AI-Enabled News Summarization for Financial Risk Management

Overview & Synopsis

The rapid advancement of Artificial Intelligence (AI), particularly in Large Language Models (LLMs) like Generative Pre-trained Transformer (GPT), presents significant opportunities for enhancing financial risk management practices. This paper examines the application of large language model (LLM)–based news summarization to financial risk surveillance at the World Bank Group. A cloud-native prototype, developed jointly by the Chief Risk Officer Market and Counterparty (CROMC) and the Technology Innovation Office (ITSTI), automates the sourcing, filtering, and summarization of financial news using the GPT family of models (OpenAI). The prototype integrates automated sourcing from curated outlets, taxonomy-based filtering, full text retrieval, LLM summarization, hallucination checks, and threshold-based alerting tied to key financial indicators (e.g., yields, foreign exchange, equity volatility). The paper concludes with lessons learned from this fruitful collaboration and recommendations for future work, including the potential for broader application for other departments and beyond.