Exposing Fraud Faster With AI-Driven Open-Source Intelligence
Insurance fraud is growing in cost and complexity. Opportunistic claims blur into organised networks, and manual methods can't keep pace with the volume and speed of digital activity. AI-enabled open-source intelligence (OSINT) gives fraud teams the reach and clarity they need to see more, act sooner, and decide with confidence.
The pressure by the numbers
Detected insurance fraud in the UK reached an estimated £1.16bn in 2024, up from £1.14bn in 2023, according to the ABI. That's just what was found. Undetected activity continues to distort risk, erode trust and push premiums higher. If budgets are going to move the needle, they must back solutions that deliver fast, repeatable results.
Social media: a rich source hiding in plain sight
Social platforms are a reliable source for spotting opportunistic and organised fraud. Think injury claims contradicted by public posts, crash-for-cash crews coordinating activity, or ghost-brokers recruiting and selling fake cover. The signals are there, scattered across posts, images, videos and niche forums. The gap is not evidence - it's the ability to find it quickly and connect the dots.
Mapping connections at machine speed
Modern OSINT can scan and prioritise millions of items, correlate across sources and surface indicators of risk up to 400x faster than manual review. It flags links between people, pages, groups, locations and claims. Patterns emerge early: shared playbooks, repeat collaborators, common assets and suspicious timelines.
Overcoming scale and data sprawl
There are nearly 55 million social users in the UK today, with projections topping 65 million by 2027. No team can review every platform - let alone venture into deep or dark spaces where tactics and recruitment often sit. AI-driven tooling filters noise, focuses on relevant signals and presents investigators with clear, verifiable leads.
Augmenting, not replacing, investigators
Technology should accelerate skilled work, not replace it. OSINT automates collection, normalises data, checks across multimedia and integrates external sources, including registers of known offenders. Investigators and assessors still make the final call. The result: stronger outcomes without endless headcount increases or slow manual processes.
Clear lines on privacy and compliance
Responsible OSINT applies configurable analysis, avoids irrelevant or excessive personal data, and respects privacy by design. Practices can align with GDPR and the principles outlined in the EU AI Act, with auditable workflows and transparent criteria. Set the rules, log the decisions, and keep proportionality front and center.
A practical playbook for insurers
- Prioritise high-yield use cases: staged accidents, exaggerated injuries, ghost-broking, linked claims, repeat participants.
- Define clear signals and thresholds: location inconsistencies, lifestyle contradictions, repeated asset reuse, shared contact details.
- Automate collection across approved sources and formats: posts, images, captions, comments, group activity, niche platforms.
- Enrich with internal data and external watchlists; maintain strict access controls and audit trails.
- Start with a pilot book and scorecard; expand once lift is proven across multiple lines.
- Upskill investigators on OSINT workflows and responsible AI use; refresh training quarterly.
Metrics that prove impact
- Time to triage and time to first actionable insight.
- Cases concluded per investigator per month.
- False-positive rate and quality of evidence packs.
- Conversion to repudiation, recovery or sanction.
- Claim leakage prevented and ROI versus legacy tooling.
Real-world examples you'll recognise
Injury claims undermined by public posts showing contact sports or heavy workouts. Orchestrated crash-for-cash chains where the same vehicles, drivers or repair shops repeat. Ghost-brokers advertising "cheap cover" through closed groups, then disappearing after a single payout. OSINT helps teams spot these patterns in minutes, not weeks.
What good looks like
- Configurable, case-centric workspaces that combine social, forums, and open records.
- Entity extraction for people, places, assets and companies, with link analysis that exposes networks.
- Multimedia analysis across text, images, and video to surface contradictions and connections.
- Human-in-the-loop review with documented reasoning to support fair decisions and audits.
Bottom line
Fraud is moving fast. AI-driven OSINT lets you meet volume with speed, strengthen evidence, and reduce loss - while staying compliant and fair. Teams that act now will cut cycle times, improve outcomes and give honest customers a better deal.
If you're building skills for your team, explore practical AI training paths here: AI training for insurance teams.
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