Too many mid-sized financial services institutions rely on reporting modules from their banking cores to try to understand business performance and make strategic decisions.
Core reporting, however, only shows what has happened in the past. It does not provide predictive insights for acting now or in the future. Looking back on what worked for your institution three months ago may inform you of past performance, but it has limited value when deciding what to do next. Your analysis is restricted to a view of the past, and then guesswork for what to do today. This is a business review, not data analytics. Moreover, it can take months to receive core reports. If you are basing your decisions on such analysis, you are making decisions based on stale data.
If you look back three to six months, you may likely see strong mortgage lending performance. But as we know, with climbing interest rates and inflation, mortgages are not the hot product that they were six months ago. The core report data is old and does not reflect important market changes.
It is critical to take action based on fresh data so you can be nimble and pivot your strategy as the market shifts course. Analytics built for mid-market banks offer this granular level of insight at the necessary speed to inform banking strategies. The change in mortgage lending is an obvious one, but what about subtle changes in the market? What about life circumstances and behaviors that change with individual customers? Having information on what was relevant to a customer three months ago does little to inform your actions today.
For example, when a customer changes jobs you have a window of opportunity to market an IRA product before the customer is likely to settle into a new 401(k). If you market the IRA to the customer three months later, they have probably already rolled-over into the new 401(k) — an opportunity missed. Yet if you had a data analytics solution that provided daily insights, such as a change in the income stream pattern by amount or timing of payroll deposits, this could alert you to a change in employment status as it is happening. This gives you the opportunity to sell an investment product when the opportunity is ripe.
Highly popular cryptocurrency is another area where daily insights are extremely valuable because of security implications. Easy entry into the industry enables bad actors to get in front of consumers due to lack of government regulation. This puts banks at greater risk as cyberattacks are reaching new levels of sophistication, and monitoring and remediation resources are scarce.
Using data analytics, you can regularly mine your transactional data to determine which customers have money leaving or entering your bank from a cryptocurrency company. This will give you an actionable list of customer accounts that the security team can flag for cyber attackers so they can take immediate action when needed. In addition, you can conduct longer-term proactive outreach and education with those customers about the security risks associated with crypto.
Up-to-the-minute intelligence about how your customers are interacting with competitors enables you to take measures to win their business. Predictive insights reveal money that is leaving a bank customer’s account and going to a competitor. Outside investment accounts, mortgages, auto loans, checking accounts and other products can be identified, and transferred funds can be analyzed by competitor, product type, customer, payment amount and duration. Based on this data, you can target selected customers with more attractive offers to keep them at your institution. These insights are gleaned daily from mining transactional data across all customers.
Only predictive data analytics can deliver daily insights at scale for all of your customers. By detecting trends and patterns revealing growth drivers through predictive analytics, your team can be nimble and positioned for informed decision-making. This leads to more of what works and less of what is not effective in growing operating income and customer loyalty.
Katie Horvath is CMO of Aunalytics, a data management and analytics company delivering insights for mid-market businesses.