Abstract
As large language models (LLMs) evolve AI capabilities for interpreting complex, and often unstructured linguistic text and for their ability to generate engaging human-like language responses, The Alan Turing Institute’s Fair Prosperity Partnership is exploring emerging opportunities for safe, trustworthy adoption within the financial services sector.
The Impact of large language Models in Finance: Towards Trustworthy Adoption captures collective insights revealed within a study conducted with the support of colleagues from HSBC, Accenture and the UK’s Financial Conduct Authority (FCA). The work included an extensive literature survey on the impact of LLMs in banking and insights shared by 43 participants who attended a face-to-face workshop examining questions about the likelihood, significance, and timing of the integration of LLMs into financial services. Workshop participants were from major high street banks, regulators, investment banks, insurers, consultancies, payment service providers, and other stakeholders, with the majority revealing that they have begun to employ LLMs for varied internal processes, and to actively assess their potential for market-facing activity. They illustrated a granularity of understanding that is inherently emerging with these deployments which could lead to the development of purpose-specific, auditable models that mitigate many risks stemming from the current lack of ability to predict or explain, and thereby rely on LLM outcomes. Overall, discussions delved into significant potential to tackle persistent concerns and develop strategies that could advance safe adoption of LLMs generally. They also elevated global considerations to be navigated, for example, unfair concentration of services in large organisations with the data to support LLM development or competitive advantage in countries with a favourable regulatory landscape. Recommendations included support for a sector-wide and cross-sector analysis of current use that can elevate best practices, and exploration into opportunities emerging with open-source models specialised in financial tasks, such as FinMA and FinGPT.
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