Loss Forecasting for Now and the Future

by Stefani Wendel 3 min read May 21, 2020

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

Related Posts

Used EV Growth Signals a New Phase of Consumer Purchasing Behavior

The electric vehicle (EV) revolution isn’t slowing down, it’s changing lanes. While recent conversations have seemingly focused on softening demand for new EVs, the used segment has been gaining momentum. According to Experian Automotive’s 2025 EV Year in Review Report, new retail individual EV registrations fell 35.9% year-over-year. Meanwhile, the used retail individual EV registrations grew 25.4% from a year ago. As affordability and growing model availability reshapes consumer behavior, buyers are increasingly turning to pre-owned EVs, which has shown an interesting market divergence that is redefining how consumers are adopting this segment and what it can mean for automakers, dealers, and the overall industry. Key players behind rising used EV demand Notably, Tesla accounted for over half (60.5%) of used retail individual EV registrations in 2025, followed by Chevrolet at 6.4% and Nissan (5.5%). Diving a bit deeper, Tesla made up the top three models of the used individual registrations last year, with the Model 3 coming in at 27.2%, Model Y at 21.7%, and Model S (6.6%). The Chevrolet Bolt EV followed at 4.8% and the Nissan Leaf was at 4%. Tesla’s position as the leading make in the used EV market is a natural extension of its long-standing dominance in new EV sales. The brand’s leadership over the years created a large fleet of vehicles that are now entering the pre-owned market. What the used EV boom means for automotive professionals The growing demand for used EVs can present more opportunities for automotive professionals. Dealers that provide a healthy supply of pre-owned EVs can increase accessibility and play a role in adoption for consumers who are actively looking to purchase, while marketers can emphasize value and ownership benefits. As the market continues to evolve, automotive professionals who understand and respond to these changing dynamics will be best positioned to capitalize on the expanding pool of used EV shoppers. To learn more about EV insights, visit Experian Automotive’s EV Resource Center.

Published: June 30, 2026 by Kirsten Von Busch
How Terrace Finance Uses NeuroID to Respond to Fraud Faster and Smarter

Learn how Terrace Finance used NeuroID behavioral analytics to detect fraud faster, respond to attacks, and strengthen risk management.

Published: June 29, 2026 by Scarlet.Nickel@experian.com
Ask the Expert: A Closer Look at Modern Lending with Jeff Hops and Erin Haselkorn

In this first episode of Ask the Expert, Experian's Jeff Hops, Senior Director of Data Platform and Product, and Erin Haselkorn, Senior Director of Analyst Relations, explore how broader data and new signals can help lenders better understand today’s consumers, while maintaining responsible decisioning. Lending is changing  Interest rates, regulation, embedded finance and AI are reshaping the lending landscape. Consumer behavior is evolving just as quickly. But the core job hasn’t changed. Lenders are still making decisions about people they don’t fully know, and that makes data more important than ever. "There are periods where nothing changes, and periods where it seems like everything changes. We’re in the latter … but the core premise hasn’t changed. You’re still trying to lend to somebody you don’t know."Jeff Hops, Senior Director of Data Platform and Product To make those decisions with confidence, lenders need a strong foundation of identity, history and reliable signals. In a period of rapid change, the quality and completeness of that data become even more critical. A more complex view of today’s consumer What has changed is the consumer. Traditional credit data is foundational but can be further enhanced with visibility on how people earn, manage and move money. Income may come from multiple sources, and financial activity often spans bank accounts, applications (apps) and digital channels. Cash flow data, for example, can provide a clearer view of what’s actually coming into a consumer’s account, beyond what traditional records may show.These additional signals can help lenders better understand: Income variability across multiple earning sources Current financial behavior through cash flow activity Digital and identity-linked activity across channels These signals don’t replace traditional data; they expand it. The result is a more complete and current view of the consumer. From exploration to real-world application The conversation around broader data signals has moved beyond theory. Lenders are no longer just asking whether these signals are useful. They’re asking where, how and under what governance they can be applied across the lending lifecycle. Lenders are actively researching, testing and implementing new data sources across the lending lifecycle. What was once experimental is now operational. Institutions are progressing through a clear path: Research Understanding available signals and use cases Testing Evaluating performance in controlled environments Implementation Applying insights in production Today, alternative data is being used in areas like analytics, channel scoring and decisioning, often within governed environments that allow for safe testing and validation. AI may accelerate this shift by helping institutions identify patterns at scale, but its value depends on the strength of the underlying data: quality, governance, context and clear business use cases. More signal, more responsibility As data availability expands, lenders have access to more granular insights than ever before. That creates opportunity, but also responsibility. The institutions that lead won’t be the ones that use the most data. They’ll be the ones that know which signals to use, how to validate them and how to apply them in ways that are fair, explainable and aligned to consumer outcomes. “Institutions can unlock more granular and powerful decisions, but they have to do it responsibly.”Erin Haselkorn, Senior Director, Analyst Relations The future of lending will be shaped not just by how much data is available, but by how thoughtfully it’s applied. Keeping the consumer at the center of decisioning is essential to building trust and long-term success. Explore alternative data with us A more complete understanding of today’s consumers starts with better data. We help lenders responsibly incorporate broader data signals and advanced analytics into decisioning strategies, enhancing visibility into today’s consumers while strengthening risk assessment and expanding access to credit. Let’s work together to build more confident, more responsible lending decisions. Learn more Contact us About our experts Jeff Hops Senior Director, Data Platform and Product, Experian Jeff Hops is a Senior Director in Experian’s Financial Services and Data business with over eight years of experience driving innovation in credit and data solutions. He has led product development for Experian’s Credit Report and played a key role in launching Ascend Identity Platform™, a leading identity resolution platform. Erin Haselkorn Senior Director, Analyst Relations, Experian Erin Haselkorn is responsible for analyst relations for Experian. She has developed an understanding of key marketing trends across a broad range of verticals. Her market research around data strategy, AI, fraud, identity and data management, paired with her broad Experian product knowledge, gives her a unique understanding of business automation and data trends. Erin is a frequent spokesperson and guest blogger.

Published: June 22, 2026 by Julie.JLee@experian.com