Non-performing assets, otherwise known and feared as loans that no longer generate income, are baked into every bank’s cake. The best efforts to keep the ratio of NPAs to gross loans as low as possible can meet many outside forces, recession being foremost.
Statistics posted by the Federal Reserve Bank of St. Louis show at the nadir of the last downturn, banks in the United States grappled with an average 5.6 percent NPA to gross loans ratio. This has since gradually modulated to a more historical norm of around 1.3 percent, but after a long and uninterrupted period of economic growth, many economists are murmuring about the potential for a trouble in the near term.
In the 10 years since the last recession, has technology been developed to help community banks manage NPAs to keep their ratio as low as possible in good times and bad?
There are developers releasing products specifically for this problem in the mode of software as a service, or SaaS, a term heard with increasing frequency in the banking community. Basically, these are pieces of software designed to be inserted into existing core products – no backend change required.
Speridian, a fintech company based in Albuquerque, N.M., with offices around the globe, is one such developer making a case that more sophisticated software should be managing, tracking and even predicting which loans are getting musty. Its NPA offering, Delinkure, was released in 2018. Bobek Djeyfroudi and Billinda Henderson represent Delinkure in the United States, working out of Portland, Ore. They say current NPA tracking models in community banks, based mostly on database queries, lack the following:
- Frequent follow ups.
- Meaningful reports to direct banker to next steps.
- Focused and planned mitigation (due to other pressures).
- Sufficient manpower (too many part-time assignments to provide consistent follow ups).
- Targeted analytics. A blanket approach is commonly used to track all customers.
- Ongoing analysis of a customer’s “big picture.” A customer’s total profile also changes over time, they remind. Systems should be in place to capture and tune processes accordingly.
“Intelligently capturing the day-to-day occurrence of alerts allows bankers to take action and escalate problems to a higher level so that a bank has better process and operational efficiency. Now this has been used in big banks having hundreds of branches as well as banks having as few as five or ten,” Djeyfroudi said of the software’s early performance testing, conducted mostly outside the United States. “Built on open source database tools it can work very well within the budgets of small banks and take on the data volumes of very large banks.”
As always, regulation must be considered, and regulators are keenly aware of NPAs. SaaS solutions are pouring into the marketplace rapidly, and finding the balance between approving the use of new fintech versus assuring the soundness of a bank’s process is ongoing. Djeyfroudi said software developers who know the banking industry start out walking hand-in-hand with evolving regulatory environments.
“Having awareness about the evolution of technology, the regulators are front-runners in helping to enable banks to benefit from the technology,” Djeyfroudi said. “They always create the frameworks so that banks can use it, give guidance to adopt technology for particular use cases, and provide research papers on particular cases that are always free and open to public. A good software developer will use those white papers extensively.”
As for SaaS in general, Djeyfroudi and Henderson said the big name core providers leave a lot to be desired when it comes to very specific, laser-guided solutions to a host of problems. They said core banking providers and full enterprise solutions focus more on customer needs, regulatory mandates, rules, process optimization, security audits and general reporting. SaaS developers can be more focused on any one of these areas and do specific research and development beyond what is available in a larger suite of a core product.
Bankers can use converging technology to solve the problems, they concurred. “Matured technologies such as data warehousing, predictive analytics and evolving technologies such as cloud computing, social media analytics, mobile computing and fast growing technologies such as artificial intelligence, block chain, etc., can all become part of new solutions,” Djeyfroudi said.