The Guiding Principles of AI Adoption  

The financial services industry is in a period of discovery and experimentation with artificial intelligence (AI) across internal business units, where leaders are developing a framework for training and adoption. This multipurpose technology has a growth trajectory being fueled by use cases that span from marketing to fraud. If implemented strategically, AI can have a significant impact on employee efficiency and revenue metrics. According to a 2024 AI in Banking study, 96% of financial institutions foresee AI playing a critical role in the next five years.

It’s no surprise that the same study revealed 75% of regional and community financial institutions (RCFIs) are at least experimenting with AI in various operational areas, with the most popular use cases including customer experiences, targeted marketing, data insights and security and fraud. However, realizing AI’s full potential requires a well-defined strategy that balances system performance, return on investment and data compliance. Despite widespread discussion about AI’s expectation to provide unlimited practicality, many financial institutions have taken a cautious approach with an emphasis on internal processes first and then account holder-facing tactics second.

As financial institutions continue to explore and build plans to utilize AI tools throughout their operations, three key components determine how consumers will interact with their bank or credit union, and how they will behave when managing their money. I refer to these as the three Ps of AI: predictive, prescriptive and protective. While the version of the technology will always be unique to the bank or credit union, these overarching methods can guide organizations to focus on the AI applications that could be the most results-oriented and that support servicing each account holder holistically.

Predictive
Predictive opportunities allow institutions to leverage AI technology to anticipate account holder behavior and their potential financial journey. Seventy-three percent of consumers expect banking brands to automatically understand their needs, up from 66% in 2020. For example, AI can identify that an account holder pays a bill each month or transfers money to a specific account, therefore predicting that action will reoccur. The technology will ask the user to complete their action each month — much like Google Maps suggests directions home after work. Banks and credit unions should develop a framework to assist in the analysis of account holder transactions and behavior data that will be foundational for predictive AI.

Prescriptive
The second component, prescriptive, refers to using AI to provide timely advice based on detailed information that can prompt account holders to act regarding their finances. Leveraging behavioral data to identify opportunities for upsell, cross-sell and account adoption has a critical revenue impact on financial institutions for their businesses to thrive. Consider an account holder that has a large sum of money in a savings account that is not maximizing the return on those funds. Prescriptive AI could recommend transferring this money to a high-yield certificate of deposit account or offer wealth investment products to those individuals in a targeted demographic, along with an estimated monetary benefit for the action.

Protective
Protective capabilities through AI technology extend beyond cybersecurity and asset protection. Financial institutions can be proactively protective of account holder funds by alerting them to suspicious activity or by notifying them of a payment causing an impending overdraft with a suggestion to transfer money from another account to avoid fees. AI can also analyze individual behavior to determine whether certain banking activities may be fraudulent, communicating with the account holder prior to processing a transaction.

The three Ps of AI are just a starting point in the broader conversation regarding the technology’s place in account holder engagement. These deployment areas are opportunities for account holders to act by responding to AI-driven recommendations. Seventy-four percent of bank consumers want more personalized services, so institutions can maximize AI’s algorithmic power to build out a banking experience for account holders that will positively and personally affect the way they manage their everyday financial transactions.