AI in banking is maturing and entering the mainstream as financial institutions (FIs) roll out AI solutions across their businesses.
AI is helping banks with their anti-money laundering and know-your-customer obligations.
Business Insider Intelligence
This marks a move beyond the experimental for the technology, with a solid majority of global financial services firms either having implemented or currently working to implement AI solutions in business domains like risk management (77%), generation of new revenue potential through new products or processes (80%), customer service (74%), process re-engineering and automation (73%), and client acquisition (69%), per the Cambridge Centre for Alternative Finance and the World Economic Forum.
But even as the AI applications for banking come into clearer focus, buzz surrounding the tech remains undiminished — making it necessary for FIs to look at real use cases to grasp the tech’s true potential. More than three-quarters (77%) of global bankers believe that unlocking value from AI will be the differentiator between winning and losing banks, per a survey conducted by The Economist Intelligence Unit on behalf of Temenos.
To cut through the hype, it’s more useful to view AI solutions in the context of their maturity, judging them through the lens of their growing adoption by consumers and companies, and the impact they have on firms that implement them.
In the AI In Banking report, Insider Intelligence identifies the AI use cases that are transforming the way FIs operate, the business impact of those use cases, and real-world examples of each. We then discuss the most important risks that banks looking to implement AI solutions should bear in mind.
We also examine prominent strategies currently in use by two banks (Bank of America and BBVA) that have invested deeply in AI technology, and provide recommendations for how FIs can best approach implementation of AI-powered digital transformation.
The companies mentioned in this report are: Bank of America, BBVA, BMO Harris, BNY Mellon, Citibank, FNBO, NatWest, Santander, and U.S. Bank.
Here are some of the key takeaways from the report:
- As AI matures and gains popularity in banking, global FIs are building on their existing solutions to solve increasingly complex challenges.
- The technology is manifesting itself in front-office banking in the form of biometrics, virtual assistants, personalized insights, and targeted product offerings.
- In the middle office, AI is helping banks with their anti-money laundering and know-your-customer obligations, aiding in the detection and prevention of fraud, and providing new ways to determine creditworthiness.
- And in the back office, AI is automating tedious tasks and helping employees be more effective at their jobs.
- FIs that want to deploy AI solutions also need to be conscious of the risks that come with the technology, including unintended biases and difficulties managing the sprawling bodies of data that AI models require.
In full, the report:
- Provides best practices that underpin successful implementations of AI in banking.
- Looks at the current adoption of AI solutions in banking and its expected importance in the near future.
- Examines applications of AI across front-, middle-, and back-office banking.
- Discusses the risks associated with the usage of AI in banking.
- Takes an in-depth look at two successful maturing cases of AI in banking.
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