Encouraging prepaid customers into a lifelong banking relationship
Extending the life of prepaid cards is vitally important to their profitability. Even an extra month of usage can make the difference between profit and loss. How we look at the problem may be one of the biggest reasons so many financial institutions fail.
Rather than considering how to entice customers to use the same card longer, we should consider how to build long-term value for those customers so they choose to stay with us.
Stickiness Through Anticipating
Prepaid issuers, program managers, and processors want prepaid customers to continue the cycle of loading and spending beyond the industry average of approximately 6 months. However, despite the increasing numbers of customers who are turning elsewhere for financial services, it’s important to remember that prepaid programs can work as a vital step in engaging customers for the future, and needs change over time. Financial institutions must fully anticipate a cardholder’s next need in order to achieve “stickiness” and attract that customer over and over.
The first step is to identify and suggest other ways to use the current prepaid card. For instance, a cardholder that has a large balance but is not paying bills with it could benefit from bill payment services. If they set up direct deposit, they could benefit from a savings accounts and advanced budgeting tools. If a cash reload occurs, why not recommend several other ways to load, such as remote deposit check capture? As the balance rises above a certain limit, you could introduce a different fee structure. Once you see their loyalty points reach a certain threshold, why not message them about the best redemption options based on historical behavior? By leveraging historical data and trends, you can predict a customer’s needs, earn additional card usage and transform the revenue model.
The second step is for those cardholders who are interested to take a step into new financial products. For instance, the data shows payroll deposit, a certain level of balance, bills being paid overtime and other indicators. While they may still lack an attractive credit score, taking a risk on such a cardholder may be worthwhile. Additionally, when comparing the average revenue and profitability of credit, debit and prepaid, there is a desire to help the cardholders who are ready to “move upstream” into new services. Possibly start with a low-limit or secured credit card with hopes of eventually moving into loans, mortgage, investment, retirement and so on.
App Services Through AI
In most cases, it is not feasible to contact every cardholder in the hope he or she will upgrade to additional services. However, artificial intelligence (AI) solutions, coupled with big data analysis, can create smart cross- and up-sell offers that can be sent directly to a customer’s smartphone app. You already have all usage data, patterns and logs. With AI techniques, intelligent inferences can be made to target customers likely to be open to upgrades – no appointment needed.
The aim is to get ahead of the customer by seeing how they are using their card and matching that with their likely next financial step. With largescale usage data and behavioral analysis, automated analytical engines can detect patterns and generate triggers for actions that could be taken to save money and consequently deepen the relationship. If a customer’s balance is now around $400 rather than the $40 it used to be, this could trigger an offer for a saving account or a message offering a better prepaid solution with a higher balance and better rewards.
But the AI does not start and end with a product suggestion. Customers will have questions about what the new product or service would mean for them. The AI engine needs to both predict likely queries and engage in a two-way conversation by providing information on fees, different options, interest rates, etc. – all delivered through the app with no need for expensive call center resources. It is an opportunity to reassure and evangelize the product benefits. It also can demonstrate how, for example, loyalty plans can be migrated to the new payment mechanisms – after all, earning double or triple points per dollar on a credit card compared to a prepaid card is a strong driver to upgrade.
By encouraging consumers to become increasingly embedded with their financial services partner, you greatly reduce the likelihood that your customers will source their financial services from another party. This is more than simply extending the life of a prepaid card, it champions using the prepaid card as a stepping stone to a long-term relationship.
AI techniques to analyze behavioral patterns are still relatively embryonic. That said, prepaid usage data is increasingly being used to support earlier access to credit facilities as it proves prudent use and financial stability. These techniques are not yet widespread, however, as the financial markets still are learning when and where big data is most effective.
AI systems may not be cheap, but with large, established customer bases, financial institutions are in a strong position to build the business case that justifies such an investment.