Day 2, Vision 2016: A Forecast on the Economy and Industry Insights

by Traci Krepper 3 min read May 17, 2016

vision-2016-paulsen

James W. Paulsen, Chief Investment Strategist for Wells Capital Management, kicked off the second day of Experian’s Vision 2016, sharing his perspective on the state of the economy and what the future holds for consumers and businesses alike.

Paulsen joked this has been “the most successful, disappointing recovery we’ve ever had.”

While media and lenders project fear for a coming recession, Paulsen stated it is important to note we are in the 8th year of recovery in the U.S., the third longest in U.S. history, with all signs pointing to this recovery extending for years to come.

Based on his indicators – leverage, restored household strength, housing, capital spending and better global growth – there is still capacity to grow.

He places recession risk at 20 to 25 percent – and only quotes those numbers due the length of the recovery thus far.

“What is the fascination with crisis policies when there is no crisis,” asks Paulsen. “I think we have a good chance of being in the longest recovery in U.S. history.”

Other noteworthy topics of the day:

Fraud prevention

Fraud prevention continues to be a hot topic at this year’s conference. Whether it’s looking at current fraud challenges, such as call-center fraud, or looking to future-proof an organization’s fraud prevention techniques, the need for flexible and innovative strategies is clear. With fraudsters being quick, and regularly ahead of the technology fighting them, the need to easily implement new tools is fundamental for you to protect your businesses and customers.

More on Regulatory

The Military Lending Act has been enhanced over the past year to strengthen protections for military consumers, and lenders must be ready to meet updated regulations by fall 2016. With 1.46 million active personnel in the U.S., all lenders are working to update processes and documentation associated with how they serve this audience.

Alternative Data

What is it? How can it be used? And most importantly, can this data predict a consumer’s credit worthiness? Experian is an advocate for getting more entities to report different types of credit data including utility payments, mobile phone data, rental payments and cable payments. Additionally, alternative data can be sourced from prepaid data, liquid assets, full file public records, DDA data, bill payment, check cashing, education data, payroll data and subscription data. Collectively, lenders desire to assess someone’s stability, ability to pay and willingness to repay. If alternative data can answer those questions, it should be considered in order to score more of the U.S. population.

Financial Health

The Center for Financial Services Innovation revealed insights into the state of American’s financial health. According to a study they conducted, 57 percent of Americans are not financially healthy, which equates to about 138 million people. As they continue to place more metrics around defining financial health, the center has landed on four components: how people plan, spend, save and borrow. And if you think income is a primary factor, think again. One-third of Americans making more than $60k a year are not healthy, while one-third making less than $60k a year are healthy.

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Final Vision 2016 breakouts, as well as a keynote from entertainer Jay Leno, will be delivered on Wednesday.

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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. 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