Financial technology has made enormous strides in recent years, though it has largely been used only by institutions that can afford it. Large banks and FinTechs are often first on the scene as they have the capital and resources to implement these innovations. This means that smaller players, such as independent banks or CUs, often risk falling behind. They will need to adapt quickly if they want to remain competitive against their larger counterparts.
One CU making waves in the digital scene is California Coast Credit Union (CCCU), a San Diego-based FI with 185,000 members and $2.6 billion in assets. PYMNTS recently spoke with Angela Moran, CCCU’s chief information officer, on its recent efforts to better engage with members via advanced learning tools.
“The whole digital transformation has really changed the landscape of how consumers interact with technology,” Moran said. “Our competitors are no longer local CUs — they’re big banks like Chase and Wells Fargo as our members are digitally savvy, and they’re accustomed to that kind of digital interaction.”
Moran went on to discuss the CU’s push to transform and evolve with the digital age, and how it uses artificial intelligence (AI) and machine learning (ML) to keep its members safe.
SHIFTING TO A MEMBER-FOCUSED APPROACH
CUs have limited resources and smaller member bases, meaning it would be folly for them to compete with large banks on their terms. CCCU kept this in mind and decided to play to its strengths.
“Our goal is to have a superior member experience, and we can do this with our digital technology,” Moran said. “Credit unions are notoriously good at having that member focus, but from a digital perspective, we need to be member-centric in all of our interactions.”
CCCU had to revamp its digital experience from the ground up. Its core system — a third-party platform called Symitar — organized customer data based on accounts rather than members, making it difficult for the CU to have a holistic view into members’ financial activities. Moran found that one of the system’s most significant challenges was handling the varying information in the accounts.
“If you’ve got five accounts, you have five different records and they can all have different names,” she ex- plained. “They can have your first name and last initial, or your full first and last names, or your first initial and last name. And then there’s variations based on the address.”
CCCU used a tool called Informatica to algorithmically cleanse and standardize Symitar’s data so each member has a unique identifier. This put member information in a single place regardless of which name was used.
USING THE MEMBER-FOCUSED SYSTEM FOR DATA ANALYTICS
The endgame of shifting to a member-focused system was sophisticated data analytics, Moran noted. These can be used for a variety of purposes, the most important being engagement and retention.
“We are sitting on a wealth of lifestyle data about our members vis-a-vis their transactional data,” she said. “Data-driven organizations are significantly better at acquiring new members and keeping them engaged, as well as retaining those members.”
CCCU leverages data analytics to keep members engaged by putting the right products and services in front of them at the right times. If a member has a car loan through another bank or CU, and CCCU is capable of refinancing that loan, the bank can present that offer, for example. She did note that this capability should not be overused.
“We want the communication to be relevant to what they need,” Moran explained. “If someone just got a new car loan through us, we shouldn’t be sending them offers for new car loans.”
The other major area in which CCCU leverages data analytics is member retention. She explained that there are certain warning signs that tell the CU that a customer is considering leaving it for another FI, such as a checking account with a low balance or a loan that is almost paid off. Once the CU has detected a wavering member, it can ramp up engagement to retain them.
“If [someone has] a car loan [they are] paying off, we want to proactively reach out to them and ask if they’ve considered getting another new car, for example,” Moran said.
SECURING CUSTOMERS FROM FRAUD
An added benefit of CCCU’s data analytics-driven approach is that it also helps fight fraud. The CU recently implemented a new security system that utilizes AI to examine and identify fraudulent transactions. It uses pattern recognition to pick out suspicious activities, which are passed on to human analysts for review.
“What this system [does] is essentially tap into our operational data store, which will allow us to detect, in near real time, different anomalies with a pattern of transactions,” Moran explained.
Fraud prevention is just the tip of the iceberg when it comes to credit unions’ use cases for AI and ML.
“We’re really just scratching the surface right now,” Moran said. “We see this changing our industry pretty dramatically, and we need to be prepared to focus on changes that happen in multiples, not just in percentages.”
It is all but certain that CCCU’s current digital transformation will not be its last as financial technologies continue to evolve.