AI is likely to change the banking industry at least as much as the creation of the internet changed the banking industry.
The problem is that we are still relatively early – new AI technologies and new solutions based on these technologies are being released every month.
So the question is what should a mid-sized bank CEO do now – if they should even do anything rather than waiting.
From working through this with multiple banks, the answer we get to is that banks should get themselves into a ready state. By getting into a ready state, banks are able to make sure they don’t fall behind their competitors – without spending a lot that could turn out to be wasted spending as new technologies develop.
To get AI ready, banks can:
- Identify use cases that will show value.
- Build data lakes to capture the right data.
- Build and test different AI models on the data.
- Upskill the business to scale AI use – by hiring people and training business teams.
Use cases could include marketing, underwriting, identifying mistakes, fraud detection, and identifying customer upsell opportunities.
Through this process, the bank gets in-line or ahead of its competitors – without risking wasted capex on solutions that will be obsolete in six months because better technology comes along, and without risking becoming locked in to technology solutions that become obsolete.
The bank instead ends up with its data in the right formats and places for any AI system to use, and it has run at least one proof-of-concept trial through which its senior and operating teams become comfortable with AI.