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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

The economic impact of the COVID-19 health crisis is ever-evolving and requires great flexibility and planning from lenders. Shannon Lois, Experian’s Senior Vice President, Analytics, Consulting and Operations, discusses what lenders can expect and next steps to take. Q: Though COVID-19 is catalyzing a sharp economic slowdown, many experts expect it to be temporary and liken it more to a global natural disaster than the prior financial crisis. What are your reactions? SL: There is still debate as to whether we will have a U-shaped or a V-shaped recession and its probable severity and longevity. Regardless, we are in a recession caused by a health pandemic with uncertainty of what it will mean for our global economy and without a clear view as to when it will end. The sooner we can contain the virus the more it will help to curtail the size of the recession. The unemployment rates and the consumer lack of confidence in the future will continue to contract spending which in turn will continue to propagate the recession. Our ability to limit COVID-19 over the coming months will have a direct impact in the economy, although the effects will probably linger on for six or more months. Q: From an economic perspective, what are the current trends we’re seeing? SL: Unemployment has skyrocketed and every business sector has been impacted although with   different degrees of severity. In particular, tourism/hospitality, airlines, automotive, consumer products and retail have suffered. Consumers’ financial status varies and will continue to fluctuate, and credit conditions tighten while welfare payments increase. The government programs that have started will help, but they’re not enough to counter a prolonged recession. As some states seek to reopen and others extend their shelter in place orders, we will continue to see economic changes, with different sectors bouncing back or dipping further depending on their geographic location. Q: How does the economic slowdown compare to what we may have expected previously? SL: This recession is different than anything we have encountered previously not only because of the health concerns and implication of our population but because of the uncertainty of it all. As an example, social distancing has significantly and immediately impacted consumer demand but overall it is their low confidence in the future that will cause a continuous drop in discretionary and non-discretionary spending. Not only do we have challenges on the demand side, we also are seeing the same on the supply side with no automotive manufacturing occurring in the USA, and international oil flooding the market causing negative impact on domestic oil and the broad energy market. Q: How do the unemployment and liquidity challenges come into play? SL: The unemployment rate has already jumped to a record high. Most consumers are facing liquidity and affordability challenges and businesses do not have enough cash reserves to sustain them. Consumer activity has shifted drastically across all channels while lenders are exercising more caution. If this is a V-shaped recession (and hopefully it will be), then most activity is bound to spring back quickly in Q3. With companies safeguarding some jobs and the help of governments’ supplemental programs, businesses will restore supply and consumer demand will get a kick start. Q: What is the smartest next play for financial institutions? SL: The path forward requires several steps. First, understand your customers, existing and new. Refine your policies with the right information around your customers’ financial situations and extend programs (forbearance and loan payment forgiveness) as needed under the right guidelines. It’s also important to use refreshed data to lend to consumers and businesses who need it now more than ever, with the proper policies and fraud checks in place. Finally, increase your agility to operate effectively and dynamically with automation, interactive communication and self-serving digital tools. Experian is committed to helping lenders throughout these uncertain times. For more resources, visit our Look Ahead 2020 Resource Hub. Learn more   About Our Expert Shannon Lois, Senior Vice President, Analytics, Consulting and Operations, Decision Analytics 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. Prior to her current role, she founded the Advisory Services practice at Experian, driving to actionable and proven solutions for our clients’ most pressing business problems.    

There is no doubt that there will be many headlines published about the latest Bureau of Labor Statistics (BLS) jobs report. The official unemployment rate spiked to 14.7%, the highest level since the Great Depression, and employers shed an unprecedented 20.5 million jobs. However, given the scale and pace that businesses around the country are adjusting their workforces, these headline numbers – especially the official unemployment rate – fall short in capturing the nuances and internal dynamics of the crisis. To get a better picture of labor market health in the coming months, there are three other components reported in BLS’s employment release that require close attention: the underemployment rate, the labor force participation rate, and the employment-population ratio. Tracking underemployment The BLS reports six unemployment figures in its monthly employment release, U1 – U6. The most cited is the “official” unemployment rate, which is U3. However, in the current crisis, the more salient measure of unemployment is U6, which is often known as the “underemployment” rate. This is because the underemployment (U6) rate takes the unemployed and adds on part-time workers who want a full-time job (BLS calls this segment “part time for economic reasons”), plus marginally attached and discouraged workers (those who don’t think they can find work). Viewing the employment landscape through this lens provides greater insight into the pain points within the labor market. In April, the underemployment rose from 8.7% to 22.8% - the largest jump on record. A large contributor to the rise was a doubling of the number of part-time workers that wanted a full-time job. Mirroring what happened in previous downturns, the rise in this segment was caused by employers downshifting workers into part-time roles. The official unemployment rate will miss this insight as it classifies everyone who is working as “employed”, regardless if they worked one hour or 100 hours. Trends in the underemployment rate will be especially important to watch as the recovery gets underway. If employers are doubtful of a strong rebound, they may keep employees on as part time and forgo filling any full-time positions. Who’s in and who’s out of the labor force The labor force participation rate is the percentage of the working-age population (aged 16+) that is employed or searching for a job. A decline in the labor force participation rate means that people are leaving the workforce and are no longer looking for employment. April’s employment report showed labor force participation declining from 62.7% to 60.2%. Teenage participation was especially hard hit, dropping from 35.5% to 30.8% - the lowest level since the government started collecting the data in 1948. During the recovery phase, tracking what happens with labor force participation will provide insight into how potential workers perceive their chances of landing a job and if it is safe to return. A healthy (or improving) labor market will bring people off the sidelines in search of work, while a weak labor market will do the opposite. Get a clearer view with the employment-population ratio In the current environment where people are bouncing rapidly between employed, unemployed, underemployed, and out of the labor force, tracking the employment-population ratio provides a more stable baseline to view the economic environment. The latest data shows that the employment-population ratio dropped to the lowest level on record of 51.3% in April. This means that only half of people who are of working age in the U.S. are currently employed in some form. Unlike the unemployment rate, which is calculated by dividing the number of unemployed workers by the labor force and thus subject to more variation as people start and stop looking for work, the employment to population ratio is the percentage of the total working-age population that is currently employed. By having a more stable baseline, it is easier to locate trends and see through the market gyrations. And finally, why it matters The labor market is the backbone of the economy and is the engine that powers the US consumer. But the ongoing crisis and rapid reallocation of the workforce has made it difficult to get a clear picture on what is happening at the ground level. By going beyond the headlines, businesses and financial institutions can glean nuanced insights that provide a better view of where the opportunities lie and how the recovery is likely to unfold. Learn more

This week, Experian released a new version of our CrossCore® digital identity and fraud risk platform, adding new tools and functionality to help businesses quickly respond to today’s emerging fraud threats. The ability to confidently recognize your customers and safeguard their digital transactions is becoming an increasing challenge for businesses. Fraud threats are already rising across the globe as fraudsters take advantage of the global health crisis and rapidly shifting economic conditions. CrossCore combines risk-based authentication, identity proofing and fraud detection into a single cloud platform, which means businesses can more quickly respond to an ever-changing environment. And with flexible decisioning orchestration and advanced analytics, businesses can make real-time risk decisions throughout the customer lifecycle. “Now more than ever, businesses need to lean on capabilities and technology that will allow them to rapidly respond in these challenging times, increase identity confidence in every transaction, and provide a safe and convenient experience for customers,” said E.K. Koh, Experian’s Senior Vice President of Global Identity & Fraud Solutions in a recent press release. “This new CrossCore release enables businesses to easily leverage best-in-class, pre-integrated identity and fraud services through simple self-service.” This new version of CrossCore features a cloud architecture, modern user interface, progressive risk assessments, faster response times, self-service workflow configuration, and a transactional volume reporting dashboard. These enhancements give you a simpler way to manage how backing applications are utilized, allow you to analyze key performance indicators in near real-time, and empower you to catch more fraud faster - without impacting the customer experience. “Recent Aite Group research shows that many banks have seen digital channel usage increase 250% in the wake of the pandemic, so ensuring a seamless and safe customer experience is more important than ever,” said Julie Conroy, Research Director at Aite Group. “Platforms such as CrossCore that can enable businesses to nimbly respond to changing patterns of customer behavior as well as rapidly evolving attack tactics are more important than ever, as financial services firms work to balance fraud mitigation with the customer experience.” CrossCore is the first identity and fraud platform that enables you to connect, access, and orchestrate decisions across multiple solutions. With the newest version, Experian enhances your ability to consolidate numerous fraud risk signals into a single, holistic assessment to improve operational processes, stay ahead of fraudsters, and protect your customers. Read Press Release Learn More About CrossCore

One of the most difficult parts of combating fraud is the ability to distinguish between the variety of fraud types. To properly manage your fraud efforts, you need to be able to differentiate between first party fraud and third party fraud so you can determine the best treatment. After all, if you’re treating first party fraud as though it’s third party fraud, the customer you’re contacting for verification will give whatever information they need to in order to continue their criminal actions. So how do you verify each type of fraud without adding additional overhead or increasing the friction experienced by your customers? Combating Fraud During an Economic Downturn Particularly in times of economic uncertainty, the ability to detect and identify individual fraud types allows you to work to prevent them in the future. Through proper identification, you can also apply the correct treatments to maximize the effectiveness of your fraud response teams, since the treatment for first and third party fraud is different. During the economic upswing, first party fraud was a secondary concern. Businesses were easing friction to help continue growth. Now, the same customers that businesses thought would drive growth are hurting and unable to help offset the losses caused by bad actors. Now is the time to revisit existing fraud prevention and mitigation strategies to ensure that fraud is properly identified, and the correct treatments are applied. Introducing Precise ID® Model Suite Experian’s Precise ID Model Suite combines identity analytics with advanced fraud risk models to: Protect the entire customer journey again fraud – across account opening, login, maintenance and transactions Distinguish first-party, third-party, and synthetic identity fraud to determine the best next action Enable agility during changing market conditions Maintain regulatory compliance (including: KYC, CIP, GLBA, FCRA, FFIEC, PATRIOT Act, FACTA, and more) Improve overall fraud management strategies and reduce losses Precise ID Model Suite allows you to detect and distinguish types of fraud with a single call – enabling your business to maximize efficiency and eliminate redundancy across your fraud prevention teams. By accurately recognizing risk, and in particular, recognizing that first party fraud is in fact a type of fraud distinct from credit risk, you’re able to protect your portfolio and your customers. Learn more

This is the next article in our series about how to handle the economic downturn – this time focusing on how to prevent fraud in the new economic environment. We tapped two new experts—Chris Ryan, Market Lead, Fraud and Identity and Tischa Agnessi, Go-to-Market Lead, Decisioning Software—to share their thoughts on how to keep fraud out of your portfolio while continuing to lend. Q: What new fraud trends do you expect during the economic downturn? CR: Perhaps unsurprisingly, we tend to see high volumes of fraud during economic downturn periods. First, we anticipate an uptick in third-party fraud, specifically account takeover or ATO. It’ll be driven by the need for first-time users to be forced online. In particular, the less tech-savvy crowd is vulnerable to phishing attacks, social engineering schemes, using out-of-date software, or landing on a spoofed page. Resources to investigate these types of fraud are already strained as more and more requests come through the top of the funnel to approve new accounts. In fact, according to Javelin Strategy & Research’s 2020 Identity Fraud Study, account takeover fraud and scams will increase at a time when consumers are feeling financial stress from the global health and economic crisis. It is too early to predict how much higher the fraud rates will go; however, criminals become more active during times of economic hardships. We also expect that first party fraud (including synthetic identity fraud) will trend upwards as a result of the deliberate abuse of credit extensions and additional financing options offered by financial services companies. Forced to rely on credit for everyday expenses, some legitimate borrowers may take out loans without any intention of repaying them – which will impact businesses’ bottom lines. Additionally, some individuals may opportunistically look to escape personal credit issues that arise during an economic downturn. The line between behaviors of stressed consumers and fraudsters will blur, making it more difficult to tell who is a criminal and who is an otherwise good consumer that is dealing with financial pressure. Businesses should anticipate an increase in synthetic identity fraud from opportunistic fraudsters looking to take advantage initial financing offers and the cushions offered to consumers as part of the stimulus package. These criminals will use the economic upset as a way to disguise the fact that they’re building up funds before busting out. Q: With payment stress on the rise for consumers, how can lenders manage credit risk and prevent fraud? TA: Businesses wrestle daily with problems created by the coronavirus pandemic and are proactively reaching out to consumers and other businesses with fresh ideas on initial credit relief, and federal credit aid. These efforts are just a start – now is the time to put your recession readiness plan and digital transformation strategies into place and find solutions that will help your organization and your customers beyond immediate needs. The faceless consumer is no longer a fraction of the volume of how organizations interact with their customers, it is now part of the new normal. Businesses need to seek out top-of-line fraud and identity solutions help protect themselves as they are forced to manage higher digital traffic volumes and address the tough questions around: How to identify and authenticate faceless consumers and their devices How to best prevent an overwhelming number of fraud tactics, including first party fraud, account takeover, synthetic identity, bust out, and more. As time passes and the economic crisis evolves, we will all adapt to yet another new normal. Organizations should be data-driven in their approach to this rapidly changing credit crisis and leverage modern technology to identify financially stressed consumers with early-warning indicators, predict future customer behavior, and respond quickly to change as they deliver the best treatment at the right time based on customer-specific activities. Whether it’s preparing portfolio risk assessment, reviewing debt management, collections, and recovery processes, or ramping up your fraud and identity verification services, Experian can help your organization prepare for another new normal. Experian is continuing to monitor 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 financial institutions differentiate legitimate consumers from fraudsters and protect their business and customers. Learn more About Our Experts [avatar user="ChrisRyan" /] Chris Ryan, Market Lead, Fraud and Identity Chris has over 20 years of experience in fraud prevention and uses this knowledge to identify the most critical fraud issues facing individuals and businesses in North America, and he guides Experian’s application of technology to mitigate fraud risk. [avatar user="tischa.agnessi" /] Tischa Agnessi, Go-to-Market Lead, Decisioning Software Tischa joined Experian in June of 2018 and is responsible for the go to market strategy for North America’s decisioning software solutions. Her responsibilities include delivering compelling propositions that are unique and aligned to markets, market problems, and buyer and user personas. She is also responsible for use cases that span the PowerCurve® software suite as well as application platforms, such as Decisioning as a ServiceSM and Experian®One.

  Many small businesses in the hardest-hit states missed out on the first round of federal relief through the recently created Paycheck Protection Program (PPP). The Coronavirus Aid, Relief, and Economic Security (CARES) Act established the PPP in order to disburse $349 billion in forgivable loans to small businesses hurt by the COVID-19 outbreak. However, the program’s funding limit and first-come, first-serve method for accepting loan applications put an immense strain on the financial institutions tasked with getting the money out the door. This resulted in many small businesses unable to get their applications submitted, approved, and funded before the program ran out of money after only two weeks. Where did the money go? The latest data from the Small Business Administration shows that the most populous states received the largest number of PPP loans. This is unsurprising, as states with higher populations tend to have a greater number of small businesses. One way to get a better picture of the impact of PPP loans on communities is to examine what percentage of a state’s small businesses received PPP loans (Figure 1). When viewed through this lens, the results are a quite striking - many of the coastal areas and larger markets missed out, while the rural, north-central states won out. Less than 4% of small businesses in California, Florida, and New York – three of the top five largest markets – were approved for PPP loans. While more than 12% of small businesses in North Dakota, Nebraska, and South Dakota received support.       What happened? There are several factors that could have played a part in the uneven distribution of PPP loans. One explanation may be that some financial institutions in highly populated urban areas did not have the capacity to process such a large volume of loan applications in such a short amount of time. There may also be an urban-rural divide to how relationship banking occurs. Rural communities and small businesses with close-knit ties to area financial institutions may have had easier access to getting their PPP applications submitted and approved. In line with this, Figure 2 shows the top five and bottom five states in terms of financial institutions (banks and credit unions) per 100,000 people. The states with the highest prevalence of financial institutions were also the top states for PPP small business loan share. While the states with the lowest prevalence of financial institutions were the states with the smallest share. Another factor may have been the extent that shelter-in-place rules were being enforced. North Dakota, Nebraska, and South Dakota – the three top states for loan share – are part of the handful of states that still do not have statewide lockdowns. California, on the other hand, was the first state in the country to issue shelter-in-place measures. Why it matters The first round of stimulus through the Paycheck Protection Program provided relief for many small businesses around the country. However, the first-come, first-serve method of distributing loans may have resulted in some small business communities having easier access to the program than others. Insights as to why these differences occurred and why small businesses in the larger markets received a lower share of PPP loans can inform future stimulus efforts and ensure that recovery among the states is as even and broad as possible.   Figure 1 Sources: Small Business Administration Paycheck Protection Program Report 4/16/2020, Census Bureau SUSB and NES Statistics. Author’s calculations. Figure 2 Sources: Experian data on financial institutions, Census Bureau population estimates. Author's calculations.

The response to the coronavirus (COVID-19) health crisis requires a brand-new mindset from businesses across the country. As part of our recently launched Q&A perspective series, Jim Bander, Market Lead of Analytics and Optimization and Kathleen Peters, Senior Vice President of Fraud and Identity, provided insight into how businesses can work to mitigate fraud and portfolio risk. Q: How can financial institutions mitigate fraud risk while monitoring portfolios? JB: The most important shift in portfolio monitoring is the view of the customer, because it’s very different during times of crisis than it is during expansionary periods. Financial institutions need to take a holistic view of their customers and use additional credit dimensions to understand consumers’ reactions to stress. While many businesses were preparing for a recession, the economic downturn caused by the coronavirus has already surpassed the stress-testing that most businesses performed. To help mitigate the increased risk, businesses need to understand how their stress testing was performed in the past and run new stress tests to understand how financially sound their institution is. KP: Most businesses—and particularly financial institutions—have suspended or relaxed many of their usual risk mitigation tools and strategies, in an effort to help support customers during this time of uncertainty. Many financial institutions are offering debt and late fee forgiveness, credit extensions, and more to help consumers bridge the financial gaps caused by the economic downturn. Unfortunately, the same actions that help consumers can hamstring fraud prevention efforts because they impact the usual risk indicators. To weather this storm, financial institutions need to pivot from standard risk mitigation strategies to more targeted fraud and identity strategies. Q: How can financial institutions’ exposure to risk be managed? JB: Financial institutions are trying to extend as much credit as is reasonably possible—per government guidelines—but when the first stage of this crisis passes, they need to be prepared to deal with the consequences. Specifically, which borrowers will actually repay their loans. Financial institutions should monitor consumer health and use proactive outreach to offer assistance while keeping a finger on the pulse of their customers’ financial health. For the foreseeable future, the focus will be on extending credit, not collecting on debt, but now is the time to start preparing for the economic aftermath. Consumer health monitoring is key, and it must include a strategy to differentiate credit abusers and other fraudsters from overall good consumers who are just financially stressed. KP: As financial institutions work to get all of their customers set up with online and mobile banking and account access, there’s an influx of new requests that all require consumer authentication, device identification, and sometimes even underwriting. All of this puts pressure on already strained resources which means increased fraud risk. To manage this risk, businesses need to balance customer experience—particularly minimizing friction—with vigilance against fraudsters and reputational risk. It will require a robust and flexible fraud strategy that utilizes automated tools as much as possible to free up personnel to follow up on the riskiest users and transactions.   Experian is 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 financial institutions manage their portfolios and protect against losses. Learn more About Our Experts: [avatar user="jim.bander" /] Jim Bander, Market Lead, Analytics and Optimization, Experian Decision Analytics, North America 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. [avatar user="kathleen.peters" /] Kathleen Peters, Vice President, Fraud and Identity, Experian Decision Analytics, North America Kathleen joined Experian in 2013 to lead business development and international sales for the recently acquired 41st Parameter business in San Jose, Calif. She went on to lead product management for Experian’s fraud and identity group within the global Decision Analytics organization, launching Experian’s CrossCore® platform in 2016, a groundbreaking and award-winning new offering for the fraud and identity market. The last two years, Kathleen has been named a “Top 100 Influencer in Identity” by One World Identity (OWI), an exclusive list that annually recognizes influencers and leaders from across the globe, showcasing a who’s who of people to know in the identity space.

As financial institutions and other organizations scramble to formulate crisis response plans, it’s important to consider the power of data and analytics. Jim Bander, PhD, Experian’s Analytics and Optimization Market Lead discusses the ways that data, analytics and models can help during a crisis. Check out what he had to say: What implications does the global pandemic have on financial institutions’ analytical needs?  JB: COVID-19 is a humanitarian crisis, one that parallels Hurricanes Sandy and Katrina and other natural disasters but which far exceeds their magnitude. It is difficult to predict the impact as huge parts of the global economy have shut down. Another dimension of this disaster is the financial impact: in the US alone, more than 17 million people applied for unemployment in the first 6 weeks of the COVID-19 crisis. That compares to 15 million people in 18 months during the Great Recession. Data and analytics are more important than ever as financial institutions formulate their responses to this crisis. Those institutions need to focus on three key things: safety, soundness, and compliance. Safety: Financial institutions are taking immediate action to mitigate safety risks for their employees and their customers. Soundness: Organizations need to mitigate credit and fraud risk and to evaluate capital and liquidity. Some executives may need a better understanding of how their bank’s stress scenarios were calculated in the past to understand how they must be updated for the future. Important analytic functions include performing portfolio monitoring and benchmarking—quantifying the effects not only of consumer distress, but also of low interest rates. Compliance: Understanding and meeting complex regulatory and compliance requirements is crucial at this time. Companies have to adapt to new credit reporting guidelines. CECL requirements have been relaxed but lenders should assess the effects of COVID, and not only during their annual stress tests. As more consumers seek credit, from an analytics perspective, what considerations should financial institutions make during this time?  JB: During this volatile time, analytics will help financial institutions: Identify financially stressed consumers with early warning indicators Predict future consumer behavior Respond quickly to changes Deliver the best treatments at the right time for individual customers given their specific situations and their specific behavior. Financial institutions should be reevaluating where their organizations have the most vulnerability and should be taking immediate action to mitigate these risks. Some important areas to keep an eye on include early warning indicators, changes in fraudulent behavior (with the increase in digital engagements), and changes in customer behavior. Banks are already offering payment flexibility, deferments, and credit reporting accommodations. If volatility continues or increases, they may need to offer debt forgiveness plans. These organizations should also be prepared to understand their own changing constraints—such as budget, staffing levels, and liquidity requirements— especially as consumers accelerate their move to digital channels. In the near future, lenders should be optimizing their operations, servicing treatments, and lending policies to meet a number of possibly conflicting objectives in the presence of changing constraints and somewhat unpredictable transaction volumes.   What is the smartest next play for financial institutions?  JB: I see our smartest clients doing four things: Adapting to the new normal Maintaining engagement with existing customers by refreshing data that companies have on-hand for these consumers, and obtain additional views of these customers for analytics and data-driven decisioning Reallocating operational resources and anticipating the need for increased capacity in various servicing departments in the future Improving their risk management practices   What is Experian doing to help clients improve their risk management? JB: During this time, banks and other financial institutions are searching for ways to predict consumer behavior, especially during a crisis that combines aspects of a natural disaster with characteristics of a global recession. It is more important than ever to use analytics and optimization. But some of the details of the methodology is different now than during a time of economic expansion. For example, while credit scores (like FICO® and VantageScore® credit scores) will continue to rank consumers in terms of their probability to pay, those scores must be interpreted differently. Furthermore, those scores should be combined with other views of the consumer—such as trends in consumer behavior and with expanded FCRA-compliant data (data that isn’t reported to traditional credit bureaus). One way we’re helping clients improve their credit risk management is to provide them with a list of 140 consumer credit data attributes in 10 categories. With this list, companies will be able to better manage portfolio risk, to better understand consumer behavior, and to select the next best action for each consumer. Four other things we’re doing: We’re quickly updating our loss forecasting and liquidity management offerings to account for new stress scenarios. We’re helping clients review their statistical models’ performance and their customer segmentation practices, and helping to update the models that need refreshing. Our consulting team—Experian Advisory Services—has been meeting with clients virtually--helping them update, execute their crisis and downturn responses, and whiteboard new or updated tactical plans. Last but not least, we’re helping lenders and consumers defend themselves against a variety of fraud and identity theft schemes. Experian is committed to helping your organization during these uncertain times. For more resources, visit our Look Ahead 2020 Hub. Learn more Jim Bander, PhD, Analytics and Optimization Market Lead, Decision Analytics, Experian North America Jim Bander, PhD 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. Jim has over 20 years of analytics, software, engineering and risk management experience across a variety of industries and disciplines. He has applied decision science to many industries including banking, transportation and the public sector. He is a consultant and frequent speaker on topics ranging from artificial intelligence and machine learning to debt management and recession readiness. Prior to joining Experian, he led the Decision Sciences team in the Risk Management department at Toyota Financial Services.

This is the second 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 word "unprecedented" gets thrown around pretty carelessly these days. When I hear that word, I think fondly of my high school history teacher.  Mr. Fuller had a sign on his wall quoting the philosopher-poet George Santayana: "Those who cannot remember the past are condemned to repeat it." Some of us thought it meant we had to memorize as many facts as possible so we wouldn't have to go to summer school. The COVID-19 crisis--with not only health consequences but also accompanying economic and financial impacts--certainly breaks with all precedents.  The bankers and other businesspeople I've been listening to are rightly worried that This Time is Different. While I'm sure there are history teachers who can name the last time a global disaster led to a widescale humanitarian crisis and an economic and financial downturn, I'm even more sure times have changed a lot since then. But there are plenty of recent precedents to guide business leaders and other policymakers through this crisis. Hurricanes Katrina and Sandy impacted large regions of the United States, with terrible human consequences followed by financial ones. Dozens of local disasters—floods, landslides, earthquakes—devastated smaller numbers of people in equally profound ways. The Great Recession, starting in 2008, put millions of Americans and others around the world out of work. Each of those disasters, like this one, broke with all precedents in various ways. Each of those events was in many ways a dress rehearsal, as bankers and other lenders learned to provide assistance to distressed businesses and consumers, while simultaneously planning for the inevitable changes to their balance sheets and income statements. Of course, the way we remember the past has changed. Just as most of us no longer memorize dates--we search for them on the web--businesspeople turn to their databases and use analytics to understand history. I've been following closely as the data engineers and data scientists here at Experian have worked on perhaps their most important problem ever. Using Experian's Ascend Analytical Sandbox--named last year as the Best Overall Analytics Platform, they combed through over eighteen years of anonymized historical data covering every credit report in the United States. They asked--using historical experience, wisdom, time-consuming analytics, a little artificial intelligence, and a lot of hard work--whether predicting credit performance during and after a crisis is possible. They even considered scenarios regarding what happens as creditors change the way they report consumer delinquencies to the credit bureaus. After weeks of sleepless nights, they wrote down their conclusions.  I've read their analysis carefully and I’m pleased to report that it says…Drumroll, please…Yes, but. Yes, it's possible to predict consumer behavior after a disaster. But not in precisely the same way those predictions are made during a period of economic growth. For a credit risk manager to review a lending portfolio and to predict its credit losses after a crisis requires looking at more data--and looking at it a little differently--than during other periods. Yes, after each disaster, credit scores like FICO® and VantageScore® credit scores continued to rank consumers from most likely to least likely to repay debts. But the interpretation of the score changes. Technically speaking, there is a substantial shift in the odds ratio that is particularly pronounced when a score is applied to subprime consumers. To predict borrower behavior more accurately, our scientists found that it helps to look at ten additional categories of data attributes and a few additional types of mathematical models. Yes, there are attributes on the credit report that help lenders identify consumer distress, willingness, and ability to pay. But, the data engineers identified that during times like these it is especially helpful to look beyond a single point in time; trends in a consumer's payment history help understand whether that customer is changing their typical behavior. Yes, the data reported to the credit bureaus is predictive, especially over time. But when expanded FCRA data is available beyond what is traditionally reported to a bureau, that data further improves predictions. All told, the data engineers found over 140 data attributes that can help lenders and others better manage their portfolio risk, understand consumer behavior, appreciate how the market is changing, and choose their next best action. The list of attributes might be indispensable to a credit data specialist whose institution needs to weather the coming storm. Because Experian knows how important it is to learn from historical precedents, we're sharing the list at no charge with qualified risk managers. To get the latest Experian data and insights or to request the Crisis Response Attributes recommendation, visit our Look Ahead 2020 page. Learn more

This is the first to a series of blog posts highlighting optimization, artificial intelligence, predictive analytics, and decisioning for lending operations in times of extreme uncertainty.   Like all businesses, lenders are facing tremendous change and uncertainty in the face of the COVID-19 crisis.  While focusing first on how to keep their employees and customers safe during the new normal, they are asking how to make data-driven decisions in this new environment.  It’s only natural that business people are skeptical about whether analytics will work in a situation like today's – in which the data deviate from all historical precedents.  Certainly, nobody predicted, for example, that the number of loans with forbearance requests would increase by over 1000% during each two-week period in March. Can anyone possibly make an optimized decision when things are changing so quickly and when so many things are unknown?   Prescriptive analytics – also known as mathematical optimization – is the practice of developing a business strategy to achieve a business objective subject to capacity and other constraints, often using a demand forecast. For example, banks use optimization software to develop marketing and debt management strategies to run their lending operations.  But what happens when the demand forecast might be wrong, when the constraints change quickly, and when decision-makers cannot agree on a single objective? The reality is that decisionmakers have to balance multiple competing objectives related to many different stakeholders. And, especially during the COVID-19 crisis and the period of change that will certainly follow, they have to do so in the face of uncertainty.   Let's discuss some of the methods that analysts use to control risk while optimizing lending practices during times like these. These techniques, collectively known as robust optimization and robust statistics, help lenders and other business people deal with the uncomfortable reality that we do not know what the future holds.     Consider a hypothetical bank or other lender servicing a portfolio of consumer loans and forecasting its loss performance in this environment. Management probably has several competing objectives: they want to improve service levels on their digital channel, they want to minimize credit and fraud losses, they're facing a reduced operating budget, and they're not certain how many employees they will have and which vendors will be able to provide adequate service levels. Furthermore, they anticipate new and unpredicted changes, and they need to be able to update their strategies quickly.   The mathematics can be quite technical, but Experian’s Marketswitch Optimization is user-friendly software to help businesspeople--not engineers--design and deploy optimal strategies for practices such as Account Management and Loan Originations while facing such a dynamic and uncertain environment. The bank's business analysts (not computer specialists or mathematicians) will use techniques such as these:   With Sensitivity Analysis, the analysts will explore the performance of their optimized Account Management, Collections, and Loan Originations strategies while considering possible changes in input variables.   Optimization Scenarios with Uncertainty (technically known as Stochastic Optimization) allow the managers and analysts to design operational strategies that control risk, particularly the bank’s exposure to probabilistic and worst-case scenarios.   Using Scenario Performance Analysis, the lender's team will validate and test their optimization scenarios against a variety of different data sets to understand how their strategies would perform in each case.   Model Quality Evaluation techniques help the credit risk managers compare model predictions against actual performance during a quickly changing economy.   Model impact analysis (related to Model Risk Management) helps senior leadership assess when it is time to invest in improving its statistical models.   Robust Model Calibration Analysis removes unjustifiable variations in the lender's predictive models to make their predictions more valid as things change over time.   These six advanced analytics techniques are especially helpful when developing business strategies for a time in which some values are unknown—including future unemployment levels, staffing budgets, data reporting practices, interest rates, and customer demands.  Business decisions can—and arguably must—be optimized during times of uncertainty. But during times like these, it is especially important that the analysts understand how and why to account for the uncertainty in both the data and the models.   Lenders, are you optimizing your servicing and debt management strategies? It has never been more important than now to do so--using the advanced techniques available to manage uncertainty mathematically. Learn more about how Marketswitch can help you solve complex business problems and meet organizational objectives. 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.  

This is the final part of a three part series of blog posts highlighting key focus areas for your response to the COVID-19 health crisis: Risk, Operations, Consumer Behavior, and Reporting and Compliance. For more information and the latest resources, please visit Look Ahead 2020, Experian’s COVID-19 resource center with the latest news and tools for our business partners as well as links to consumer resources and a risk simulator. To read the first post, click here. To read the second post, click here.  Consumer Behavior Changes Consumers will be hit hard by the economic fallout from the virus. They’ll need to manage available credit and monthly income to bridge the gap when many people are faced with lost wages, tips and the ability to work. Often, the only way to monitor these short-term risks is with trended credit attributes, from both traditional and alternative data sources. These attributes were developed to provide additional insights into how consumer credit usage is trending over time. Is their debt and spending increasing? Have their credit lines been reduced? Have they historically been a transactor but have now started revolving balances? Could the account be a synthetic identity, set up for intentional misuse of credit? The most predictive attributes available in these times can transform how you can identify and respond to risk.   Reporting and Compliance The regulatory environment is continuing to shift. There are continuous changes to compliance in the digital space for emerging channels and applications. There will be impacts to credit reporting and processes that may echo the response from other major natural disasters. The good news is that the framework developed for Comprehensive Capital Analysis and Review (CCAR) stress testing can be used to run scenarios and understand impacts. Although bank capital is very strong, additional regulation, such as the Current Expected Credit Losses (CECL), with all the latest shifts around compliance, may continue to increase the pressure on financial institutions. Having an adaptable process to forecast and stress-test scenarios to adjust capital requirements, especially in light of government fiscal and monetary stimulus measures, will be at the core of managing financial stability during a period of changes.   Conclusion We need to brace for the pending recession after the longest economic expansion in our lifetimes. These are the times where organizations may struggle to survive or thrive in the face of adversity. This is the time to act on your strategic plan, lean on your strategic partners, and leverage industry leading data and capabilities to soften the landing and thrive in the next phase of growth. Let’s prepare and get through this, together.   Learn More

For the last several years, as the global economy flourished, the opportunities created by removing friction and driving growth guided business strategies governing identity and fraud. The amount of profitable business available in a low-friction environment simply outweighed the fraud that could be mitigated with more stringent verification methods. Now that we’re facing a global crisis, it’s time to reconsider the approach that drove the economic boom that defined that last decade. Recognizing how economic changes impact fraud At the highest level, we separate fraud into two types; third party fraud and first party fraud. In simple terms, third party fraud involves the misuse of a real customer’s identity or unauthorized access to a real customer’s accounts or assets. First party fraud involves the use of an identity that the fraudster controls—whether it’s their own identity, a manipulated version of their own identity, or a synthetic identity that they have created. The important difference in this case is that the methods of finding and stopping third party fraud remain constant even in the event of an economic downturn – establish contact with the owner of the identity and verify whether the events are legitimate. Fraud tactics will evolve, and volumes increase as perpetrators also face pressure to generate income, but at the end of the day, a real person is being impersonated, and a victim exists that will confirm when fraud is taking place. Changes in first party fraud during an economic downturn are dramatically different and much more problematic. The baseline level of first party fraud using synthetic, manipulated and the perpetrator’s own identity continue, but they are augmented by real people facing desperate circumstances and existing “good” customers who over-extend while awaiting a turn-around. The problem is that there is no “victim” to confirm fraud is occurring, and the line between fraud (which implies intent) and credit default (which does not) becomes very difficult to navigate. With limited resources and pressures of their own, at some point lenders must try to distinguish deliberate theft from good customers facing bad circumstances and manage cases accordingly. The new strategy When times are good, it’s easier to build up a solid book of business with good customers. Employment rates are high, incomes are stable, and the risks are manageable. Now, we’re experiencing rapidly changing conditions, entire industries are disrupted, unemployment claims have skyrocketed and customers will need assistance and support from their lenders to help them weather the storm. This is a reciprocal relationship – it behooves those same lenders to help their customers get through to the other side. Lenders will look to limit losses and strengthen relationships. At the same time, they’ll need to reassess their existing fraud and identity strategies (among others) as every interaction with a customer takes on new meaning. Unexpected losses We’ve all been bracing for a recession for a while. But no one expected it to show up quite like it did. Consumers who have been model customers are suddenly faced with a complete shift in their daily life. A job that seemed secure may be less so, investments are less lucrative in the short term, and small business owners are feeling the pressure of a change in day-to-day commerce. All of this can lead to unexpected losses from formerly low-risk customers. As this occurs, it becomes more critical than ever to identify and help good customers facing grim circumstances and find different ways to handle those that have malicious intent. Shifting priorities When the economy was strong, many businesses were able to accept higher losses because those losses were offset by immense growth. Unfortunately, the current crisis means that some of those policies could have unforeseen consequences. For instance – the loss of the ability to differentiate between a good customer who has fallen on hard times and someone who’s been a bad actor from the start. Additionally, businesses need to revise their risk management strategies to align with shifting customer needs. The demand for emergency loans and will likely rise, while loans for new purchases like cars and homes will fall as consumers look to keep their finances secure. As the need to assist customers in distress rises and internal resources are stressed, it’s critical that companies have the right tools in place to triage and help customers who are truly in need. The good news The tools businesses like yours need to screen first party fraud already exist. In fact, you may already have the necessary framework in place thanks to an existing partnership, and a relatively simple process could prepare your business to properly screen both new and existing customers at every touchpoint. This global crisis is nowhere near over, but with the right tools, your business can protect itself and your customers from increased fraud risks and losses of all sorts – first party, stolen identities, or synthetic identities, and come out on the other side even stronger. Contact Experian for a review of your current fraud strategy to help ensure you’re prepared to face upcoming challenges. Contact us