Key ‘analytics interventions’ that drive effective credit card strategy

If you want to boggle your mind, think for a moment about consumer credit card usage.

  • Every second, over 10,000 credit card transactions happen around the world.
  • In 2018, there were 41 billion credit card transactions in the U.S. alone.
  • There are more than 180 million credit card holders in the U.S. – approximately 7 out of 10 adult Americans.
  • The average credit card holder has four different cards.

Since the Diner’s Club became the first multipurpose charge card in 1950, credit cards have worked their way into the wallets of hundreds of millions of American consumers. With a market this big, it is surprising that nearly 40% of U.S. credit unions either don’t have a credit card portfolio – or have sold or outsourced it years ago.

Of credit unions that do, 75% have a credit card penetration well below 20%. The data is clear: credit cards are a source of major untapped potential for credit unions, and the multi-faceted rewards for a good card strategy are many.

A strong credit card portfolio helps to drive growth, profitability, loyalty and deeper relationships. Credit cards are one of the most dynamic and engaging products a CU can offer, and those with greater credit card penetration enjoy higher return on assets than most other loan products.

Credit unions that want to get serious about a credit card strategy should start first with their data. Here are three key ways analytics will make your efforts far more effective.

First, understand who is most likely to respond to a credit card offer. While it’s true that most adults use credit cards, blanketing your membership with the same credit card offer isn’t the best approach. First, start with a predictive analysis that can tell you which members are the most likely to respond.

Mining transaction data will show you which members are currently making payments to other credit card issuers – this is a great place to start. Many credit unions are then able to make very competitive offers with better rates, fewer fees, and attractive rewards to get high response rates. (The most savvy CUs use their member data to know exactly what types of rewards and promotions to offer – more on that later!)

Implement data-driven credit card communication strategies from day one – and never stop. Getting a great response rate to your credit card offers isn’t the end-game – in fact, it’s just the beginning of what can be a long and mutually rewarding product relationship. Once the card is in their wallet, members that activate the card within 10 to 30 days are much more active throughout the life cycle. Enable smart triggers and equip your staff with strategies that get 90% of your cards activated within 30 days – within the first week is optimum based on our analysis.

After six months, reanalyze your data sets to segment and determine go-forward marketing communications. Look at behavioral, demographic, transactional, and spend data for the most relevant reward and promotional strategies. A member with high grocery spend should be offered increased rewards on food category purchases to consolidate their spending to your card. A member with a middle-tier credit profile that is using a store-branded credit card is likely paying high interest rates. Target them with a balance transfer offer that provides valuable cost-savings.

“Re-evaluate and readjust” according to data analysis should become a regular, ongoing practice. This is where we’ve seen many credit unions lose their way, particularly when it comes to lifecycle upgrades. A lot of credit unions still have members in their 40s with inactive student credit cards. Evaluate and extend offers that graduate them through card tiers, progressively unlocking new benefits that provide the right incentives.

Practice proactive and efficient risk management and mitigation. Looking at consumer data from the end of 2019, many were well-positioned with historically low debt levels. But just months later came the rapid and unexpected rise of unemployment, and it’s still unclear how long we’ll remain in the enhanced risk environment.  In our current circumstances and for the foreseeable future, data analytics can provide a more sophisticated understanding and approach to card risk mitigation.

Early delinquency detection and action is a first line of defense. Analytical models can synthesize hundreds or thousands of data points to establish the triggers that predict an impending risk increase. Early interventions can then extend help before problems become more serious. Many of the major card issuers have announced plans to assist cardholders during COVID-19. With help from your data analytics, you can tailor the assistance to a member’s individual situation.

Card collections can be handled with greater efficiency by using data analysis to focus efforts where they will have the most impact, as a California credit union recently did to successfully manage a heavy collection volume. By analyzing hundreds of data points, they were able to determine which accounts had the highest propensity to “roll forward,” – or fall deeper past-due by two or more cycles. They built an ongoing process to track and manage cardholders with the highest roll-forward propensity. This not only reduced the collection queue by 25%, but lowered their losses by focusing on the highest-risk cardholders.

When it comes to credit cards (and actually, every area of a CU) “Analyze and Act” should become a mantra and a habit. A well-managed credit card program will create deep and lasting value for members – and help your card earn its place at the top of their wallet. To learn more on how to drive your card strategies for 2020 using analytics, check out our webinar.

Karan Bhalla

Karan Bhalla

Karan Bhalla is the CEO of CU Rise Analytics and who has almost two decades of financial services and data analytics experience. CU Rise Analytics is a global CUSO helping ... Web: https://www.cu-rise.com Details

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