Why AI is the Future of Community Banking

On a surface level, community banking and artificial intelligence (AI) can seem like something of a mismatch in concept. Community banking is all about relationship-lending — forging personal and lasting connections directly with a consumer, while AI — particularly embodied by chat bots and voice assistants — focuses primarily on digitally mediating that personal relationship.
The surface perspective misses the bigger AI picture and the scope of what AI can really offer to community bankers and their customers across the country. AI is a tremendous opportunity for community banking. In fact, it could be a game changer for community banks over the next five years.
There is tremendous potential with the advent of AI to help level the playing field in the financial services space. Use cases are rapidly growing and they are proving that they can really streamline the customer experience in a number of ways while strengthening those personal relationships between the bank and its customers.
The emerging world of AI is complex, especially because it is still in the early phases of entering the marketplace. Artificial intelligence is still a big umbrella, where solution providers are flooding the marketplace and the applications are wide-ranging.
When talking about the AI-enabled future, one might be talking about the Internet of Things (IoT), voice assistants or fraud protection — the list goes on. That leaves community banks with a lot to sift through, and a lot of due diligence ahead of them to determine which firms meet their needs and will, ultimately, be around for a while to serve them.
That task can seem daunting from the outside, particularly to community banks that need to strategically deploy technological infrastructure resources. But, because of the power that AI technology can offer when deployed across a variety of use cases (especially with an early buy-in), and because AI is increasingly looking like the figure of the financial services sector, it is the direction community banks need to fully explore.

No Single Road Map
Every community bank has different needs because every community is different, which means that there is no single road map that community banks must take when they start building out their uses for AI.
What community banks all have in common, is that they focus on the direct relationship with the customer. That means the natural starting point, to include AI use cases that “fit nicely,” is to dig into the customer’s need and figure out where AI can step into the background in providing the necessary services for their customers, such as on boarding and fraud protection. This is so they can provide direct employee contact with the more complex, important transactions that need more oversight. 
For community banks, building an AI strategy is about looking at where the strategic goals already are, and then finding the right AI application and vendor to help achieve those goals.

The Evolving Industry
Big banks do have an advantage, particularly when it comes to technology, with large reserves of resources — they can self-determine the technological path they will follow. But because AI is still in its early days, and interactions and vendors are developing to serve such a wide variety of use cases (niche and general), community banks have an opportunity to leverage technological advances in a new way.
In fact, community banks are using AI to tap into their own internal resources to build better, more responsive community banks.
But as community banks increasingly tap into the mountains of data they collect, they need to be more aware of the challenges that data protection entails. That is even more important with regulators increasingly scrutinizing data usage. Like riding a wave just as it starts to crest, community banks looking to wade into the AI waters early need to be selective when it comes to picking the most relevant use cases and finding the vendors most sufficient to fill those needs. That is real work that needs to be done with care, Giorgio said.
However, community banks have a long track record of protecting consumer data, she noted. As they consider using this data now, community banks need to be guided by regulation without being intimidated by it, because protecting their data has long been central to what they’re already doing.
The AI world is where community banks need to be wading since it is where the market is undeniably growing. That can be seen in the official projections that predict there will be 50 billion connected devices on the market by 2023. And, she noted, most consumers can see it in their own lives, where connected devices have been steadily creeping in for years.
And it’s not just the volume of devices, but what they are doing now that they weren’t two years ago. They are recommending books, movies, clothes, vacation destinations, songs — AI-embedding is increasingly able to use previous behavior to make better recommendations for other things consumers might want or need. Consumers are becoming more used to it and are more likely to look for it as a feature.
It’s a very different environment, and one that community banks are well-served to become versed in, because we are still only in the early days of the changes that are coming.
AI is going to continue to evolve as we move through the remainder of this year and the foreseeable future. It is expected that the rapid pace of change in the AI environment is likely going to continue for at least the next three to five years.


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