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Big data is bringing changes to the way credit scores are reported and making it easier for lenders to find creditworthy consumers, and for consumers to qualify for the financing they need. Since last year’s annual report, alternative credit data1 has continued to gain in popularity. In Experian’s latest 2020 State of Alternative Credit Data report, we take a closer look at why alternative credit data is supplemental and essential to consumer lending and how it’s being adopted by both consumers and financial institutions. While the topic of alternative credit data has become more well known, its capabilities and benefits are still not widely discussed. For instance, did you know that … 89% of lenders agree that alternative credit data allows them to extend credit to more consumers. 96% of lenders agree that in times of economic stress, alternative credit data allows them to more closely evaluate consumer’s creditworthiness and reduce their credit risk exposure. 3 out of 4 consumers believe they are a better borrower than their credit score represents. Not only do consumers believe they’re more financially astute than their credit score depicts – but they’re happy to prove it, with 80% saying they would share various types of financial information with lenders if it meant increased chances for approval or improved interest rates. This year’s report provides a deeper look into lenders’ and consumers’ perceptions of alternative credit data, as well as an overview of the regulatory landscape and how alternative credit data is being used across the lending marketplace. Lenders who incorporate alternative credit data and machine learning techniques into their current processes can harness the data to unlock their portfolio’s growth potential, make smarter lending decisions and mitigate risk. Learn more in the 2020 State of Alternative Credit Data white paper. Download now

No one was quite prepared for COVID-19 and its unprecedented impact on the automotive industry. Factories shutdown, dealerships closed and sales plummeted. But, now as the market begins to recover, the environment looks different than it did before. In order to move forward and rebound from the pandemic, manufacturers and dealers need to rely on market trends and insights to assess their go-forward strategy. As expected, new and used vehicle registrations experienced significant declines compared to last year. According to Experian’s Q2 2020 Market Trends Review, there were 6.4 million new vehicle registrations through the first half of the year, down from 8.4 million a year ago; used vehicle registrations came in at 18.3 million, down from 21.8 million over the same period. Despite the significant drop in new and used vehicle registrations at the onset of the pandemic, a positive trend is emerging. In March, when COVID-19 was officially declared a pandemic, the volume of new vehicle registrations dropped by approximately 460,000 compared to February; a similar trend was observed on the used vehicle side, where registrations declined by as much as 1.6 million. We have since seen new and used vehicle registrations slowly approach pre-pandemic levels; and in some instances, exceed them. In both June and July, there were approximately 1.2 million new vehicle registrations; only about 120,000 off February levels—and used vehicle registrations actually surpassed the February mark, in both June and July by surpassing 3.7 million vehicles each month. This positive trend eludes to a cautious return to normalcy as stay-at-home orders lift and consumers once again consider purchasing vehicles. But with more consumers re-entering the automotive market, understanding which vehicles are most in demand is crucial to meeting the needs of car buyers. The top three makes for new vehicle registrations for consumers were GM (13.9%), Toyota (12.4%) and Ford (10.1%). Meanwhile, the top three make and models include Ford F-150 (3.4%), Chevy Silverado 1500 (3.3%) and Toyota RAV4(3.1%). Beyond the preferred makes and models, the industry needs to understand who is buying cars. And contrary to popular belief, Millennials and Gen Z have actually increased their car purchasing. Both groups saw an increase in the percentage of consumers purchasing vehicles, while Baby Boomers and Gen X saw a decrease. It’s important to note, Baby Boomers, Millennials and Gen Xers still make up the majority of consumers purchasing new vehicles. People are at different points in the COVID-19 recovery lifecycle. Understanding who is in the market for a vehicle and what they are looking for is more important than ever. As the market rebounds, manufacturers and dealers can both meet the demands of consumers and increase sales by identifying in-market car shoppers and reaching them with relevant messages. For example, Millennials might be more receptive to digital messaging across many platforms while Baby Boomers and Gen X consumers may gravitate towards print. It’s these small details that will carry messaging further. As consumers begin to reconsider automotive purchases, manufacturers and dealers can stay one step ahead by digging into the data. Staying ahead of the trends and adjusting to what lies ahead, will not only support sales growth, but also support consumers as they begin to recover from the impact of COVID-19. To view Experian's full Q2 2020 Market Trends Review, click here

Changing consumer behaviors caused by the COVID-19 pandemic have made it difficult for businesses to make good lending decisions. Maintaining a consistent lending portfolio and differentiating good customers who are facing financial struggles from bad actors with criminal intent is getting more difficult, highlighting the need for effective decisioning tools. As part of our ongoing Q&A perspective series, Jim Bander, Experian’s Market Lead, Analytics and Optimization, discusses the importance of automated decisions in today’s uncertain lending environment. Check out what he had to say: Q: What trends and challenges have emerged in the decisioning space since March? JB: In the age of COVID-19, many businesses are facing several challenges simultaneously. First, customers have moved online, and there is a critical need to provide a seamless digital-first experience. Second, there are operational challenges as employees have moved to work from home; IT departments in particular have to place increase priority on agility, security, and cost-control. Note that all of these priorities are well-served by a cloud-first approach to decisioning. Third, the pandemic has led to changes in customer behavior and credit reporting practices. Q: Are automated decisioning tools still effective, given the changes in consumer behaviors and spending? JB: Many businesses are finding automated decisioning tools more important than ever. For example, there are up-sell and cross-sell opportunities when an at-home bank employee speaks with a customer over the phone that simply were not happening in the branch environment. Automated prequalification and instant credit decisions empower these employees to meet consumer needs. Some financial institutions are ready to attract new customers but they have tight marketing budgets. They can make the most of their budget by combining predictive models with automated prescreen decisioning to provide the right customers with the right offers. And, of course, decisioning is a key part of a debt management strategy. As consumers show signs of distress and become delinquent on some of their accounts, lenders need data-driven decisioning systems to treat those customers fairly and effectively. Q: How does automated decisioning differentiate customers who may have missed a payment due to COVID-19 from those with a history of missed payments? JB: Using a variety of credit attributes in an automated decision is the key to understanding a consumer’s financial situation. We have been helping businesses understand that during a downturn, it is important for a decisioning system to look at a consumer through several different lenses to identify financially stressed consumers with early-warning indicators, respond quickly to change, predict future customer behavior, and deliver the best treatment at the right time based on customer specific situations or behaviors. In addition to traditional credit attributes that reflect a consumer’s credit behavior at a single point in time, trended attributes can highlight changes in a consumer’s behavior. Furthermore, Experian was the first lender to release new attributes specifically created to address new challenges that have arisen since the onset of COVID. These attributes help lenders gain a broader view of each consumer in the current environment to better support them. For example, lenders can use decisioning to proactively identify consumers who may need assistance. Q: What should financial institutions do next? JB: Financial institutions have rarely faced so much uncertainty, but they are generally rising to the occasion. Some had already adopted the CECL accounting standard, and all financial institutions were planning for it. That regulation has encouraged them to set aside loss reserves so they will be in better financial shape during and after the COVID-19 Recession than they were during the Great Recession. The best lenders are making smart investments now—in cloud technology, automated decisioning, and even Ethical and Explainable Artificial Intelligence—that will allow them to survive the COVID Recession and to be even more competitive during an eventual recovery. Financial institutions should also look for tools like Experian’s In the Market Model and Trended 3D Attributes to maximize efficiency and decisioning tactics – helping good customers remain that way while protecting the bottom line. In the Market Models Trended 3D Attributes About our Expert: [avatar user="jim.bander" /] Jim Bander, PhD, Market Lead, Analytics and Optimization, Experian Decision Analytics Jim joined Experian in April 2018 and is responsible for solutions and value propositions applying analytics for financial institutions and other Experian business-to-business clients throughout North America. He has over 20 years of analytics, software, engineering and risk management experience across a variety of industries and disciplines. Jim has applied decision science to many industries, including banking, transportation and the public sector.
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