AI plays a key role in transforming unstructured communication data into usable information. For example: • Speech recognition (ASR) converts voice recordings into searchable text • Optical character recognition (OCR) extracts text from images and attachments These capabilities make previously inaccessible data available for analysis

In certain scenarios, AI is used to identify behavioral patterns and communication characteristics. For instance, in video surveillance contexts, AI can assist in detecting specific behaviors or anomalies, helping to surface situations that may require further attention.

This helps identify more complex or implicit risk scenarios that may not be captured through rule-based methods alone. AI provides context and insight, but does not determine compliance outcomes.

In investigation, AI is used to support more advanced analysis, including: • multi-dimensional association and relevance analysis • identification of key stages within an event • early identification of potential risk signals These capabilities help narrow down large datasets and assist in reconstructing how an event developed over time It allows risk detection and analysis to operate consistently and at scale, while also supporting business-side insights such as behavioral trends and communication patterns.

Across all stages, AI serves as an analytical aid rather than a decision-maker. Final judgments—particularly those related to risk or compliance—are always made by human professionals. This ensures that outcomes are: • context-aware • explainable to regulators • aligned with internal policies and governance standards This improves operational efficiency while ensuring consistency and explainability in the identification process.