Fraud Analytics
Detect and prevent claims fraud at scale — spot suspicious claims and organised fraud early, cutting leakage while treating genuine claimants fairly.
What is Fraud Analytics?
Fraud Analytics at MindCraft Solution helps insurers cut the costly leakage of claims fraud. We build analytics that score claims for fraud risk, detect networks of organised fraud, and surface the suspicious cases for investigation — so you reduce fraudulent payouts while settling genuine claims quickly and fairly.
Fraud is increasingly organised and hard to spot manually. We combine predictive models, anomaly detection and network / link analysis over claims, parties and history to flag both opportunistic and organised fraud, with explainable indicators and case-management tools for your special investigations unit.
Integrated with your claims workflow, the result is lower fraud leakage and faster, fairer settlement for honest customers — with the explainability and audit trail investigations require.
What Fraud Analytics includes
Everything you need to take fraud Analytics from idea to a dependable, owned capability.
Fraud risk scoring
Score every claim for fraud likelihood.
Network & link analysis
Detect organised fraud across parties and claims.
Anomaly detection
Surface unusual patterns and outliers.
SIU case management
Tools and context for investigators.
Explainable indicators
Clear fraud indicators investigators can act on.
Claims-workflow integration
Screening built into the claims process.
Outcomes we target
Typical results from MindCraft insurance AI Platform engagements.
Our delivery model
A clear, low-risk path from first call to a running, optimized solution.
- 1
Analyse fraud patterns
We study your fraud history, data and current controls.
- 2
Build detection
We build scoring, anomaly and network-analysis models.
- 3
Integrate
We embed screening into the claims workflow and SIU tools.
- 4
Operate & adapt
We refine with investigation outcomes and new patterns.
From problem to outcome
The pressures we see in insurance — and how we fix them.
- Challenge
Slow claims settlement
How we solve itTouchless claims automation that settles faster.
- Challenge
Inconsistent underwriting
How we solve itData-driven, explainable underwriting AI.
- Challenge
Claims fraud leakage
How we solve itAdvanced fraud analytics before payout.
The stack we use
What you get
Concrete, owned artifacts — not just advice.
- Fraud scoring models
- Network / link analysis
- SIU case-management tools
- Claims-workflow integration
- Dashboards & reporting
Questions, answered
Through network and link analysis — connecting parties, claims, addresses and history to reveal rings and patterns that scoring a single claim in isolation would miss.
No — the goal is the opposite: by quickly clearing low-risk claims and focusing scrutiny on suspicious ones, honest customers are settled faster while fraud is caught.
Yes — we surface clear, explainable indicators and context so investigators understand why a claim was flagged and can act with confidence.
Yes — scoring runs in the claims workflow and flagged cases flow into SIU case-management tools with the supporting evidence.
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Ready to talk about Fraud Analytics?
Tell us where you are and what success looks like. We'll bring the right people, stack and plan — and reply within one business day.