Automatable processes in the sector are often rules-based, involving collecting data, validating it against internal and external databases, and assembling required documentation. In theory, conventional software has been used to automate such work. However, Marco Argenti, Goldman’s chief information officer, argues that if a rules-based system resolves most cases, a small percentage of transactions fall outside defined parameters that can translate into thousands of individual items at the type of scale in question. He cites the example of identity verification in KYC compliance, where minor discrepancies or documents approaching expiry can create edge cases requiring judgement.

Argenti says that neural networks can address these micro-decisions as they’re capable of applying contextual reasoning where fixed rules might be missing or don’t necessarily give a clear answer. In this scenario, generative AI augments existing rules systems rather than supplanting them. Operational improvements, therefore lie in the reduction in the number of cases that require manual intervention and thus shortening time needed to resolve the exceptions.