AI is trendy, but CUs can't fall into the common trap of pursuing trendy technologies only because everyone else is using them.
The past few years have been filled with complexity and change in the banking industry, which has also triggered a shift in how credit unions use artificial intelligence. We have witnessed an incremental increase in the use of AI in all aspects of banking, as it can reduce labor costs, increase efficiency and productivity, and help credit unions provide better service for their members. Traditionally, credit unions only leveraged AI to automate routine internal processes, like compliance, underwriting or fraud detection, but recent technological developments have led to AI now also being used for front-office purposes, like member service.
This trend will continue this year, as members of credit unions will default primarily to digital channels when searching for solutions to match their financial needs. When it comes to AI, we have seen consumers get particularly excited about features like uniquely tailored services or offerings that anticipate their needs, such as chatboxes or 24/7 customer service bots that can proactively start conversations and provide relevant information and recommendations at any time. Customer relationship management in banking was previously mainly conducted by humans, but AI is now leading the way.
Simply put, AI is trendy. But credit unions need to be careful not to fall into the common trap of pursuing trendy technologies only because everyone else is using them. Known as the shiny object syndrome (SOS), the want rather than need to implement AI can be more detrimental than beneficial for a multitude of reasons.
For starters, investing millions in data infrastructure, AI software tools, data expertise and model development due to a fear of missing out and without actually having a need or long-term strategic plan is an expensive and futile proposition. Even with a plan, acquiring AI without understanding its complexity or conducting a comprehensive proof of concept is wasteful, as the technology will be hard to implement and manage in the long term. One of the biggest mistakes credit union executives make is view AI as a technology with immediate returns, while in reality, months or years can pass before the technology starts bringing in the big wins that executives expected. Being strategic and cautious about acquiring technology should be the norm for all credit unions but is particularly crucial when it comes to AI.
Moreover, AI technology is still far from perfect, especially when it comes to customer service support. This deficit might not be a deterrent for big or medium-sized banks, as their focus has never been on delivering a personalized banking experience for their customers. But many credit union members have specifically chosen to bank with credit unions due to their ethos of caring for their communities and uniquely tailored member service offerings. If credit unions jump on the AI trend and start replacing humans with a substandard customer service bot, without conducting an in-depth market research and analysis beforehand, they gamble losing the essence of what differentiates them in the market.
So, what can credit unions do to avoid falling in the SOS trap?
This trend will continue this year, as members of credit unions will default primarily to digital channels when searching for solutions to match their financial needs. When it comes to AI, we have seen consumers get particularly excited about features like uniquely tailored services or offerings that anticipate their needs, such as chatboxes or 24/7 customer service bots that can proactively start conversations and provide relevant information and recommendations at any time. Customer relationship management in banking was previously mainly conducted by humans, but AI is now leading the way.
Simply put, AI is trendy. But credit unions need to be careful not to fall into the common trap of pursuing trendy technologies only because everyone else is using them. Known as the shiny object syndrome (SOS), the want rather than need to implement AI can be more detrimental than beneficial for a multitude of reasons.
For starters, investing millions in data infrastructure, AI software tools, data expertise and model development due to a fear of missing out and without actually having a need or long-term strategic plan is an expensive and futile proposition. Even with a plan, acquiring AI without understanding its complexity or conducting a comprehensive proof of concept is wasteful, as the technology will be hard to implement and manage in the long term. One of the biggest mistakes credit union executives make is view AI as a technology with immediate returns, while in reality, months or years can pass before the technology starts bringing in the big wins that executives expected. Being strategic and cautious about acquiring technology should be the norm for all credit unions but is particularly crucial when it comes to AI.
Moreover, AI technology is still far from perfect, especially when it comes to customer service support. This deficit might not be a deterrent for big or medium-sized banks, as their focus has never been on delivering a personalized banking experience for their customers. But many credit union members have specifically chosen to bank with credit unions due to their ethos of caring for their communities and uniquely tailored member service offerings. If credit unions jump on the AI trend and start replacing humans with a substandard customer service bot, without conducting an in-depth market research and analysis beforehand, they gamble losing the essence of what differentiates them in the market.
So, what can credit unions do to avoid falling in the SOS trap?
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