Tag: scoring models

This article was updated on February 28, 2024. There's always a risk that a borrower will miss or completely stop making payments. And when lending is your business, quantifying that credit risk is imperative. However, your credit risk analysts need the right tools and resources to perform at the highest level — which is why understanding the latest developments in credit risk analytics and finding the right partner are important. What is credit risk analytics? Credit risk analytics help turn historical and forecast data into actionable analytical insights, enabling financial institutions to assess risk and make lending and account management decisions. One way organizations do this is by incorporating credit risk modeling into their decisions. Credit risk modeling Financial institutions can use credit risk modeling tools in different ways. They might use one credit risk model, also called a scorecard, to assess credit risk (the likelihood that you won't be repaid) at the time of application. Its output helps you determine whether to approve or deny an application and set the terms of approved accounts. Later in the customer lifecycle, a behavior scorecard might help you understand the risk in your portfolio, adjust credit lines and identify up- or cross-selling opportunities. Risk modeling can also go beyond individual account management to help drive high-level portfolio and strategic decisions. However, managing risk models is an ongoing task. As market conditions and business goals change, monitoring, testing and recalibrating your models is important for accurately assessing credit risk. Credit scoring models Application credit scoring models are one of the most popular applications for credit risk modeling. Designed to predict the probability of default (PD) when making lending decisions, conventional credit risk scoring models focus on the likelihood that a borrower will become 90 days past due (DPD) on a credit obligation in the following 24 months. These risk scores are traditionally logistic regression models built on historical credit bureau data. They often have a 300 to 850 scoring range, and they rank-order consumers so people with higher scores are less likely to go 90 DPD than those with lower scores. However, credit risk models can have different score ranges and be developed to predict different outcomes over varying horizons, such as 60 DPD in the next 12 months. In addition to the conventional credit risk scores, organizations can use in-house and custom credit risk models that incorporate additional data points to better predict PD for their target market. However, they need to have the resources to manage the entire development and deployment or find an experienced partner who can help. The latest trends in credit risk scoring Organizations have used statistical and mathematical tools to measure risk and predict outcomes for decades. But the future of credit underwriting is playing out as big data meets advanced data analytics and increased computing power. Some of the recent trends that we see are: Machine learning credit risk models: Machine learning (ML) is a type of artificial intelligence (AI) that's proven to be especially helpful in evaluating credit risk. ML models can outperform traditional models by 10 to 15 percent.1 Experian survey data from September 2021 found that about 80 percent of businesses are confident in AI and cloud-based credit risk decisioning, and 70 percent frequently discuss using advanced analytics and AI for determining credit risk and collection efforts.2 Expanding data sources: The ML models' performance lift is due, in part, to their ability to incorporate internal and alternative credit data* (or expanded FCRA-regulated data), such as credit data from alternative financial services, rental payments and Buy Now Pay Later loans. Cognitively countering bias: Lenders have a regulatory and moral imperative to remove biases from their lending decisions. They need to beware of how biased training data could influence their credit risk models (ML or otherwise) and monitor the outcomes for unintentionally discriminatory results. This is also why lenders need to be certain that their ML-driven models are fully explainable — there are no black boxes. A focus on agility: The pandemic highlighted the need to have credit risk models and systems that you can quickly adjust to account for unexpected world events and changes in consumer behavior. Real-time analytical insights can increase accuracy during these transitory periods. Financial institutions that can efficiently incorporate the latest developments in credit risk analytics have a lot to gain. For instance, a digital-first lending platform coupled with ML models allows lenders to increasingly automate loan underwriting, which can help them manage rising loan volumes, improve customer satisfaction and free up resources for other growth opportunities. READ: The getting AI-driven decisioning right in financial services white paper to learn more about the current AI decisioning landscape. Why does getting credit risk right matter? Getting credit risk right is at the heart of what lenders do and accurately predicting the likelihood that a borrower won't repay a loan is the starting point. From there, you can look for ways to more accurately score a wider population of consumers, and focus on how to automate and efficiently scale your system. Credit risk analysis also goes beyond simply using the output from a scoring model. Organizations must make lending decisions within the constraints of their internal resources, goals and policies, as well as the external regulatory requirements and market conditions. Analytics and modeling are essential tools, but as credit analysts will tell you, there's also an art to the practice. CASE STUDY: Atlas Credit, a small-dollar lender, worked with Experian's analytics experts to create a custom explainable ML-powered model using various data sources. After reworking the prequalification and credit decisioning processes and optimizing their score cutoffs and business rules, the company can now make instant decisions. It also doubled its approval rate while reducing risk by 15 to 20 percent. How Experian helps clients With decades of experience in credit risk analytics and data management, Experian offers a variety of products and services for financial services firms. Ascend Intelligence Services™ is an award-winning, end-to-end suite of analytics solutions. At a high level, the offering set can rapidly develop new credit risk models, seamlessly deploy them into production and optimize decisioning strategies. It also has the capability to continuously monitor and retrain models to improve performance over time. For organizations that have the experience and resources to develop new credit risk models on their own, Experian can give you access to data and expertise to help guide and improve the process. But there are also off-the-shelf options for organizations that want to quickly benefit from the latest developments in credit risk modeling. Learn more 1Experian (2020). Machine Learning Decisions in Milliseconds 2Experian (2021). Global Insights Report September/October 2021

Alternative credit scoring has become mainstream. Lenders that use alternative credit scores can find opportunities to expand their lending universe without taking on additional risk and more accurately assess the credit risk of traditionally scoreable consumers. Obtaining a more holistic consumer view can help lenders improve automation and efficiency throughout the customer lifecycle. What is alternative credit scoring? Alternative credit scoring models incorporate alternative credit data* that isn't typically found on consumer credit reports. These scores aren't necessarily trying to predict alternative outcomes. The goal is the same — to understand the likelihood that a borrower will miss payments in the future. What's different is the information (and sometimes the analytical techniques) that inform these predictions.Traditional credit scoring models solely consider information found in consumer credit reports. There's a lot of information there — Experian's consumer credit database has data on over 245 million consumers. But although traditional consumer data can be insightful, it doesn't necessarily give lenders a complete picture of consumers' creditworthiness. Alternative credit scores draw from additional data sources, including: Alternative financial services: Credit data from alternative financial services (AFS) can tell you about consumers' experiences with small-dollar installment loans, single-payment loans, point-of-sale financing, auto title loans and rent-to-own agreements. Buy Now Pay Later: Buy Now Pay Later (BNPL) borrowing is popular with consumers across the scoring spectrum, and lenders can use access to open BNPL loans to better assess consumers' current capacity. Rental payments: Landlords, property managers, collection companies, rent payment services and consumer-permissioned data can give lenders access to consumers' rent payment history. Full-file public records: Credit reports generally only include bankruptcy records from the previous seven to ten years. However, lenders with access to full-file public records can also learn about consumers' property deeds, address history, and professional and occupational licenses. READ: Take a deep dive into Experian's State of Alternative Credit Data report to learn more about the different types of alternative credit data and uses across the loan lifecycle. With open banking, consumers can now easily and securely share access to their banking and brokerage account data — and they're increasingly comfortable doing so. In fact, 70% would likely share their banking data for better loan rates, financial tools or personalized spending insights.Tools like Experian Boost allow consumers to add certain types of positive payment information to their Experian credit reports, including rent, utility and select streaming service payments. Some traditional scores consider these additional data points, and users have seen their FICO Score 8 from Experian boosted by an average of 13 points.1 Experian Go also allows credit invisible consumers to establish a credit report with consumer-permissioned alternative data.  The benefits of using alternative credit data The primary benefit for lenders is access to new borrowers. Alternative credit scores help lenders accurately score more consumers — identifying creditworthy borrowers who might otherwise be automatically denied because they don't qualify for traditional credit scores. The increased access to credit may also align with lenders' financial inclusion goals.Lenders may additionally benefit from a more precise understanding of consumers who are scoreable. When integrated into a credit decisioning platform, the alternative scores could allow lenders to increase automation (and consumers' experiences) without taking on more credit risk. The future of alternative credit scoring Alternative credit scoring might not be an alternative for much longer, and the future looks bright for lenders who can take advantage of increased access to data, advanced analytics and computing power.Continued investment in alternative data sources and machine learning could help bring more consumers into the credit system — breaking barriers and decreasing the cost of basic lending products for millions. At the same time, lenders can further customize offers and automate their operations throughout the customer lifecycle. Partnering with Experian Small and medium-sized lenders may lack the budget or expertise to unlock the potential of alternative data on their own. Instead, lenders can turn to off-the-shelf alternative models that can offer immediate performance lifts without a heavy IT investment.Experian's Lift PlusTM score draws on industry- leading mainstream credit data and FCRA-regulated alternative credit data to provide additional consumer behavior insights. It can score 49% of mainstream credit-invisible consumers and for thin file consumers with a new trade, a 29% lift in scoreable accounts. Learn more about our alternative credit data scoring solutions. Learn more * When we refer to “Alternative Credit Data," this refers to the use of alternative data and its appropriate use in consumer credit lending decisions as regulated by the Fair Credit Reporting Act (FCRA). Hence, the term “Expanded FCRA Data" may also apply in this instance and both can be used interchangeably.1Experian (2023). Experian Boost

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

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.  

Today is National Fintech Day – a day that recognizes the ever-important role that fintech companies play in revolutionizing the customer experience and altering the financial services landscape. Fintech. The word itself has become synonymous with constant innovation, agile technology structures and being on the cusp of the future of finance. Fintech challengers are disrupting existing financial models by leveraging data, advanced analytics and technology – both inspiring traditional financial institutions in their digital transformation strategies and giving consumers access to a variety of innovative financial products and services. But to us at Experian, National Fintech Day means more than just financial disruption. National Fintech Day represents the partnerships we have carefully fostered with our fintech clients to drive financial inclusion for millions of people around the globe and provide consumers with greater control and more opportunities to access the quality credit they deserve. “We are actively seeking out unresolved problems and creating products and technologies that will help transform the way businesses operate and consumers thrive in our society. But we know we can’t do it alone,” said Experian North American CEO, Craig Boundy in a recent blog article on Experian’s fintech partnerships. “That’s why over the last year, we have built out an entire team of account executives and other support staff that are fully dedicated to developing and supporting partnerships with leading fintech companies. We’ve made significant strides that will help us pave the way for the next generation of lending while improving the financial health of people around the world.” At Experian, we understand the challenges fintechs face – and our real-world solutions help fintech clients stay ahead of constantly changing market conditions and demands. “Experian’s pace of innovation is very impressive – we are helping both lenders and consumers by delivering technological solutions that make the lending ecosystem more efficient,” said Experian Senior Account Executive Warren Linde. “Financial technology is arguably the most important type of tech out there, it is an honor to be a part of Experian’s fintech team and help to create a better tomorrow.” If you’d like to learn more about Experian’s fintech solutions, visit us at Experian.com/Fintech.

Using a risk model based on older data can result in reduced predictive power.