Automation and AI for fraud-prevention workflows

Start with a narrow use case

A program might compare a submitted account identifier against an approved register, generate a review checklist or organise incident files.

Before building software, define which data it can access and what constitutes a meaningful result.

Treat AI outputs as hypotheses

A language model can summarise a suspicious message but may invent explanations or miss contextual details. It should not silently approve payments or identify a supposed offender.

Keep the original inputs, review the output and record the decision made by the responsible person.

Design for independent operation

Local processing, modest dependencies and exportable results can reduce unnecessary data transfers. Software requires maintenance and documented limits.

Pacta Cyber Lab develops technical tools and guidance; every implementation should be adapted to the customer’s authorised systems.

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