How to Modernize Your Payments Strategy

2020 induced widespread digital transformation in response to the coronavirus pandemic.

In payments, we saw the rise of options for contactless payments, digital wallets, P2P transfers and more. The challenge for banks was that consumers often did not have to go through their bank to use any of these solutions.

The developments in the payment space over the past year make one thing clear: Banks should keep up with the newest available consumer technology to retain and attract customers, and modernize their digital payments strategy for future success as well.

Consumer demand remains strong, and the experience companies provide matters more than ever. After leaning so heavily on digital solutions for the past year and a half, they expect everything to be easy and instant. It is now relatively easy to find payment apps that provide real-time payments, P2P, bill pay and more. Banks that don’t offer similar solutions runs the risk of losing market share to non-banks that do.

Customers are weighing their banking experience against their experience with fintech apps as well as  any other experience they have when shopping online, ordering food or taking a rideshare. Any good customer experience — no matter the industry — is one that the bank must now measure up to.

Take artificial intelligence (AI) and machine learning, for example. While not every financial institution is using AI and machine learning today, retailers like Amazon.com use AI and machine learning to predict consumer behavior, knowing what they need and when they will need it. They estimate when consumers will repurchase a product or try something new. A bank that is not doing the same is falling behind in providing the experiences that many consumers are growing accustomed to.

Where to Start?
By leveraging technologies like AI and machine learning, banks can use the tremendous wealth of customer data at their disposal to provide a more personalized experience. This is a tremendous advantage over non-bank competitors that do not have access to the same consumer information. It can seem like a challenge to effectively put customer data to use, but there are a few steps banks should take to make the change a successful one.

First, a bank must set clear goals for what it wants to achieve when updating its payment platform or adding a technology like AI and machine learning. For most, the goal will be to provide a better experience, but it is helpful to dig even deeper than that. Ask: Do we want better customer satisfaction? More engagement with the platform? More bill pay users? More account-to-account (A2A) transactions? More P2P transactions? Be as specific as possible with goals, as these form the roadmap for the remainder of the process.

Once goals are set, find the partner that can help achieve those goals. Look for a partner that shares the bank’s vision for payments and has the right skill sets and capabilities to achieve those goals. Finding the right vendor partner will ensure the bank is successful in the end.

Clear goals and a like-minded vendor ensure that the tech a bank uses can help meet its goals. Just as Amazon uses AI and machine learning to predict a consumers’ purchases or recommend a product, banks can predict customers’ payment habits or make proactive payment recommendations to manage their financial health. The use cases of AI and machine learning are versatile, and can serve many different purposes to help banks reach their unique goals.

Finally, do not lose sight of the future. It is easy for banks to get concerned with what will make them successful now, but keep looking ahead. Work with your vendor to think about where both the industry and your bank are going. Be sure to choose solutions that can grow and change with the bank and its customers for years to come, rather than focusing too heavily on the here and now.

Change can be intimidating, but following the right steps to implement a tool like AI will ensure success by creating a better customer experience. Revitalizing your bank’s digital payment strategy is a process, but done right, the stronger digital relationships you build with your customers will be worth it.

Unlocking the Value of Customers’ Data

A customer data platform is at the heart of the most cutting edge, customer-centric digital programs at leading financial institutions. This platform should clean, connect and share customer data so the business lines that need it most can create distinctive and relevant experiences. Amperity’s Jill Meuzelaar details the four key features banks should look for in a customer data platform, as well as common issues they may encounter when evaluating a current or prospective system.

  • How to Connect Customer Data
  • Incorporating Flexibility for Maximum Functionality
  • Avoiding Common Pitfalls

Rethinking the FICO Score


FICO-6-20-18.pngFor decades, pre-dating many banking careers today, the tried and true method to evaluate credit applications from individual consumers was their FICO score. More than 10 billion credit scores were purchased in 2013 alone, a clear indicator of how important they are to lenders. But is it time for the banking industry to reconsider its use of this metric?

The FICO score, produced by Fair Isaac Corp. using information from the three major credit bureaus—Equifax, TransUnion and Experian—has been considered the gold standard for evaluating consumer credit worthiness. It focuses squarely on the concentration of credit, payment history and the timeliness of those payments. FICO scores have generally proven to be a reliable indicator for banks and other lenders, but in an age operating at light speed, in which many purchases can be made in seconds, a score that can fluctuate in a matter of days might be heading toward obsolescence.

Some believe a person’s credit score should be considered only in parity with other, more current indicators of consumer behavior. A study released in April by the National Bureau of Economic Research says even whether people choose an Apple or Samsung phone “is equivalent to the difference in default rates between a median FICO score and the 80th percentile of the FICO score.”

Consider the following example. A consumer pays off an auto loan, resulting in a reduction in their FICO score. This is largely due to the reduced amount of credit extended. That reduced score could become a deciding factor if the customer has applied for, but not yet closed, a mortgage 60 or so days before paying off the vehicle and could affect the interest rate of the applicant.

That leaves a bitter taste for anyone with average or above average credit who has demonstrated financial responsibility and, it could be reasonably argued, would be a much better candidate for credit extension than someone with the same score who doesn’t give two flips about the regular ebbs and flows in their credit.

For all its inherent benefits to the industry, the traditional credit score isn’t perfect. Banks could be using their own troves of customer data to evaluate their credit applications more accurately, more fairly or more often. This could be a boon for institutions hoping to grow their deposit base or enhance their loan portfolios. Some regulators have indicated their attention to this approach as well. The Federal Deposit Insurance Corp.’s Winter 2017 Supervisory Insights suggests data could be a helpful indicator of risk and encouraged member institutions to be more “forward-thinking” in their credit risk management.

“As new risks emerge, an effective credit [management information system] program is sufficiently flexible to expand or develop new reporting to assess the effect those risks may have on the institution’s operations,” the agency said.

That suggests the FICO score banks are currently using might not tell the full story about how responsible credit applicants might be.

“My personal opinion is that among most people, if you have someone who thinks about [their digital footprint and credit], you’re already talking about people who are financially quite sophisticated,” Tobias Berg, the lead author of the NBER study and an associate professor at Frankfurt School of Finance & Management, told Wired Magazine recently. The study examined a number of data points that go far beyond what is incorporated in a FICO score.

That certainly has value for banks. The data they already collect about their customers could be used to determine credit worthiness, but there’s a counter argument to be made. Digital footprints are much easier to manipulate more quickly over time by changing usernames, search history, devices and the like. Using an Android over a more expensive iPhone could be a negative in the study’s findings, for example, which might not reflect the customer’s true credit profile.

But FICO scores are not reviewed as regularly as they could be, and a swing of a couple dozen points from one moment to another can significantly sway some credit applications.

For now, fully abandoning the FICO score isn’t a likely or manageable option for banks, nor one that’s favored by regulators, but the inclusion of digital data in credit applications is something that could be adapted and be beneficial to both the bank and customers eager to expand that relationship with their institution.