38th annual Vision Conference kicks off on Sunday, May 5 in San Antonio, Texas. The sold-out thought leadership conference, is known for driving discussions on the industry’s hard-hitting topics as well as introducing the latest and greatest in technology, innovation and data science. “For 38 years, Experian’s Vision Conference has connected business leaders to new ideas and solutions through cutting edge data and insights. Our goal is to power opportunities for you to target new markets, grow existing customer bases, improve response rates, reduce fraud and increase profits by using our data, analytics and technology. The intimate setting of the conference allows for unique networking opportunities with the industry’s most sought-after thought leaders,” said Klaudette Christensen, Experian’s Chief Operations Officer. A few spotlight sessions include: Several sessions about machine learning and artificial intelligence, highlighting opportunities related to best practices, underwriting and fraud detection A deep dive into the modern mortgage, leveraging insights on home equity and how to leverage data and analytics to redefine the process as it’s known today Sessions on credit delinquency, collections and the Great Recession Marketing analytics and the latest releases from Experian’s Ascend Platform Sessions on advanced analytics and integrated decisioning as they relate to commercial and consumer insights The event, which runs through Tuesday evening, continues its tradition of featuring several noteworthy keynote speakers. On Monday, Gary D. Cohn, American business leader, philanthropist and former Director of the U.S. National Economic Council, will kick off the event. On Tuesday, Aimée Mullins will take the stage discussing what is “possible” by drawing from her experiences as a record-breaking Olympic athlete, model and actress. The closing keynote will feature five-time NBA Champion and two-time Olympic Gold Medalist, Kobe Bryant. The event will also include a Tech Showcase, featuring hands-on demos for attendees to experience. Stay tuned for additional highlights and insights on our social media platforms throughout the course of the conference. Follow Experian Insights on Twitter and LinkedIn and check out #ExperianVision.

Do more with less. Once the mantra of the life-hacking movement, it seems to be the charge given to marketers across the globe. Reduce waste; increase conversion rates; customize messages at a customer level; and do it all faster and more efficiently (read cheaper) than you did last quarter. The marketing challenges facing all companies seem to be more pronounced for financial institutions – not surprising for an industry with a reputation for late adoption. But doing more with less is not just a catchphrase thrown around by lean-obsessed consultants, it’s a response to key changes and challenges in the market. Here are 3 of the top marketing challenges creating business problems for financial institutions today. Budget constraints and misalignment As someone charged with the marketing remit in your firm, this probably comes as no surprise to you. Marketing budgets are stagnant, if not shrinking. Based on a 2018 report from CMO Survey, marketing budgets represent just over 11% of firm expenditures, a level which has remained largely constant over the last six years.Meanwhile, budgets at many financial firms appear to be out-of-touch with today’s ever-evolving market. In this Financial Brand report, virtually no financial institution committed more than 40% of their budget to mobile marketing, a stat unchanged from the prior two years. More channels mean even more segmentation Gone are the days where a company can rely heavily on traditional media to reach targets and clients. Now more than ever, your customers have access to a compounding amount of media on a proliferating number of channels. Some examples: In 2018, the Pew Research Center found most Americans (68%) get their news from social media. Cable companies recently followed streaming services to offer seamless service and experience across TV, desktop and mobile. Apple and Disney are two of several media juggernauts who are throwing their new streaming services and networks into the ring.This level of access is driving a shift in customers’ expectations for how, when and where they consume content. They want custom messages delivered in a seamless experience across the various channels they use. Shorter campaign cycles According to a recent study by Microsoft, humans now have shorter attention spans, at 8 seconds, than goldfish at 9 seconds. This isn’t surprising considering the levels of digital reach and access your customers are presented with. But this is also forcing a shortening of content and campaign cycles in response.   Marketers are now expected to plan, launch and analyze engaging campaigns to meet and stay ahead of customer need and expectation. Ironically, while there’s an intentional shortening of campaign cycles, there’s also a corporate focus to prolong and grow the customer relationship. It’s clear, competing in today’s world requires transforming your organization to address rapidly increasing complexity while containing costs. Competing against stagnant marketing budgets, proliferating media channels and shorter campaign cycles while delivering results is a formidable task, especially if your financial institution is not effectively leveraging data and analytics as differentiators. CMOs and their marketing teams must invest in new technologies and revisit product and channel strategies that reflect the expectations of their customers. How is your bank or credit union responding to these financial marketing challenges? Download Customer Acquisition eBook

If you’re a credit risk manager or a data scientist responsible for modeling consumer credit risk at a lender, a fintech, a telecommunications company or even a utility company you’re certainly exploring how machine learning (ML) will make you even more successful with predictive analytics. You know your competition is looking beyond the algorithms that have long been used to predict consumer payment behavior: algorithms with names like regression, decision trees and cluster analysis. Perhaps you’re experimenting with or even building a few models with artificial intelligence (AI) algorithms that may be less familiar to your business: neural networks, support vector machines, gradient boosting machines or random forests. One recent survey found that 25 percent of financial services companies are ahead of the industry; they’re already implementing or scaling up adoption of advanced analytics and ML. My alma mater, the Virginia Cavaliers, recently won the 2019 NCAA national championship in nail-biting overtime. With the utmost respect to Coach Tony Bennett, this victory got me thinking more about John Wooden, perhaps the greatest college coach ever. In his book Coach Wooden and Me, Kareem Abdul-Jabbar recalled starting at UCLA in 1965 with what was probably the greatest freshman team in the history of basketball. What was their new coach’s secret as he transformed UCLA into the best college basketball program in the country? I can only imagine their surprise at the first practice when the coach told them, “Today we are going to learn how to put on our sneakers and socks correctly. … Wrinkles cause blisters. Blisters force players to sit on the sideline. And players sitting on the sideline lose games.” What’s that got to do with machine learning? Simply put, the financial services companies ready to move beyond the exploration stage with AI are those that have mastered the tasks that come before and after modeling with the new algorithms. Any ML library — whether it’s TensorFlow, PyTorch, extreme gradient boosting or your company’s in-house library — simply enables a computer to spot patterns in training data that can be generalized for new customers. To win in the ML game, the team and the process are more important than the algorithm. If you’ve assembled the wrong stakeholders, if your project is poorly defined or if you’ve got the wrong training data, you may as well be sitting on the sideline. Consider these important best practices before modeling: Careful project planning is a prerequisite — Assemble all the key project stakeholders, and insist they reach a consensus on specific and measurable project objectives. When during the project life cycle will the model be used? A wealth of new data sources are available. Which data sources and attributes are appropriate candidates for use in the modeling project? Does the final model need to be explainable, or is a black box good enough? If the model will be used to make real-time decisions, what data will be available at runtime? Good ML consultants (like those at Experian) use their experience to help their clients carefully define the model development parameters. Data collection and data preparation are incredibly important — Explore the data to determine not only how important and appropriate each candidate attribute is for your project, but also how you’ll handle missing or corrupt data during training and implementation. Carefully select the training and validation data samples and the performance definition. Any biases in the training data will be reflected in the patterns the algorithm learns and therefore in your future business decisions. When ML is used to build a credit scoring model for loan originations, a common source of bias is the difference between the application population and the population of booked accounts. ML experts from outside the credit risk industry may need to work with specialists to appreciate the variety of reject inference techniques available. Segmentation analysis — In most cases, more than one ML model needs to be built, because different segments of your population perform differently. The segmentation needs to be done in a way that makes sense — both statistically and from a business perspective. Intriguingly, some credit modeling experts have had success using an AI library to inform segmentation and then a more tried-and-true method, such as regression, to develop the actual models. During modeling: With a good plan and well-designed data sets, the modeling project has a very good chance of succeeding. But no automated tool can make the tough decisions that can make or break whether the model is suitable for use in your business — such as trade-offs between the ML model’s accuracy and its simplicity and transparency. Engaged leadership is important. After modeling: Model validation — Your project team should be sure the analysts and consultants appreciate and mitigate the risk of over fitting the model parameters to the training data set. Validate that any ML model is stable. Test it with samples from a different group of customers — preferably a different time period from which the training sample was taken. Documentation — AI models can have important impacts on people’s lives. In our industry, they determine whether someone gets a loan, a credit line increase or an unpleasant loss mitigation experience. Good model governance practice insists that a lender won’t make decisions based on an unexplained black box. In a globally transparent model, good documentation thoroughly explains the data sources and attributes and how the model considers those inputs. With a locally transparent model, you can further explain how a decision is reached for any specific individual — for example, by providing FCRA-compliant adverse action reasons. Model implementation — Plan ahead. How will your ML model be put into production? Will it be recoded into a new computer language, or can it be imported into one of your systems using a format such as the Predictive Model Markup Language (PMML)? How will you test that it works as designed? Post-implementation — Just as with an old-fashioned regression model, it’s important to monitor both the usage and the performance of the ML model. Your governance team should check periodically that the model is being used as it was intended. Audit the model periodically to know whether changing internal and external factors — which might range from a change in data definition to a new customer population to a shift in the economic environment — might impact the model’s strength and predictive power. Coach Wooden used to say, “It isn’t what you do. It’s how you do it.” Just like his players, the most successful ML practitioners understand that a process based on best practices is as important as the “game” itself.

Earlier this month, Experian joined the nation’s largest community of online lenders at LendIt Fintech USA 2019 in San Francisco, CA to show over 5,000 attendees from 50 countries the ways consumer-permissioned data is changing the credit landscape. Experian Consumer Information Services Group President, Alex Lintner, and FICO Chief Executive Officer, Will Lansing, delivered a joint keynote on the topic of innovation around financial inclusion and credit access. The keynote addressed the analytical developments behind consumer-permissioned data and how it can be leveraged to responsibly and securely extend credit to more consumers. The session was moderated by personal finance expert, Lynnette Khalfani-Cox, from The Money Coach. “Consumer-permissioned data is not a new concept,” said Lintner. “All of us are on Facebook, Twitter, and LinkedIn. The information on these platforms is given by consumers. The way we are using consumer-permissioned data extends that concept to credit services.” During the keynote, both speakers highlighted recent company credit innovations. Lansing talked about UltraFICO™, a score that adds bank transaction data with consumer consent to recalibrate an existing FICO® Score, and Lintner discussed the newly launched Experian Boost™, a free, groundbreaking online platform that allows consumers to instantly boost their credit scores by adding telecommunications and utility bill payments to their credit file. “If a consumer feels that the information on their credit files is not complete and that they are not represented holistically as an applicant for a loan, then they can contribute their own data by giving access to tradelines, such as utility and cell phone payments,” explained Lintner. There are approximately 100 million people in America who do not have access to fair credit, because they are subprime, have thin credit files, or have no lending history. Subprime consumers will spend an additional $200,000 over their lifetime on the average loan portfolio. Credit innovations, such as Experian Boost and UltraFICO not only give consumers greater control and access to quality credit, but also expand the population that lenders can responsibly serve while providing a differentiated and competitive advantage. “Every day, our data is used in one million credit decisions; 350 million per year,” said Lintner. “When our data is being used, it represents the consumers’ credit reputation. It needs to be accurate, it needs to be timely and it needs to be complete.” Following the keynote, Experian, FICO, Finicity and Deserve joined forces in a breakout panel to dive deeper into the concept of consumer-permissioned data. Panel speakers included Greg Wright, Chief Product Officer at Experian’s Consumer Information Services; Dave Shellenberger, Vice President of Product Management at FICO; Nick Thomas, Co-Founder, President and Chief Technology Officer at Finicity, and Kalpesh Kapadia, Chief Executive Officer at Deserve. “As Alex described in today’s keynote, consumer-permissioned data is not a new concept,” said Greg Wright. “The difference here is that Experian, FICO and Finicity are applying this concept to credit services, working together to bring consumer-permissioned data to mass scale, so that lenders can reach more people while taking on less risk.” For an inside look at Experian and FICO’s joint keynote, watch the video below, or visit Experian.com and boost your own credit score.

So often a microscope is set on examining millennials and their behaviors – especially when it comes to their priorities and finances. But there’s a new generation entering the economy, with an entirely new set of preferences, behaviors and approach to money. Enter Gen Z. According to Bloomberg, this year, Generation Z becomes the biggest consumer cohort globally, “displacing millennials as a top obsession for investors.” This generation (falling between the ages of seven and 22) is 61 million strong and has a spending power of $143 billion in the U.S. alone. While much of the population that makes up Generation Z may still be in school, they are already creating their reputation as conscientious consumers. And lenders and financial institutions need to get in front of them if they want a chance at these meaningful investments. Because this generation has grown up in a world where the internet has always existed, everything can be ordered and delivered on demand, and communications occur over mobile platforms like Instagram and Snapchat, they view the world – and finances – through a different lens. Bloomberg suggests the following Gen Z broad trends; which investors should consider if they want this growing generation in their portfolios: They can be influenced. According to a recent Bloomberg survey, 52% of Gen Zers said they primarily find out about new products from social media. And they are 3 times more likely to purchase a product recommended by one of their favorite influencers than by a television or film celebrity. They have different vices – beyond just their smartphone addictions. As they are growing up in a world where screen time is eminent and cannabis is becoming legal (already legal in 10 U.S. states), they live with a different world view than many of the other generations. They don’t have to go to stores. Gen Z shops via clicks, not bricks. They choose their brand loyalties carefully. This generation is interested in environmental issues and ethical shopping, which drives their consumer activities, meaning it’s time for new considerations when it comes to marketing. They eat differently. Less likely to eat meat, we’re already seeing the shift that fast-food restaurants and packaged-food distributors are taking. What does this mean for financial institutions? You don’t have to be a social media influencer to get Gen Z in your portfolio – but it wouldn’t hurt. Many reports indicate that by 2020, Gen Z will command nearly 40% of all consumer shopping. With shopping driven by scrolling and purpose-driven purchases facilitated primarily by online transactions, gaining an understanding of these young consumers’ credit and charge card habits means you can better understand bankcard wallet share and target them as they start joining the workforce and beyond. In the not-too-distant future, there will be a need to examine high spend to increase interchange income. Trended data solutions can gain insight into these consumers as well as help you target and offer new lines of credit as they purchase with purpose – fueling them with credit to fund the ventures that matter to them most. Learn More  

With the number of consumer visits to bank branches having declined from 52% of people visiting their bank branch on a monthly basis to 32% since 2015, the shift in banking to digital is apparent. Rather than face-to-face interaction, today’s financial consumers value remote, on-demand, services. They expect instant credit decisioning, immediate account funding, and around-the-clock customer assistance. To adapt, financial service providers see the necessity to respond to consumers’ growing expectations and become part of their overall digital lifestyle. Here are a few ways that financial services can adjust to changing consumer behavior: Drive mobile app activity With more than 50% of the world’s population actively using smartphones, the popularity of mobile banking apps has soared. Mobile apps have revolutionized the banking sector by facilitating easier communication between clients and institutions, offering value-added services, and introducing blockchain technologies. Consumers use mobile banking apps to pay bills, transfer funds, deposit checks, and make person-to-person payments. In fact, according to a study by Bank of America, more than 60% of millennials use mobile apps to make person-to-person payments on a regular basis! Financial institutions who launch new, or invest in enhancing existing mobile apps, can lower their overall costs, increase ROI, and maintain customer loyalty. Provide convenience and rewards CGI conducted a survey on emerging financial consumer trends, focusing on bank customers’ top requirements. Results confirmed that 81% of respondents expected to receive some form of an incentive from their primary banks. Today’s financial consumers may reasonably be won over by service offerings. They want rewards, limited fees, and convenience. As an example, Experian’s Text for CreditTM simplifies the credit process by providing customers with instant credit decisioning through their mobile devices. Personalized offers based on customer behavior can help enhance your brand and attract new customers. Stay connected Today’s consumers expect instant service and gratification. Consumers prefer to work with banks who offer accessible and responsive customer service. According to a recent NGDATA consumer banking survey, 41% of banking customers report that poor customer service is the primary reason they would leave their bank. Mintel suggests developing an omnichannel experience aligned with consumer media consumption. Stay connected with consumers through mobile apps, chatbots, social media, and email. Ensure that all interactions are relevant and helpful and immediately alert customers of any institutional issues or changes. The growing digital demands of consumers are influencing how people purchase banking, lending, and credit services. These changes are driving increased urgency for financial service institutions to adopt real-time financial processes that meet demands for convenience and speed. Interested in more best practices? Watch our On-Demand Webinar

When it comes to new vehicle registration, there is one segment that stands out from the pack: crossover vehicles. According to Experian’s Q4 2018 Automotive Market Trends Analysis, over the last four years, crossovers (CUVs) have spiked in popularity, representing about a third of new vehicle registrations in 2014 (34.1 percent), but growing to nearly half the new vehicle market in 2018 (47.6 percent). In fact, the large growth in CUVs isn’t limited to just the last four years – there was a large volume of growth year-over-year compared to 2017; the share has grown nearly 4 percent. Sedans and hatchbacks, meanwhile, have seen their share decrease year-over-year. The charts below detail this change in market, based on Experian’s latest 2018 quarterly findings. Source: Experian Automotive VIO as of December 31, 2018 (light duty registered vehicles only) What’s driving this growth? Across the board, the number of light-duty vehicles on the road continues to increase, up to 275.3 million in the U.S. market, at the end of 2018, compared to 271.4 million a year prior. The growth in CUVs isn’t entirely unprecedented, as it’s been going on for a number of years.  CUVs continue to grow in popularity for a variety of reasons including: Greater visibility, as the driver sits higher than in a sedan/coupe Larger storage capacities for passengers or cargo Number of varieties available, such as size, engines, and manufactures Higher fuel efficiency than a full-size SUV or minivan Currently, there are over 130 different CUV/SUV Make/Model combos offered, and of those, the different engines, options, etc. drive that volume even higher. Source: Experian Automotive VIO as of December 31, 2018 (light duty registered vehicles only) Potential for growth Currently, there are only two CUVs among the top vehicles in the aftermarket “sweet spot.” Vehicles in the sweet spot are 6 to 12 model years old, and typically aged out of general OEM warranties for any repairs. These vehicles likely require more part replacement services, which may be performed by aftermarket service shops using parts from aftermarket part manufacturers. According to Experian data, the sweet spot has stopped falling and has settled for now. But, there is expected growth of the number of vehicles that fall into the sweet spot over the coming years. One of the segments where the aftermarket industry can begin to focus on will be CUVs. Source: Experian Automotive VIO as of December 31, 2018 (light duty registered vehicles only) The aftermarket can use this data to make more informed product decisions, specifically, around the high volume of CUVs expected to come into the sweet spot. With the number of vehicle options available on the market today, CUVs will continue to 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 CUVs and its potential for even greater growth. To learn more about CUVs/SUVs and total vehicles in operation, view the full Q4 2018 Automotive Market Trends Analysis.