They say nature abhors a vacuum, and apparently so do predatory and payday lenders. As people hit by COVID-19 loss of jobs or businesses have struggled to make ends meet and experienced credit rejections or delays in government support, those lenders have stepped in to fill the gap. For many consumers, what looks like a quick fix for their finances ends up a debt trap that’s incredibly tough to escape.
Predatory lenders provide unsecured bridging loans, at high interest rates, which are due for repayment only weeks later. During COVID-19, these lenders have been aggressively pitching their products to the millions of consumers in need of cash.
In some cases, consumers have become increasingly financially vulnerable for more reasons than one. In July 2020, the Consumer Financial Protection Bureau formally scrapped a payday lending rule meant to protect vulnerable borrowers from getting sucked into debt. The rule would have required payday lenders to verify whether people taking out short-term, high interest loans are likely to be able to pay them back — something banks are already required to do.
As a result, retail banking institutions are finding that their customers are frequently in worse trouble than they need to be and, by the time they ask for help, it’s too late. But banks and credit unions that proactively help their customers maintain their financial health, especially at this critical time, can create a win for both their institutions and their consumers.
Step 1: Identify At-Risk Consumers
Some might argue that it’s a financial institution’s duty to educate its customers about predatory lending. Duty aside, it’s also in the interest of banks and credit unions, as a consumer in serious default is a burden.
But institutions need to do more than just publicly condemn predatory loans. To tackle them decisively, they first need to single out at-risk consumers — and they can do this with predictive technologies driven by artificial intelligence.
To kill predatory lending, institutions will need to harness the enormous amount of information that consumers create and share. This information provides the key to pinpointing those at risk. The problem is that most consumers now leave a trail of information so big — and so much of it outside their communications with their banks or credit unions — that the average relationship manager has no chance of collecting and processing it manually.
With AI technologies that use machine learning, institutions can gather more information to develop a holistic view of consumers’ finances, financial relationships, money-management approaches and purchasing behaviors. Armed with this 360-degree perspective, traditional lenders can then zero in on at-risk customers.
Step 2: Proactively Provide Personalized Advice and Loans
Once banks identify which of their customers are most at-risk, they can intervene to offer either small loans at responsible rates, or advice on when to make key purchases and debt repayments, and to whom. Doing the big grocery shopping trip at a different time or paying off a higher interest rate credit card with a lower balance first — all of these decisions can make the difference between solvency or a serious, spiraling problem.
Information generated by machine learning can also help banks structure loans quickly and in a personalized way, maximizing the effect of the money and improving the chances of collecting down the line. Not only does this reduce the risk to the bank or credit union, but it also greatly improves customer service and, ultimately, customer loyalty.
Step 3: Build Your Brand While Protecting Consumers
Increasingly, banks will need to shift from being authoritative and functional to supportive and emotional. This involves forging more educational relationships with people and helping them better themselves financially to achieve their life goals.
Using AI to help consumers better manage their finances, especially in the current environment, presents a clear-cut market opportunity for banks and credit unions to attract and retain customers. The ability to deliver this kind of counsel and helpful intervention to customers is also part of a broader shift they must make to survive and thrive in the future.
When it comes to predatory lending, equality is particularly relevant issue as women and minorities have historically been disadvantaged by unfair lending practices, which — in turn — has contributed to a widening wealth gap. Using AI to help protect vulnerable groups, financial institutions can do their part to close this gap.
In the future, societies will increasingly demand that financial institutions have this kind of ethical impact on the people and communities they serve.
New Challenges Demand a New Approach
COVID-19 has created exceptional circumstances for financial institutions and the consumers they serve. As people’s needs and expectations keep changing, the demand for innovation cannot be contested.
Institutions can use AI to lead customers in the right direction by helping them manage their finances, steer clear of poor decisions resulting from stress, and avoid being preyed on by less-than-honorable lenders, or even fraudsters. And they can use it to help themselves evolve into a banking institution of the future.