Experian Platform Expansion Brings Advanced Analytics and Faster, Better Decisions to FIs of All Sizes

by Jesse Hoggard 3 min read August 15, 2019

Big Data, once thought to be overhyped consultant-speak, is now a term and business model so ubiquitous it underpins billions of dollars in revenue across nearly every industry. Similarly, the advanced analytics derived from big data are key to staying relevant in an everchanging global economy and to consumers with expanding expectations.

But for many financial institutions, using big data and advanced analytics seemed to only be in reach for big banks with large, advanced data teams. With the expansion of the Experian Ascend Technology PlatformTM, the conversation is changing. Financial institutions of all sizes can now leverage advanced analytics, artificial intelligence and machine learning with new configurations in the award-winning platform.

In a release earlier this week, Experian announced new tools and configurations in the Ascend Analytical SandboxTM to fit teams of every size and skill level. Now fintechs, banks and credit unions of every size can have access to Experian’s one-stop source for advanced analytics, business intelligence and ultimately, better decisions.

The secure hybrid-cloud environment allows users to combine their own data sets with Experian’s exclusive data assets, including credit, alternative, commercial, auto and more. From there, users can build and test models across different stages of the lending cycle, including originations, prescreen, account management and collections, and seamlessly put their models into production. Experian’s Ascend Analytical Sandbox also allows users to benchmark their portfolios against the industry, identify credit trends and explore new product opportunities.

All the insights gathered through the Ascend Analytical Sandbox can be viewed and shared through interactive dashboards and customizable reports that can be pulled in near real time. Additional use cases include:

  • Reject inferencing – refine models, scorecards and strategies by analyzing trades opened by previous applicants who were rejected or approved but did not move forward
  • Prescreen campaigns – design prescreen campaigns, evaluate results and improve strategies
  • Cross-sell – identify cross-sell opportunities for existing customers and identify how they may be working with other lenders
  • Collections strategies, stress testing and loss forecasting – build stronger models to identify customers that have ability and willingness to pay debts, stress test and forecast loss
  • Peer benchmarking and industry trends – compare current portfolio against peers and the industry
  • Recession planning – identify areas to adjust your portfolio to prepare for an economic downturn

OneMain Financial, a large provider of personal installment loans serving 10 million total customers across more than 1,700 branches, turned to Experian to improve its risk modeling and credit portfolio management capabilities with the Ascend Analytical Sandbox. Since using the solution, the company has seen significant improvements in reject inferencing – a process that is traditionally expensive, manually-intensive and time consuming. According to OneMain Financial, the Ascend Analytical Sandbox has shortened the process to less than two weeks from up to 180 days.

“Experian’s Ascend Technology Platform and Analytical Sandbox is an industry gamechanger,” said Michael Kortering, OneMain Financial’s Senior Managing Director and Head of Model Development. “We’re completing analyses that just weren’t possible before and we’re getting decisions to our clients faster, without compromising risk.”

For more information on Ascend Analytical Sandbox SX – the latest solution for financial institutions of all sizes – or other enterprise-wide capabilities of the Experian Ascend Technology Platform, click here.

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One Platform, Fewer Handoffs, Faster Decisions

The average credit union manages between 100-300 vendor relationships, and nearly a third have no dedicated staff managing them. What was supposed to drive efficiency is stunting growth and compromising the member experience. Application volume is continuing to rise, and consumers expect a loan decision at digital speed. But for credit unions, meeting that expectation isn't the only goal. They must also continue to make the right lending decisions while also prioritizing risk management. The institutions pulling ahead aren't the ones with the most tools. They're the ones that have turned credit, fraud and decisioning into a single, coordinated system. A single loan decision touches: Credit data Identity verification Fraud signals Decisioning logic Reporting Rarely does all of that live in one place. More often, it’s stitched together across separate platforms, each with its own contract and its own support line. When a credit view and a fraud view are generated separately, they must be reconciled instead of read together in the same instant. Every handoff is a place where a decision slows down and a signal gets missed. It's why a fraud pattern that would be obvious next to the credit file often surfaces only after the funds are already gone. Fragmentation also makes it harder to optimize lending strategies over time. When data, analytics and decisioning are disconnected, credit unions have less visibility into what's working, what's changing and where strategies need to be adjusted. An integrated decisioning ecosystem closes those seams by design, with credit, fraud and lending strategy running on one platform and accessed through a single Application Programming Interface (API). Identity and compliance capabilities can be an integrated decisioning flow. The data doesn't need to be reconciled after the fact because it was never separated in the first place. Stop overengineering, start removing friction When decisioning underperforms, the instinct is to build something more custom: a proprietary model, tighter segmentation, more configuration.  Custom modeling has its place for institutions with the scale and data to justify it. But often, for small or mid-sized credit unions, the bigger opportunity is a flexible decisioning strategy that uses a strong, continuously refreshed model. This shouldn't be either/or. The right approach gives credit unions a strong decisioning strategy today, with the ability to introduce more customized analytics and modeling as their needs evolve.  The same principle applies to strategy management: credit unions can gain greater control through self-service capabilities as they build a more sophisticated data science team.   That kind of flexibility is important as credit unions modernize their decisioning infrastructure. Research surveying more than 2,000 senior credit risk and fraud decision-makers across 11 countries found that organizations investing in unified platforms and modern infrastructure are moving faster and realizing the greatest Return on Investment (ROI).   As their needs evolve, credit unions can adjust decisioning strategies without introducing another layer of technology or relying on third parties to make every change. Until self-service is the right fit, choose a partner that understands what makes your credit union’s membership and risk appetite different from others.  Same member, same afternoon, faster answer Consider a credit union growing its auto and personal loan originations.  A member applies for an auto loan on Saturday afternoon. Credit data, identity and fraud signals are read together in a single real-time pass instead of separate reviews:  Most applications resolve immediately, approved or declined based on a more comprehensive view of the applicant. A smaller number are flagged for quick step-up verification and cleared within minutes. Only genuinely ambiguous cases reach an underwriter, who is working from one complete picture instead of reconciling multiple signals. The member has an answer before the weekend is over. The credit union books the loan before competitors even open on Monday. Built to scale This kind of process holds up today. However, the better test is whether it holds up eighteen months from now when application volume has grown, new products are live and the data flowing through the system looks nothing like it does right now. Future-proofing isn't only about handling more volume. It's about having room to be nimbler and make adjustments as quickly as the market changes. A credit union that relies on standard models within a decisioning strategy may want more customized analytics and greater control over its strategies tomorrow. Connect with us With more than three decades of credit expertise and one of the industry's largest data footprints, Experian helps credit unions do more than solve this year's friction. We're helping to build a decisioning foundation that scales, so growth becomes something the system absorbs, rather than something it must be rebuilt around. Explore More

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