Fraud Autoinvestigate
Automated fraud investigation that does the legwork before an analyst opens the case
An AI fraud investigator that automatically enriches and investigates cases across connected data sources — Companies House, OSINT and watchlists — so analysts start from evidence, not a blank screen.
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What Fraud Autoinvestigate does
Fraud Autoinvestigate is bigspark's AI fraud investigator. The moment a case opens it goes to work — gathering, enriching and cross-referencing evidence across connected data sources — so your analysts begin from a consolidated picture instead of a blank screen.
Auto-investigation
enrichment checks run automatically as soon as a case opens, with no prompting required.
Event-triggered reports
an investigation can be kicked off automatically by an event (for example a transaction alert or an onboarding trigger), producing a ready-to-review report with no analyst action needed.
Connected data sources
pulls from Companies House, open-source intelligence (web/OSINT) and watchlists, plus your own knowledge bases, through a governed tool layer (Model Context Protocol).
Phase-based workflow
a disciplined locate → investigate → review → close journey, with human confirmation gates between each phase.
Evidence-first discipline
the agent verifies before it asserts, and every finding is traceable back to its source.
How it works
Locate
identifies the subject (person or company) and assembles the identifiers needed to investigate.
Auto-investigate
runs enrichment tools across connected sources automatically, building a consolidated evidence picture.
Investigate deeper
analysts extend the investigation with broader tools and one-click suggested next steps.
Close
a clear risk summary with predefined outcomes (fraud suspected / clear), fully audit-logged.
Built for financial crime teams
Fraud and financial-crime analysts spend hours gathering context before they can make a decision. Fraud Autoinvestigate front-loads that work — cutting time-to-decision, standardising how investigations are run, and keeping a complete, auditable trail of every check and its source. It sits alongside Kai and SparkScan in bigspark's financial-crime toolkit.
Investigation, before the investigator
Most of a fraud analyst’s time goes on the same groundwork: pulling company records, searching the open web, checking watchlists, and stitching it all into a picture they can act on. Fraud Autoinvestigate does that groundwork automatically — the moment a case lands, it gathers and cross-references the evidence, so the analyst opens the case to a consolidated view rather than a blank screen.
It doesn’t have to wait for an analyst, either: an incoming event — a transaction alert, a new onboarding, a watchlist hit — can trigger an investigation on its own and produce a ready-to-review report, so the work is already done by the time a human picks it up.
Governed by design
Fraud Autoinvestigate is built for regulated environments, where “the AI said so” is never enough:
- Traceable evidence — every enrichment and finding links back to the source it came from.
- Human gates — the workflow pauses for analyst confirmation between phases; the agent never runs the whole case unsupervised.
- Governed tool access — data sources are exposed through a controlled Model Context Protocol layer, so the agent can only reach approved tools and knowledge.
- Auditable close — outcomes are recorded against a full trail of what was checked, when, and why.
Ready to get started?
Get in touch with the bigspark team to arrange a guided walkthrough.
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