Models & Scores

As industry experts are still unsure when the economy will fully recover, re-entry into marketing preapproved credit offers seems like a far-off proposal. However, several of the top credit card issuers are already mailing prescreen offers, with many other lenders following suit. When the time comes for organizations to resume, or even expand this type of targeting, odds are that the marketing budget will be tighter than in the past. To make the most of the limited available marketing spend, lenders will need to be more prescriptive with their selection process to increase response rates on fewer delivered offers. Choosing the best candidates to receive these offers, from a credit risk perspective, will be critical. With delinquencies being suppressed due to CARES Act reporting guidelines, identifying consumers with the ability to repay will require additional assessment of recent credit behavior metrics, such as actual payment amounts and balance migration. Along with the presence of explicit indicators of accommodated trades (trades affected by natural disaster, trades with a balance but no scheduled payment amount) on a prospect’s credit file, their recent trends in payments and balance shifts can be integral in determining whether a prospect has been adversely impacted by today’s economic environment. Once risk criteria have been developed using a mix of bureau scores (like the VantageScore® credit score), traditional credit attributes and trended attributes measuring recent activity, additional targeting will be critical for selecting a population that’s most likely to open the relevant trade type. For credit cards and personal installment loans, response performance can be greatly improved by aligning product offers with prospects based on their propensity to revolve, pay in full each month or consolidate balances. Additionally, the process to select final prospects should integrate a propensity to open/respond assessment for the specific offering. While many lenders have custom models developed on previous internal response performance, off-the-shelf propensity to open models are also available to provide an assessment of a prospect’s likelihood to open a particular type of trade in the coming months. These models can act as a fast-start for lenders that intend to develop internal custom models, but don’t have the response performance within a particular product/geography/risk profile. They are also commonly used as a long-term solution for lenders without an internal model development team or budget for an outsourced model. Prescreen selection best practices Identify geography and traditional credit risk assessment of the prospect universe. Overlay attributes measuring accommodated trades and recent payment/balance trends to identify prospects with indications of ability to pay. Segment the prospect universe by recent credit usage to determine products that would resonate. Make final selections using propensity to open model scores to increase response rates by only making offers to consumers who are likely looking for new credit offers. While the best practices listed above don’t represent a risk-free approach in these uncertain times, they do provide a framework for identifying prospects with mitigated repayment risk and insights into the appropriate credit offer to make and when to make it. Learn about in the market models Learn about trended attributes VantageScore® is a registered trademark of VantageScore Solutions, LLC.

Profitability analysis is one of the most powerful analytics tools in business and strategy development. Yet it’s underrated, deemed too complicated and often ignored. A chief lending officer may state that the goal of strategy development is to increase approvals or to reduce losses. Each one of these goals has an impact generally inversely on each other. That impact may be consequential, and evaluating the effects requires deeper thought and discipline. I propose that the benefits of a profitability analysis in strategy development are worth the additional effort, time and cost. Profitability analysis provides a disciplined framework for making business decisions. For financial companies, a simple profit and loss (P&L) statement will identify interest income, subtract losses and arrive at a risk-adjusted yield. A more robust P&L statement will include interest expense, loss reserves, recovery, fees and other income, operating expenses, other cost per account, and net income. Whether simplified or fully loaded, a P&L analysis used in strategy development must provide a clear and informative representation of key performance metrics and risks. The most important benefit of a profitability analysis is its inherent ability to quantify the trade-offs between risk and rewards. In the P&L terminology, we mean the trade-off between expenses and revenue or losses and interest income. Understanding trade-offs allows companies to make informed decisions and explore serious alternatives. The net income is a concise and elegant metric that captures the impact of various and sometimes competing business objectives. Consider different divisions within a financial organization. Each division has its own specific and measurable objective. Marketing’s goal is to increase loan approvals while Risk is tasked with managing losses. Operations looks to improve efficiencies while IT aims to provide stable, reliable and accurate systems infrastructure. Legal and Compliance ensure regulatory compliance across the entire organization. Each division working to achieve its objectives creates externalities — each division’s actions may not fully incorporate costs imposed on other divisions. For example, targeting highly responsive consumers for a loan product achieves higher loan approvals and may in turn lead to higher credit risk losses. A P&L analysis imposes the discipline for each division to internalize costs and lead to a favorable and efficient outcome for the organization. The challenge with profitability analysis in strategy development is how to develop a good P&L statement. We look to historical data to define assumptions and calibrate inputs to the P&L. There will be uncertainty and concerns regarding the reliability and quality of such data. Organizations don’t regularly conduct test and control experiments or champion and challenger strategies that provide actual performance information on specific areas of studies. Though imperfect, historical data provides a starting foundation for profitability analysis. We augment historical data with predictive credit attributes, industry experience and understanding consumer behavior and incentives. For example, to estimate interest income we may utilize estimated interest rates combined with balance propensity behavior, such as a balance revolver or transactor. To estimate losses on declined population that may be considered for approval, we infer on-us performance using off-us performance with other lenders. Defining assumptions is tedious, hard work and full of uncertainty. This exercise once again imposes the discipline required of organizations to know in detail the characteristics of their products and businesses that make them relevant to consumers. We generate P&L simulations using a set of assumptions, acknowledge the data limitations and evaluate recommendations. A profitability analysis is useful in both times of economic expansion and contraction. A P&L analysis is valuable when evaluating strategies across the customer life cycle. Remember, we live in a world of trade-offs and choices are inevitable. In the prospecting and acquisition life cycle, a P&L analysis provides insights on approval expansion and the consequences of higher credit losses. Alternatively, tighter lending criteria will have a direct impact on balance growth and interest income with lower losses. In account management, a P&L analysis provides estimates on expanded account authorization limits and the effect on activation and usage. In collections, a P&L analysis provides valuation on recoveries and operational costs. These various assessments are quantified in the P&L and allows the organization to identify other mechanisms such as marketing campaigns, customer services or technology investments in support of the organization’s goals and mission. Organizations face a full spectrum of opportunities and risks. We propose a profitability analysis to evaluate business trade-offs, navigate the marketplace, and continue to provide relevant financial products and services to consumers and businesses. Learn more

This is the fourth in a series of blog posts highlighting optimization, artificial intelligence, predictive analytics, and decisioning for lending operations in times of extreme uncertainty. The first post dealt with optimization under uncertainty, the second with predicting consumer payment behavior, and the third with validating consumer credit scores. This post describes some specific Experian solutions that are especially timely for lenders strategizing their response to the COVID Recession. Will the US economy recover from the pandemic recession?  Certainly yes. When will the economy recover? There is a lot more uncertainty around that question. Many people are encouraged by positive indicators, such as the initial rebound of the stock market, a return of many of the jobs lost at the beginning of the pandemic, and a significant increase in housing starts. August’s retail spending and homebuilder confidence are very encouraging economic indicators. Other experts doubt that the “V-shaped” recovery can survive flare-ups of the virus in various parts of the US and the world, and are calling for a “W-shaped” recovery.  Employment indicators are alarming: many people remain out of work, some job losses are permanent, and there are more initial jobless claims each week now than at the height of the Great Recession. Serious hurdles to economic recovery may remain until a vaccine is widely available: childcare, urban transportation, and global trade, for example. I’m encouraged by the resilience of many of our country’s consumer lenders. They are generally responding well to these challenges. If past recessions are a guide, some lenders will not survive these turbulent times. This time, many lenders—whether or not they have already adopted the CECL accounting standards—have been increasing allowances for their anticipated credit losses. At least one rating agency believes major banks are prepared to absorb those losses from earnings.  The lenders who are most prepared for the eventual recovery will be those that make good decisions during these volatile times and take action to put themselves in the best position in anticipation of the recovery that will certainly follow. The best lenders are making smart investments now to be prepared to capitalize on future opportunities. Experian’s analytics and consulting experts are continuously improving our suite of solutions that help consumer lenders and others assess consumer behavior and respond quickly to the rapidly fluctuating market conditions as well as changing regulations and credit reporting practices. Our newly announced Economic Response and Recovery Suite includes the ABCD’s that lenders need to be resilient and competitive now and to prepare to thrive during the eventual recovery: A – Analytics. As I’ve written about in prior blog posts, data is a prerequisite to making good business decisions, but data alone is not enough. To make wise, insightful decisions, lenders need to use the most appropriate analytical techniques, whether that means more meaningful attributes, more predictive and compliant credit scores, more accurate and defensible loss forecasting solutions, or optimization systems that help develop strategies in a world where budgets, regulations, and other constraints are changing. For example, Experian has released a set of Spotlight 2020 Attributes that help consumer lenders create a positive experience for customers who have received an accommodation during the pandemic. In many cases motivated by the new race to improve customer experience online, and in other cases as a reaction to new and creative fraud schemes, some clients are using this period as an opportunity to explore or deploy ethical and explainable Artificial Intelligence. B – Business Intelligence. Credit bureaus like Experian are uniquely situated to understand the impact of the COVID recession on America’s consumers. With impact reports, dashboards, and custom business intelligence solutions, lenders are working during the recession to gain an even better understanding of their current and prospective customers. We’re helping many of them to proactively help consumers when they need it most. For example, lenders have turned to us to understand their customer’s payment hierarchy—which bills they pay first when times are tough. Our free COVID-19 US Business Risk Index helps make lending options available to the businesses who need them most. And we’ve armed lenders with recommendations for which of our pre-existing attributes and scores are most helpful during trying times. Additional reporting tools such as the Auto Market Tracker, Ascend Market Insights Dashboard, and the weekly economic update video provide businesses with information on new market trends—information that helps them respond during the recession and promises to help them grow during the eventual recovery. C – Consulting. It’s good to turn data into information and information into insight, but how do these lenders incorporate these insights in their business strategies? Lenders and other businesses have been turning to Experian’s analytics and Advisory services consultants to unlock the information hidden in credit and other data sources—finding ways to make their business processes more efficient and more effective while developing quick response plans and more long-term recovery strategies. D – Delivery.  Decision science is the practice of using advanced analytics, artificial intelligence, and other techniques to determine the best decision based on available data and resources. But putting those decisions into action can be a challenge. (Organizations like IBM and Gartner estimate that a great majority of data science projects are never put into production.) Experian technologies—from our analytics platform to our attribute integration and decision management solutions ensure that data-driven decisions can be quickly implemented to make a real difference. Treating each customer optimally has a number of benefits—whether you are trying to responsibly grow your portfolio, reduce credit losses and allowances, control servicing costs, or simply staying in compliance during dynamic times. In the age of COVID, IT departments have placed increased priority on agility, security, customer experience, and cost control, and appreciate cloud-first approach to deploying analytics. It’s too early to know how long this period of extreme uncertainty will last. But one thing is certain: it will come to an end, and the economy will recover someday. I predict that many of the companies that make the best use of data now will be the ones who do the best during the recovery. To hear more ways your organization can navigate this downturn and the recovery to follow, please watch our on-demand webinar and check out our Economic Response and Recovery Suite. Watch the Webinar

In today’s uncertain economic environment, the question of how to reduce portfolio volatility while still meeting consumers’ needs is on every lender’s mind.  With more than 100 million consumers already restricted by traditional scoring methods used today, lenders need to look beyond traditional credit information to make more informed decisions. By leveraging alternative credit data, you can continue to support your borrowers and expand your lending universe. In our most recent podcast, Experian’s Shawn Rife, Director of Risk Scoring and Alpa Lally, Vice President of Data Business, discuss how to enhance your portfolio analysis after an economic downturn, respond to the changing lending marketplace and drive greater access to credit for financially distressed consumers. Topics discussed, include: Making strategic, data-driven decisions across the credit lifecycle Better managing and responding to portfolio risk Predicting consumer behavior in times of extreme uncertainty Listen in on the discussion to learn more. Experian · Effective Lending in the Age of COVID-19

Do consumers pay certain types of credit accounts before others during financial distress? For instance, do they prioritize paying mortgage bills over credit card bills or personal loans? During the Great Recession, the traditional notion of payment priority among multiple credit accounts was upended, throwing strategies employed by financial institutions into disarray. Similarly, current circumstances in the context of COVID-19 might cause sudden shifts in prioritization of payments which might have a dramatic impact on your credit portfolio. Financial institutions would be better able to forecast and control exposure to credit risk, and to optimize servicing practices such as forbearance and collections treatments if they could understand changing customer payment behaviors and priorities of their existing customers across all open trades.  Unfortunately, financial institutions’ data—including their own behavioral data and refreshed credit bureau data--are limited to information about their own portfolio. Experian data provides insight which complements the financial institutions’ data expanding understanding of consumer payment behavior and priorities spanning all trades. Experian recently completed a study aimed at providing financial institutions valuable insights about their customer portfolios prior to COVID-19 and during the initial months of COVID-19. Using the Experian Ascend Technology Platform™, our data scientists evaluated a random 10% sample of U.S. consumers from its national credit file. Data from multiple vintages were pulled (June 2006, June 2008 and February 2018) and the payment trends were studied over the subsequent performance period. Experian tabulated the counts of consumers who had various combinations of open and active trade types and selected several trade type combinations with volume to differentiate performance by trade type. The selected combinations collectively span a variety of scenarios involving six trade types (Auto Loans, Bankcard, Student Loan, Unsecured Personal Loans, Retail Cards and First Mortgages). The trade combinations selected accommodate a variety of lenders offering different products. For each of the consumer groups identified, Experian calculated default rates associated with each trade type across several performance periods. For brevity, this blog will focus on customers identified as of February 2018 and their subsequent performance through February 2020. As the recession evolves and when the economy eventually recovers, we will continue to monitor the impacts of COVID-19 on consumer payment behavior and priorities and share updates to this analysis. Consumers with Bankcard, Mortgage, Auto and Retail accounts Among consumers having open and recently active Bankcard, Mortgage, Auto and Retail accounts, bankcard delinquency was highest throughout the 24-month performance window, followed by Retail.  Delinquency rates for Auto and Mortgage were the lowest. During the pre-COVID-19 period, consumers paid their secured loans before their unsecured loans. As demonstrated in the table below, customer payment priority was stable across the entire 24-month period, with no significant shift in payment priorities between trade types. Consumers with Unsecured Personal Loan, Retail Card and Bankcard accounts. Among consumers having open and recently active Unsecured Personal Loan, Retail Card and Bankcard accounts, consumers are likely to pay unsecured personal loans first when in financial distress. Retail is the second priority, followed by Bankcard. KEY FINDINGS From February 2018 through April 2020, relative payment priority by trade type has been stable Auto and Mortgage trades, when present, show very high payment priority Download the full Payment Hierarchy Report here. Download Now Learn more about how Experian can create a custom payment hierarchy for the customers in your own portfolio, contact your Experian Account Executive, or visit our website.

Account management is a critical strategy during any type of economy (pro-cycle, counter-cycle, cycle neutral). In times like these, marked by economic volatility, it is an effective way to identify which parts of your portfolio and which of your consumers need the most attention. Check out this podcast where Cyndy Chang, Senior Director of Product Management, and Craig Wilson, Senior Director of Consulting, discuss the foundational elements of account management, best practices and use cases. Account management today looks very different than what it has been during over a decade of growth proactive; account review is a critical part of navigating the path forward. Questions that need to be addressed include: Do you have the right data? Are you monitoring between data loads? Are you reviewing accounts at the frequency that today’s changing demands require? Listen in on the discussion to learn more. Experian · Look Ahead Podcast

Today, Experian and Oliver Wyman launched the Ascend Portfolio Loss ForecasterTM, a solution built to help lenders make better decisions – during COVID-19 and beyond – with customized forecasts and macroeconomic data. Phrases like “the new normal,” “unprecedented times,” and “extreme economic volatility” have flooded not only media for the last few months, but also financial institutions’ strategic discussions regarding plans to move forward. What has largely been crisis response is quickly shifting to an urgent need to answer the many questions around “Will we survive this crisis?,” let alone “What’s next?” And arguably, we’ve entered a new era of loss forecasting. After the longest period of economic growth in post-war U.S. history, previously built models are not sufficient for the unprecedented and sudden changes in economic conditions due to COVID-19. Lenders need instant insights to assess impact and losses to their portfolios. The Ascend Portfolio Loss Forecaster combines advanced modeling from Oliver Wyman,  pandemic-specific insights and macroeconomic scenarios from Oxford Economics, and Experian’s quality data to analyze and produce accurate loan loss forecasts. Additionally, all of the data, including the forecasts and models, are regularly updated as macroeconomic conditions change. “Experian’s agility and innovative technologies allow us to help lenders make informed decisions in real time to mitigate future risk,” said Greg Wright, chief product officer of Experian’s Consumer Information Services, in a recent press release. “We’re proud to work with our partners, Oxford Economics and Oliver Wyman, to bring lenders a product powered by machine learning, comprehensive data and macroeconomic forecast scenarios.” Built using advanced modeling and expert scenarios, the web-based application maximizes the more than 15 years of Experian’s loan-level data, including VantageScore® credit score, bankruptcy scores and customer-level attributes.  Financial institutions can gauge loan portfolio performance under various scenarios. “It is important that the banks take into account the evolving credit behaviors due to the COVID-19 pandemic, in addition to the robust modeling technique for their loss forecasting and strategic decisioning,” said Anshul Verma, senior director of products at Oliver Wyman, also in the release. “With the Ascend Portfolio Loss Forecaster, lenders get robust models that work in the current conditions and take into account evolving consumer behaviors,” Verma said. To watch Experian’s webinar on portfolio loss forecasting, please click here and to learn more about the Ascend Portfolio Loss Forecaster, click the button below. Learn More

To combat the growing threat of synthetic identity fraud, Experian recently announced the launch of Sure ProfileTM, a revolutionary change to the credit profile that gives lenders peace of mind with Experian’s commitment to share in losses that result from an identity we’ve assured.   “Experian has always been a leader in combatting fraud, and with Sure Profile, we’re proud to deliver an industry-first fraud offering integrated into the credit profile that mitigates lender losses while protecting millions of consumers’ identities,” said Robert Boxberger, President of Decision Analytics, Experian North America.   Synthetic identity fraud is expected to drive $48 billion in annual online payment fraud losses by 2023. Between opportunistic fraudsters and a lack of a unified definition for synthetic identity theft it can be nearly impossible to detect—and therefore prevent—this type of fraud.   This breakthrough solution provides a composite history of a consumer’s identification, public record, and credit information and determines the risk of synthetic fraud associated with that consumer. It’s not just a fraud tool, it’s a comprehensive credit profile that utilizes premium data so lenders can make positive credit decisions.   Sure Profile leverages the capabilities of the Experian Ascend Identity PlatformTM and uses Experian’s industry-leading data assets and data quality to drive advanced analytics that set a higher level of protection for lenders. It’s powered by newly-developed machine learning and AI models. And it offers a streamlined approach to define and detect synthetic identities early in the originations process.   Most importantly, Sure Profile differentiates between real people and potentially risky applicants so lenders can increase application approvals with greater assurance and less risk.   “Experian can confidently define and help detect synthetic fraud. That's why we can help stop it,” said Craig Boundy, CEO of Experian North America. “Experian stands behind our data with assurance given to our clients. It’s better for lenders and it’s better for consumers.”   Sure Profile is a complement to our robust set of identity protection and fraud management capabilities, which are designed to address fraud and identity challenges including account openings, account takeovers, e-commerce fraud and more. This first-of-its kind profile is the future of underwriting and portfolio protection and it’s here now. Read press release Learn More About Sure Profile

While an overdue economic downturn has been long discussed, arguably no one could have foreseen the economic disruption from COVID-19 to the extent that’s been witnessed thus far. But now that we’re here, is there a line of sight to financial institutions’ next move? With the current situation marked by a history-making rise in unemployment, massive amounts of uncertainty within the market as well as for consumers and small businesses and consumer spending changes, loss forecasting is more important now than ever before. After the longest period of economic growth in history, financial institutions are caught off guard. While large banks are more prepared as they have stress testing capabilities in place and are estimating the potential large impact on their loss allowances, the since-delayed CECL requirements emphasized forecasting for the masses, and yet many are still under-equipped. Loss forecasting has evolved from a need for a small few to now a necessary strategy for all. While some financial institutions will look to loss forecasting to potentially reduce the severity of impact for the path ahead during these times (or even how they might come out stronger than their competition), for many, loss forecasting is the key to survival. Bare necessities. Understanding the possible outcomes of the pandemic’s impact is necessary to make critical business decisions. Lenders are likely receiving numerous questions about their portfolios and possible outcomes. These questions include, but are not limited to: What could the range of outcomes to my portfolio based on expert forecasts of macroeconomic conditions? How will I make lending decisions in the short term? Do my models need to change? How bad could charge offs be for my portfolio? If I have reduced marketing and application flows, at what point do I need to begin opening new accounts or consider portfolio acquisitions? How can lenders get answers? Loss forecasting. As Mohammed Chaudhri, Experian Chief Economist, said, “Loss forecasting is more pivotal than ever…existing models are not going to be up to the task of accurately predicting losses.” Whatever questions you’re receiving, you need certain necessary pieces of information to navigate this new era of loss forecasting. Those pieces are frequently updated client and industry data; ongoing access to expert macroeconomic forecasts; and sophisticated and evolved forecasting models. Client and Industry Data Loan-level data, bankruptcy scores and customer-level attributes are key insights to fueling loss forecasting models. By combining several data sets and scores (and a comprehensive history of both) your organization can see greater benefits. Macroeconomic Forecasts As has been mentioned numerous times, the economic impact resulting from COVID-19 is not at all like the Great Recession. As such, leveraging macroeconomic forecasts, and specifically COVID-19 forecasts, is critical to analyzing the potential impacts to your organization. Sophisticated Models Whether building models on your own or leveraging an expert, the key ingredients include the innerworkings of the model, leveraging historical data and making sure that both the models and the data are updated regularly to ensure you have the most accurate, thorough forecasts available. Also, leveraging machine learning tools is imperative for model specification and evaluation. Fortunately, while model building and loss forecasting used to be synonymous with countless resources and dollar signs, innovation and digital transformation have made these strategies within reach for financial institutions of all sizes. Incorporating the right data (and ensuring that data is regularly updated), with the right tools and macroeconomic scenarios (including COVID-19, upside, baseline, adverse and severely adverse scenarios) enables you to get a line of sight into the actions you need to take now. Empowered with insights to compare and benchmark results, discover the cause of changes in results, explore result scenarios in advance, and access recommended optimizations, loss forecasting enables you to focus on the critical decisions your business depends on. Experian helps you with loss forecasting for now and the future. For more information, including an on-demand webinar Experian presented with Oliver Wyman as well as the opportunity to engage Experian experts into your loss forecasting strategy, please click the button below. Learn More

This is the third in a series of blog posts highlighting optimization, artificial intelligence, predictive analytics, and decisioning for lending operations in times of extreme uncertainty. The first post dealt with optimization under uncertainty and the second with predicting consumer payment behavior. In this post I will discuss how well credit scores will work for consumer lenders during and after the COVID-19 crisis and offer some recommendations for what lenders can be doing to measure and manage that model risk in a time like this. Perhaps no analytics innovation has created opportunity for more individuals than the credit score has. The first commercially available credit score was developed by MDS (now part of Experian) in 1987. Soon afterwards FICO® popularized the use of scores that evaluate the risk that a consumer would default on a loan. Prior to that, lending decisions were made by loan officers largely on the basis on their personal familiarity with credit applicants. Using data and analytics to assess risk not only created economic opportunity for millions of borrowers, but it also greatly improved the financial soundness of lending institutions worldwide. Predictive models such as credit scores have become the most critical tools for consumer lending businesses. They determine, among other things, who gets a loan and at what price and how an account such as a credit line is managed through its life cycle. Predictive models are in many cases critical for calculating loan and loss reserves, for stress testing, and for complying with accounting standards. Nearly all lenders rely on generic scores such as the FICO® score and VantageScore® credit score. Most larger companies also have a portfolio of custom scorecards that better predict particular aspects of payment behavior for the customers of interest. So how well are these scorecards likely to perform during and after the current pandemic? The models need to predict consumer credit risk even as: Nearly all consumers change their behaviors in response to the health crisis, Millions of people—in America and internationally—find their income suddenly reduced, and Consumers receive large numbers of accommodations from creditors, who have in turn temporarily changed some of their credit reporting practices in response to guidelines in the federal CARES Act. In an earlier post, I pointed out that there is good reason to believe that credit scores will tend to continue to rank order consumers from most likely to least likely to repay their debts even as we move from the longest economic expansion in history to a period of unforeseen and unexpected challenges. But the interpretation of the score (for example, the log odds or the bad rate) may need to be adjusted. Furthermore, that assumes that the model was working well on a lender’s population before this crisis started. If it has been a long time since a scorecard was validated, that assumption needs to be questioned. Because experts are considering several different scenarios regarding both the immediate and long-term economic impacts of COVID-19, it’s important to have a plan for ongoing monitoring as long as necessary. Some lenders have strong Model Risk Management (MRM) teams complying with requirements from the Federal Reserve, Federal Deposit Insurance Corporation (FDIC), the Office of the Comptroller of the Currency (OCC). Those resources are now stretched thin. Other institutions, with fewer resources for MRM, are now discovering gaps in their model inventories as they implement operational changes. In either case, now’s the time to reassess how well scorecards are working. Good model validation practices are especially critical now if lenders are to continue to make the sound data-driven decisions that promote fairness for consumers and financial soundness for the institution. If you’re a credit risk manager responsible for the generic or custom models driving your lending, servicing, or capital allocation policies, there are several things you can do--starting now--to be sure that your organization can continue to make fair and sound lending decisions throughout this volatile period: Assess your model inventory. Do you have good documentation showing when each of the models in your organization was built? When was it last validated? Assign a level of criticality to each model in use. Starting with your most critical models, perform a baseline validation to determine how the model was performing prior to the global health crisis. It may be prudent to conduct not only your routine validation (verifying that the model was continuing to perform at the beginning of the period) but also a baseline validation with a shortened performance window (such as 6-12 months). That baseline validation will be useful if the downturn becomes a protracted one—in which case your scorecard models should be validated more frequently than usual. A shorter outcome window will allow a timelier assessment of the relationship between the score and the bad rate—which will help you update your lending and servicing policies to prevent losses. Determine if any of your scorecards had deteriorated even before the global pandemic. Consider recalibrating or rebuilding those scorecards. (Use metrics such as the Population Stability Index, the K-S statistic and the Gini Coefficient to help with that decision.) Many lenders chose not to prioritize rebuilding their behavioral scorecards for account management or collections during the longest period of economic growth in memory. Those models may soon be among the most critical models in your organization as you work to maintain the trust of your accountholders while also maintaining your institution’s financial soundness. Once the CARES accommodation period has expired, it will be important to revalidate your models more frequently than in the past—for as long as it takes until consumer behavior normalizes and the economy finds its footing. When you find it appropriate to rebuild a scorecard model, consider whether now is the time to implement ethical and explainable AI. Some of our clients are finding that Machine Learned models are more predictive than traditional scorecards. Early Experian research using data from the last recession indicates this will continue to be true for the foreseeable future. Furthermore, Experian has invested in Research and Development to help these clients deliver FCRA-compliant Adverse Action reasons to their consumers and to make the models explainable and transparent for model risk governance and compliance purposes. The sudden economic volatility that has resulted from this global health crisis has been a shock to all organizations. It is important for lenders to take the pulse of their predictive models now and throughout the downturn. They are especially critical tools for making sound data-driven business decisions until the economy is less volatile. Experian is committed to helping your organization during times of uncertainty. For more resources, visit our Look Ahead 2020 Hub. Learn more

Today’s lending market has seen a significant increase in alternative business lending, with companies utilizing new data assets and technology. As the lending landscape becomes increasingly competitive, consumers have more choices than ever when it comes to lending products. To drive profitable growth, lenders must find new ways to help applicants gain access to the loans they need. How Spring EQ is leveraging Experian BoostTM Home equity lender Spring EQ turned to Experian’s first-of-its-kind financial tool that empowers consumers to add positive payments directly into their credit file to assist applicants with attaining the best loan opportunities and rates. By using Experian BoostTM, which captures the value of consumer’s utility and telecom trade lines, in their current lending process, Spring EQ can help applicants near approval or risk thresholds move to higher risk tiers and qualify for better loan terms and conditions. Driving growth with consumer-permissioned data Over 40 million consumers in the U.S. either have no credit file or have insufficient information in their files to generate a traditional credit score. Consumer-permissioned data empowers these individuals to leverage their online financial data and payment histories to gain better access to loans and other financial services while providing lenders with a more comprehensive view of their creditworthiness. According to Experian research, 70% of consumers see the benefits of sharing additional financial information and contributing positive payment history to their credit file if it increases their odds of approval and helps them access more favorable credit terms. Read our case study for more insight on using Experian Boost to: Make better lending decisions Offer or underwrite credit to more people Promote the right credit products Increase conversion and utilization rates Read case study Learn more about Experian Boost

The coronavirus (COVID-19) outbreak is causing widespread concern and economic hardship for consumers and businesses across the globe – including financial institutions, who have had to refine their lending and downturn response strategies while keeping up with compliance regulations and market changes. As part of our recently launched Q&A perspective series, Shannon Lois, Experian’s Head of DA Analytics and Consulting and Bryan Collins, Senior Product Manager, tackled some of the tough questions for lenders. Here’s what they had to say: Q: What trends and triggers should lenders be prepared to react to? BC: Lenders are still trying to figure out how to assess risk between the broader, longer-term impacts of the pandemic and the near-term Coronavirus Aid, Relief, and Economic Security (CARES) Act that extends relief funds and deferment to consumers and small businesses. Traditional lending processes are not possible, lenders will have to adjust underwriting strategies and workflows as they deploy hardship programs while complying with the Act. From a utilization perspective, lenders need to look for near-term trends on payments, balances and skipped payments. From an extension standpoint, they should review limits extended or reduced by other lenders. Critical trends to look for would be missed or late auto payments, non-traditional credit shopping and rental payment delinquencies. Q: What should lenders be doing to plan for an uptick in delinquencies? SL: First, lenders should make sure they have a complete picture of how credit risk and losses are evolving, as well as any changes to their consumers’ affordability status. This will allow a pointed refinement of their customer management strategies (I.e. payment holidays, changing customer to cheaper product, offering additional services, re-pricing, term amendment and forbearance management.) Second, given the increased stress on collection processes and regulations guidelines, they should ensure proper and prepared staffing to handle increased call volumes and that agency outsourcing and automation is enabled. Additionally, lenders should migrate to self-service and interactive communication channels whenever possible while adopting new segmentation schemas/scores/attributes based on fresh data triggers to queue lower risk accounts entering collections. Q: How can lenders best help their customers? SL: Lenders should understand customers’ profiles with vulnerability and affordability metrics allowing changes in both treatment and payment. Payment Holidays are common in credit card management, consider offering payment freezes on different types of credit like mortgage and secured loans, as well as short term workout programs with lower interest rates and fee suppression. Additionally, lenders should offer self-service and FAQ portals with information about programs that can help customers in times of need. BC: Lenders can help by complying with aspects of the CARES Act guidance; they must understand how to deploy payment relief and hardship programs effectively and efficiently. Data integrity and accuracy of loan reporting will be critical. Financial institutions should adjust their collection and risk strategies and processes. Additionally, lenders must determine a way to address the unbanked population with relief checks. We understand how challenging it is to navigate the changing economic tides and will continue to offer support to both businesses and consumers alike. Our advanced data and analytics can help you refine your lending processes and better understand regulatory changes. Learn more About Our Experts: Shannon Lois, Head of DA Analytics and Consulting, Experian Data Analytics, North America Shannon and her team of analysts, scientists, credit, fraud and marketing risk management experts provide results-driven consulting services and state-of-the-art advanced analytics, science and data products to clients in a wide range of businesses, including banking, auto, credit, utility, marketing and finance. Shannon has been a presenter at many credit scoring and risk management conferences and is currently leading the Experian Decision Analytics advisory board. Bryan Collins, Senior Product Manager, Experian Consumer Information Services, North America Bryan is a member of Experian's CIS product management team, focusing on the Acquisitions suite and our evolving Ascend Identity Services Platform. With more than 20 years of experience in the financial services and credit industries, Bryan has established strong partnerships and a thorough understanding of client needs. He was instrumental in the launch of CIS's segmentation suite and led product management for lender and credit-related initiatives in Auto. Prior to joining Experian, Bryan held marketing and consumer experience roles in consumer finance, business lending and card services.

With new legislation, including the Coronavirus Aid, Relief, and Economic Security (CARES) Act impacting how data furnishers will report accounts, and government relief programs offering payment flexibility, data reporting under the coronavirus (COVID-19) outbreak can be complicated. Especially when it comes to small businesses, many of which are facing sharp declines in consumer demand and an increased need for capital. As part of our recently launched Q&A perspective series, Greg Carmean, Experian’s Director of Product Management and Matt Shubert, Director of Data Science and Modelling, provided insight on how data furnishers can help support small businesses amidst the pandemic while complying with recent regulations. Check out what they had to say: Q: How can data reporters best respond to the COVID-19 global pandemic? GC: Data reporters should make every effort to continue reporting their trade experiences, as losing visibility into account performance could lead to unintended consequences. For small businesses that have been negatively affected by the pandemic, we advise that when providing forbearance, deferrals be reported as “current”, meaning they should not adversely impact the credit scores of those small business accounts. We also recommend that our data reporters stay in close contact with their legal counsel to ensure they follow CARES Act guidelines. Q: How can financial institutions help small businesses during this time? GC: The most critical thing financial institutions can do is ensure that small businesses continue to have access to the capital they need. Financial institutions can help small businesses through deferral of payments on existing loans for businesses that have been most heavily impacted by the COVID-19 crisis. Small Business Administration (SBA) lenders can also help small businesses take advantage of government relief programs, like the Payment Protection Program (PPP), available through the CARES Act that provides forgiveness on up to 75% of payroll expenses and 25% of other qualifying expenses. Q: How do financial institutions maintain data accuracy while also protecting consumers and small businesses who may be undergoing financial stress at this time? GC: Following bureau recommendations regarding data reporting will be critical to ensure that businesses are being treated fairly and that the tools lenders depend on continue to provide value. The COVID-19 crisis also provides a great opportunity for lenders to educate their small business customers on their business credit. Experian has made free business credit reports available to every business across the country to help small business owners ensure the information lenders are using in their credit decisioning is up-to-date and accurate. Q: What is the smartest next play for financial institutions? GC: Experian has several resources that lenders can leverage, including Experian’s COVID-19 Business Risk Index which identifies the industries and geographies that have been most impacted by the COVID crisis. We also have scores and alerts that can help financial institutions gain greater insights into how the pandemic may impact their portfolios, especially for accounts with the greatest immediate exposure and need. MS: To help small businesses weather the storm, financial institutions should make it simple and efficient for them to access the loans and credit they need to survive. With cash flow to help bridge the gap or resume normal operations, small businesses can be more effective in their recovery processes and more easily comply with new legislation. Finances offer the support needed to augment currently reduced cash flows and provide the stability needed to be successful when a return to a more normal business environment occurs. At Experian, we’re closely monitoring the updates around the coronavirus outbreak and its widespread impact on both consumers and businesses. We will continue to share industry-leading insights to help data furnishers navigate and successfully respond to the current environment. Learn more About Our Experts Greg Carmean, Director of Product Management, Experian Business Information Services, North America Greg has over 20 years of experience in the information industry specializing in commercial risk management services. In his current role, he is responsible for managing multiple product initiatives including Experian’s Small Business Financial Exchange (SBFE), domestic and international commercial reports and Corporate Linkage. Recently, he managed the development and launch of Experian’s Global Data Network product line, a commercial data environment that provides a single source of up to date international credit and firmographic information from Experian commercial bureaus and Tier 1 partners across the globe. Matt Shubert, Director of Data Science and Modelling, Experian Data Analytics, North America Matt leads Experian’s Commercial Data Sciences Team which consists of a combination of data scientists, data engineers and statistical model developers. The Commercial Data Science Team is responsible for the development of attributes and models in support of Experian’s BIS business unit. Matt’s 15+ years of experience leading data science and model development efforts within some of the largest global financial institutions gives our clients access to a wealth of knowledge to discover the hidden ROI within their own data.  

In the face of severe financial stress, such as that brought about by an economic downturn, lenders seeking to reduce their credit risk exposure often resort to tactics executed at the portfolio level, such as raising credit score cut-offs for new loans or reducing credit limits on existing accounts. What if lenders could tune their portfolio throughout economic cycles so they don’t have to rely on abrupt measures when faced with current or future economic disruptions? Now they can. The impact of economic downturns on financial institutions Historically, economic hardships have directly impacted loan performance due to differences in demand, supply or a combination of both. For example, let’s explore the Great Recession of 2008, which challenged financial institutions with credit losses, declines in the value of investments and reductions in new business revenues. Over the short term, the financial crisis of 2008 affected the lending market by causing financial institutions to lose money on mortgage defaults and credit to consumers and businesses to dry up. For the much longer term, loan growth at commercial banks decreased substantially and remained negative for almost four years after the financial crisis. Additionally, lending from banks to small businesses decreased by 18 percent between 2008-2011. And – it was no walk in the park for consumers. Already faced with a rise in unemployment and a decline in stock values, they suddenly found it harder to qualify for an extension of credit, as lenders tightened their standards for both businesses and consumers. Are you prepared to navigate and successfully respond to the current environment? Those who prove adaptable to harsh economic conditions will be the ones most poised to lead when the economy picks up again. Introducing the FICO® Resilience Index The FICO® Resilience Index provides an additional way to evaluate the quality of portfolios at any point in an economic cycle. This allows financial institutions to discover and manage potential latent risk within groups of consumers bearing similar FICO® Scores, without cutting off access to credit for resilient consumers. By incorporating the FICO® Resilience Index into your lending strategies, you can gain deeper insight into consumer sensitivity for more precise credit decisioning. What are the benefits? The FICO® Resilience Index is designed to assess consumers with respect to their resilience or sensitivity to an economic downturn and provides insight into which consumers are more likely to default during periods of economic stress. It can be used by lenders as another input in credit decisions and account strategies across the credit lifecycle and can be delivered with a credit file, along with the FICO® Score. No matter what factors lead to an economic correction, downturns can result in unexpected stressors, affecting consumers’ ability or willingness to repay. The FICO® Resilience Index can easily be added to your current FICO® Score processes to become a key part of your resilience-building strategies. Learn more

Article written by Alex Lintner, Experian's Group President of Consumer Information Services and Sandy Anderson, Experian's Senior Vice President of Client and Sales Operations Many consumers are facing financial stress due to unemployment and other hardships related to the COVID-19 pandemic. Not surprisingly, data scientists at Experian are looking into how consumers’ credit scores may be impacted during the COVID-19 national emergency period as financial institutions and credit bureaus follow guidance from financial regulators and law established in Section 4021 of the Coronavirus Aid, Relief, and Economic Security Act (CARES Act). In a nutshell, Experian finds that if consumers contact their lenders and are granted an accommodation, such as a payment holiday or forbearance, and lenders report the accommodation accordingly, consumer scores will not be materially affected negatively. It’s not just Experian’s findings, but also those of the major credit scoring companies, FICO® and VantageScore®. FICO has reported that if a lender provides an accommodation and payments are reported on time consistent with the CARES Act, consumers will not be negatively impacted by late payments related to COVID-19. VantageScore® has also addressed this issue and stated that its models are designed to mitigate the impact of missed payments from COVID-19. At the same time, if as predicted, lenders tighten underwriting standards following 11 consecutive years of economic growth, access to credit for some consumers may be curtailed notwithstanding their score because their ability to repay the loan may be diminished. Regulatory guidance and law provide a robust response Recently, the Federal Reserve, along with the federal and state banking regulators, issued a statement encouraging mortgage servicers to work with struggling homeowners affected by the COVID-19 national emergency by allowing borrowers to defer mortgage payments up to 180-days or longer. The Federal Deposit Insurance Corporation stated that financial institutions should “take prudent steps to assist customers and communities affected by COVID-19.” The Office of the Comptroller of the Currency, which regulates nationally chartered banks, encouraged banks to offer consumers payment accommodations to avoid delinquencies and negative credit bureau reporting. This regulatory guidance was backed by Congress in passing the CARES Act, which requires any payment accommodations to be reported to a credit bureau as “current.” The Consumer Financial Protection Bureau, which has oversight of all financial service providers, reinforced the regulatory obligation in the CARES Act. In a statement, the Bureau said “the continuation of reporting such accurate payment information produces substantial benefits for consumers, users of consumer reports and the economy as a whole.” Moreover, the consumer reporting industry has a history of successful coordination during emergency circumstances, like COVID-19, and we’ve provided the support necessary for lenders to report accurately and consistent with regulatory guidance. For example, when a consumer faces hardship, a lender can add a code that indicates a customer or borrower has been “affected by natural or declared disaster.” If a lender uses this or a similar code, a notification about the disaster or other event will appear in the credit report with the trade line for the customer’s account and will remain on the trade line until the lender removes it. As a result, the presence of the code will not negatively impact the consumer credit score. However, other factors may impact a consumer’s score, such as an increase in a consumer’s utilization of their credit lines, which is a likely scenario during a period of financial stress. Suppression or Deletion of late payments will hurt, not help, credit scores In response to the nationwide impact of COVID-19, some lawmakers have suggested that lenders should not report missed payments or that credit bureaus should delete them. The presumption is that these actions would hold consumers harmless during the crisis caused by this pandemic. However, these good intentions end up having a detrimental impact on the whole credit ecosystem as consumer credit information is no longer accurately reflecting consumers’ specific situation. This makes it difficult for lenders to assess risk and for consumers to obtain appropriately priced credit. Ultimately, the best way to help is a consumer-specific solution, meaning one in which a lender reaches an accommodation with each affected individual, and accurately reflects that person’s unique situation when reporting to credit bureaus. When a consumer misses a payment, the information doesn’t end up on a credit report immediately. Most payments are monthly, so a consumer’s payment history with a financial institution is updated on a similar timeline. If, for example, a lender was required to suppress reporting for three months during the COVID-19 national emergency, the result would be no data flowing onto a credit report for three months. A credit report would therefore show monthly payments and then three months of no updates. The same would be true if a credit reporting agency were required to suppress or delete payment information. The lack of data, due to suppression or deletion, means that lenders would be blinded when making credit decisions, for example to increase a credit limit to an existing customer or to grant a new line of credit to a prospective customer. When faced with a blind spot, and unable to assess the real risk of a consumer’s credit history, the prudential tendency would be to raise the cost of credit, or to decrease the availability of credit, to cover the risk that cannot be measured. This could effectively end granting of credit to new customers, further stifling economic recovery and consumer financial health at a time when it’s needed most. Beyond the direct impact on consumers, suppression or deletion of credit information could directly affect the safety and soundness of the nation’s consumer and small business lending system. With missing data, lenders and their regulators would be flying blind as to the accurate information about a consumer’s risk and could result in unknowingly holding loan portfolios with heightened risk for loss. Too many unexpected losses threaten the balance of the financial system and could further seize credit markets. Experian is committed to helping consumers manage their credit and working with lenders on how best to report consumer-specific solutions. To learn more about what consumers can do to manage credit during the COVID-19 national emergency, we’ve provided resources on our website. For individuals looking to explore options their lenders may offer, we’ve included links to many of the companies and update them continuously. With good public policy and consumer-specific solutions, consumers can continue to build credit and help our economy grow.