Credit unions and the challenges of the digital age

Can credit unions remain relevant in a digital age? And, if so, how? These are the questions that Mark Sievewright tried to answer at the annual conference of ABCUL in Manchester.

As the senior vice president and chief risk officer of Financial Services Technology (FISERV), Mr Sievewright advises credit unions in the USA on how to make the most of new technology. Apart from dealing with challenges such as legislation, regulation and competition, credit unions must remain relevant by fulfilling the needs of the customers.

“We are at the beginning of the end of the plastic card,” he warned, citing the examples of former industry leaders Kodak and Blockbuster, which were left behind by customers after failing to adapt to market changes.

“We shall never say,‘this will never happen’ – the graveyard is full of companies who have said that,” he added.

One change is that a convenient branch location is no longer the key driver for credit unions.

“Your location today is everywhere,” said Mr Sievewright, explaining that consumers increasingly want to access their credit unions and their accounts no matter where they were. “We don’t talk about extended hours, we talk about online banking, which is 24 hours.”

Branches will remain the cornerstone of relations with most customers, he added, but far more transactions will take place online or via mobile platforms. At the same time, that the implementation of self-service in branches would free up staff to spend more time with members.

“Branches must be tightly integrated with either delivery channels giving members choice that best meets needs,” he said, adding that credit unions must focus on providing outstanding experience in branches, online and mobile.

He argues that CUs need to change their priorities. “You have to say – how are we going to be relevant 10 years from now? You should worry much less about becoming insolvent and much more about becoming relevant,” he said.

To help this process, he said FISERV has developed 12 algorithms for predicting customer behaviour, such as whether members are likely to leave an institution and how likely it is for a credit union to win those members away.