NLP Risk Scoring AMS

Overview

NLP Risk Scoring AMS (Adverse Media Screening) is my MSc dissertation project at the University of Warwick, applying NLP and AI techniques to score adverse media risk and help combat financial fraud.

Key Features

• Adverse Media Screening: Uses NLP to scan and score news and media mentions for financial-crime risk signals.
• Risk Scoring Model: Combines NLP-driven text analysis with a scoring model to grade entities by adverse media risk.
• Compliance-Oriented: Designed to support AML/KYC-style screening workflows used in financial compliance.

Technical Implementation

• NLP/AI: Building and evaluating NLP pipelines for entity extraction, sentiment, and risk classification from adverse media text.
• Domain Grounding: Draws on hands-on AML/FCCM experience from my time at Oracle, applied here in an academic research setting.

Status: In progress — part of my dissertation for the MSc in Cyber Security Management.

• Python
• NLP
• AI/ML