With increasing pressure from regulators regarding know-your-customer (KYC) principles and anti-money laundering (AML), many financial institutions are now turning to artificial intelligence (AI)- and machine learning-based solutions to automate and speed up these processes. Although most financial institutions have some automated processes in place, they are typically only rule-based and are non-adaptive (i.e. non-intelligent. This means that they rely on manual efforts to sift, sort and analyze mounds of data. This is precisely where AI and machine learning can help.
After appropriate testing, AI- and machine learning-based solutions offer enormous benefits. Firstly, they improve the overall quality of transaction monitoring and compliance as they can read and make sense of large quantities of structured and unstructured data and can conduct real-time analysis of transactions to classify potentially suspicious ones and grade them as low-, medium- and high-risk categories. This enables prioritized-processing by human operators. They also learn to spot newer patterns of potentially suspicious transactions through continuous learning (both supervised and unsupervised), usually much faster than humans can. Finally, they free up staff to spend more time in creative, problem-solving roles that improve consumer experiences. In the end, these solutions have incalculable potential to transform the financial services industry.