Financial institutions are discovering ways to leverage Artificial Intelligence (AI) and Machine Learning (ML) to better combat the rapidly growing challenge of financial crime.
The catalyst for application of these new technologies in crime risk management for banks and credit unions has been the advent of big data. Equipped with a large dataset that provides all of the variations and nuances of legitimate and fraudulent behaviors, systems can be trained to identify abnormal patterns and generate appropriate decisions and actions to mitigate the corresponding financial crime risk.
For large financial institutions, access to big data has been a game changer. The significant volume of data available to those firms is enabling AI and Machine Learning-based solutions to be applied to a broad range of critical business applications; enabling those tasks to be performed more accurately, quickly and cost effectively than manual methods. In turn, this capability has provided large banks with significant competitive advantage, in terms of greater protection and lower customer friction.
However, for smaller banks and credit unions that lack the resources or a customer base that’s large enough to generate a significant dataset, AI and ML-based solutions have failed to deliver the same benefits. Lacking the ability to leverage new technologies, these financial institutions have less ability to manage financial crime risk, which puts them at greater competitive disadvantage.
To compensate for the absence of datasets that are large enough to leverage AI and ML-based solutions, small and mid-sized financial institutions must develop alternative solutions that yield operational benefits that put them on an equal footing with their larger competitors.
That goal can be accomplished through a strategy that integrates these three tactics:
Despite the lack of data necessary for them to benefit fully from AI and ML crime solutions, small and mid-sized financial institutions are actually in a strong position to match or exceed the fraud risk management capabilities of their larger competitors. While capital requirements demand that big banks rely heavily on AI, ML and other technologies, smaller banks can gain competitive advantage through the application of solutions that are tailored to their resources and requirements, are cost effective, keep pace with growing crime risk, and enhance the customer experience.
– By N. Venu Gopal