From Reactive To Anticipatory: How Banks Can Use Data To Deliver The Next-Best Action
Deep Varma is the chief technology officer at Alkami.
gettyFor decades, financial institutions have been sitting on the data needed to understand their account holders in far more meaningful ways. They can see when someone gets paid, their spending patterns, savings behavior, recurring bills, deposit changes, loan activity and signs of financial stress. Often, they can also see when a major life event may be taking shape, from buying a home to sending a child to college to managing irregular income.
The problem is not that banks and credit unions lack data; it’s that too much of that data remains unused, fragmented across systems or applied only after an account holder has already taken action.
That gap matters because consumer expectations have changed. According to research from The Center for Generational Kinetics (CGK), conducted in partnership with my company, 44% of digital banking account holders wish their primary financial provider did a better job at anticipating their financial needs and goals. Account holders are not asking their bank to know everything about them. They’re asking for the relationship to feel smarter, more relevant and more useful.
That is the shift from reactive banking to anticipatory banking.
Anticipatory banking is not about guessing what an account holder might need or overwhelming them with offers. It is about using data, context and timing to identify moments when a financial institution can be genuinely helpful before the account holder has to ask.
The first rule of anticipatory banking is that relevance has to come before technology.
Too often, financial institutions start with a tool such as a new analytics platform, an artificial intelligence (AI) model, a campaign engine or an engagement feature. Those tools can be powerful, but they only matter if the institution has first defined the outcome it is trying to improve.
Is the goal to help someone avoid a fee? Move idle cash into a better account? Understand whether they can afford a major purchase? Reduce anxiety around a pending paycheck? Identify a product that genuinely fits their life stage?
Without that clarity, personalization can quickly become noise.
The best data strategies start with simple questions such as “What is the account holder trying to do?” And how can we make that easier?
That requires financial institutions to securely connect data across the full digital journey. Account opening, digital banking, marketing and service interactions cannot operate as separate experiences. When those systems are disconnected, the account holder feels the friction. They receive irrelevant offers, repeat information they have already provided or miss out on guidance their institution should have been able to deliver.
When those systems work together, the experience feels like the institution understands the person behind the account.
Some of the most meaningful data signals are not hidden. Consider a gig worker who logs into their banking app 20 times a day. On the surface, that might look like high engagement, but it may also signal financial anxiety. The account holder may be waiting for a deposit to hit so they can pay a bill, buy groceries or make another time-sensitive decision.
A reactive institution might simply count those logins as usage. An institution that practices anticipatory banking would ask why the behavior is happening and what could make the experience better. In this case, a timely push notification when a deposit arrives may reduce the need to manually check the app repeatedly, turning an anxious, repetitive behavior into a moment of trust.
That is the kind of intervention that matters. It is not flashy. It is not personalization for its own sake. It solves a real problem for the account holder.
This is also where technology leaders play an important role. The CTO is no longer responsible only for infrastructure, security and uptime. Those responsibilities still matter deeply, but technology teams also need to help the business identify where data can improve the account holder experience.
That means project, engineering, data and security teams should be close to real user problems. They should understand where friction exists, where signals are being missed and where automation can make a banking relationship feel more human, not less.
There is a fine line between anticipatory and intrusive.
Account holders want relevance, but they also want control. They want their institution to use data responsibly and not make assumptions that feel uncomfortable or overly aggressive. That makes timing, context and consent essential.
The same message can feel helpful or irritating depending on when it appears. A budgeting insight delivered while someone is rushing through a morning commute may be ignored. The same insight, delivered later when the account holder has time to engage, may be useful.
Institutions should also build feedback into the experience. Asking simple questions such as “Was this helpful?” or “Would you like more insights like this?” gives account holders a sense of control. It also helps the institution learn what relevance actually means for each person.
That feedback loop is part of the trust layer. Anticipatory banking cannot be a one-way system in which the institution pushes messages and assumes value. It has to be a learning system that improves over time.
None of this works without clean, well-governed data.
Financial institutions cannot deliver relevant experiences if account holder information is incomplete, poorly integrated or trapped in separate systems. They also cannot build trust if the data behind the experience is inaccurate.
That is why the shift to anticipatory banking needs to be an enterprise technology and leadership priority. It requires architecture for secure integration, consistent data quality and responsible use of intelligence across channels.
It’s about helping banks and credit unions recognize meaningful moments and respond with the right action, at the right time, in the right context.
When that happens, account holders feel known. They feel supported. And over time, that is what turns data into trust.
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