Generative AI in Action

Opportunities & Risk Management in Financial Services

Generative AI deployment in financial services has seen a meaningful progression from experimentation to real-world deployment with tangible value for business processes in the last 24 months. Firms’ innovation has nonetheless been careful and responsible, with use cases being implemented only as risk mitigations develop.

As can be expected in financial services, these deployments have so far represented a relatively conservative risk appetite. Considering the speed of technological evolution, more value can likely be unlocked in the future. For example, there remains an opportunity to deploy the technology further in more complex customer-facing use cases and for higher-risk internal tasks. This will however also require appropriate safeguards, such as retaining the ability to introduce a HITL where necessary.

For this to be possible, firms need to find the right balance and navigate the moving parts of not only the emerging technology itself but also evolving best practices in risk management and governance. This would enable firms to confidently operate within the existing regulatory environment and evidence their compliance. Continued investment in data, data governance, cloud and cyber security will all bear fruit when scaling both generative and predictive AI. Only on these foundations will more sophisticated applications such as multi-agent deployments and a combination of generative AI with predictive AI be possible at scale.

Author

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