What AI Means For The Future Of RCFIs And Digital Banking

Deep Varma is the chief technology officer at Alkami.

While many of the financial institutions making headway with artificial intelligence (AI) are major national and international players, my digital banking company’s research has identified that regional and community financial institutions (RCFIs) are gaining a stronger foothold through experimentation with various use cases.

With this transformation, RCFIs have a unique opportunity to differentiate themselves from larger players by understanding unique ways to bring AI capabilities to their front, mid and back offices.

The Current State Of AI In RCFIs

Since the late 2000s, banks and credit unions have used AI and ML for data analysis. Financial institutions quickly saw an opportunity to use AI for automating fraud and anomaly detection. The industry’s AI spend is projected to rise from $35 billion in 2023 to $97 billion by 2027, which represents a compound annual growth rate of 29%.

Generative AI (GenAI) is improving these detection efforts with real-time insights that can minimize disruptions and keep account holders informed of issues. GenAI also powers chatbots, virtual assistants and documentation tools to improve customer experience.

Likewise, GenAI solutions are being used to support operational efficiency by automating repetitive tasks and data entry. According to McKinsey, GenAI may add between $200 billion and $340 billion in annual value within the industry, in part due to increased productivity through technology.

AI-driven data modeling, similarly, helps financial institutions in areas like credit scoring and loan processing. RCFIs have begun to take this further, implementing AI solutions to enable greater personalization. For example, AI tools can recommend specific products based on industry trends and individual behaviors. These efforts can open up new avenues of revenue generation for the institution.

My company’s research cited above shows that 88% of RCFIs report mostly or very successful outcomes when testing AI technology. The research also showed that 78% of banks and credit unions believe AI can be a catalyst for new business.

This success will be partly due to improved account holder experiences that come from personalization. My company’s research found that 73% of financial institutions believe AI can improve account-holder interactions. Customers tend to agree, with 70% of banking consumers desiring personalized financial advice and 72% seeing value in tailored product recommendations.

Future AI Applications

As AI becomes standard across larger banks and credit unions, RCFIs must prepare for the growing use and influence of these solutions. The good news is RCFIs remain optimistic about AI in banking. My company’s report found that 96% of RCFIs predict AI will have a critical role in the next five years, and 82% believe AI will have a generally positive impact on the banking industry over the same term.

RCFIs must also start to explore the next evolution of AI after GenAI: agentic AI, or AI that can work independently of human direction to make decisions. Through applied reasoning, agentic AI not only takes in information but also reasons, acts and iterates to solve problems. These agents could be the next wave of innovation for RCFIs to support efforts in cybersecurity, human resources and software development.

Agentic AI could also augment personalization efforts, factoring in consumer preferences and market conditions. All of this will be key to transforming account holder experiences and retaining market share.

RCFIs should also explore how AI will continue to create opportunities for greater efficiency and productivity within internal teams. These include developing strategies to consolidate enterprise technology, integrate conversational AI agents and improve regulatory compliance through AI- and ML-assisted analysis.

To prepare for these AI-powered innovations, leaders should start by evaluating their existing data management foundations. To effectively leverage AI tools, data should first be cleaned, organized and readily accessible.

From there, financial institutions can develop new AI processes based on strategic roadmaps, operating models and risk controls while accounting for training programs that can enhance AI literacy and adoption. A structure for ongoing technology review encompassing use, efficiency, security and innovation will help RCFIs remain ahead of the curve as new AI applications continue to evolve.

AI is reshaping RCFIs and digital banking, making them more efficient, secure and customer-focused. Despite challenges like data privacy, ethical concerns and regulatory compliance, institutions that adopt AI have the opportunity to gain a competitive advantage in the evolving financial industry

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