Using data for good

According to a recent report from Business Insider Intelligence, banks could see an estimated $447 billion in cost savings by 2023 from AI applications. Some retail banks have already implemented AI features including 24/7 chatbots, virtual voice assistants, predictive analytics and fraud-flagging services.

Business banks are also using AI technology to detect and prevent payments fraud, aid in underwriting assessments and improve anti-money laundering (AML) and know-your-customer (KYC) regulatory checks. The U.N. estimates that around $2 trillion is laundered globally each year, or about 2-5% of global GDP. As money launderers became more sophisticated over the years, AML compliance-related costs rose by more than 50% from 2015-2018. New AI platforms are helping financial institutions stop money launderers, while saving them time and money in the long run.

Driving new efficiencies with ML

Similarly, machine learning (ML) algorithms assess past behavior in order to identify potential trends and future outcomes, as well as flag unusual or suspicious activity. ML tools can also analyze and verify potential customers to ensure they meet strict KYC requirements.

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