CrediSignal — Real-Time Adverse News and Risk Intelligence Monitoring
An automated news intelligence pipeline that collects, matches, summarises, and risk-tags adverse news about banking entities — enabling proactive early-warning monitoring for credit and financial crime risk teams.
Executive Summary
Risk teams need timely monitoring of adverse news about clients, counterparties, directors, and connected parties. Manual monitoring does not scale. CrediSignal is an automated pipeline that collects relevant news, matches entities to banking records, summarises with LLMs, and surfaces risk-tagged output through structured reporting.
Business Problem
Adverse news — negative press about financial difficulties, legal issues, regulatory actions, or fraud allegations — is a key early-warning signal in credit and financial crime risk management. News APIs and web sources produce enormous amounts of content, most of it irrelevant to any given entity.
My Role
I led the design and development: entity list management, keyword generation, news collection, text cleaning, entity matching logic, LLM summarisation prompt design, risk taxonomy development, and output design for dashboard and Excel reporting.
Architecture
Risk Taxonomy
Summarised articles are tagged against a risk taxonomy covering major adverse news categories relevant to banking:
Business Impact
Lessons Learned
Confidentiality Note: Due to employer obligations, code, raw data, proprietary models, and internal investigation details are not disclosed. This case study presents architecture, methodology, and business impact only.