A lexicon-based model is a computational approach that uses predefined lists of words, phrases, or terms to categorize and analyze text or data. In the context of financial crime prevention, a lexicon-based model may be used to scan documents, communications, or transactions for keywords or patterns associated with money laundering, fraud, or regulatory violations. While lexicon-based models can provide initial insights, they may lack the sophistication of more advanced natural language processing (NLP) and machine learning techniques.
