Solution 01

Find the fraud that rules-based systems miss.

Q: How do you control false positives?

Alerts are scored and prioritised, thresholds are tuned to your investigation capacity, and investigator feedback continuously recalibrates the models.

Q: Is the output explainable to a regulator?

Yes. Every alert carries its reasoning, and the methodology is documented and auditable end to end.

Opportunistic and organised fraud both leak value quietly. We turn your claims, policy and payment data into a prioritised, explainable alert queue, so investigators spend their time on the claims that matter.

Request a consultation How it works

ALERT QUEUE · ILLUSTRATIVE SORTED BY SCORE

94 Connected network · 6 linked claims

81 Late reporting + high-value item

63 Document reused across claims

28 Minor timing anomaly

TYPICAL FIRST STEP Fixed-scope fraud diagnostic

DATA REQUIRED 12–24 months of claims, policy and payment history

FIRST FINDINGS Typically within 4–6 weeks

DELIVERABLE A scored, explainable alert queue in your workflow

The problem

Static rules catch yesterday's fraud, not tomorrow's.

Fixed rules flag the patterns you already know about and flood investigators with false positives on everything else. Organised networks structure their claims to stay under those thresholds, while genuine claimants get held up. The result is leakage you cannot see and friction you can feel.

The asymmetry is what makes it expensive. A rule that misfires costs an investigator-hour every time it fires; a ring that adapts costs you silently for years. And the friction lands on genuine claimants — the delayed settlement, the request for yet another document — in a product where the claim is the product. Detection has to become more precise, not merely stricter.

Opportunistic fraud Inflated or fabricated single claims, plausible enough to pass a manual review.

Organised fraud Networks of connected claimants, providers and payment details, invisible claim by claim.

What we deliver

Four detection methods, one prioritised queue.

Anomaly detection Statistical models learn each portfolio's normal and flag the claims that sit outside it.

Network analysis Links across claimants, providers, devices and payments expose organised rings.

Document checks Reused invoices, altered receipts and duplicate supporting documents are caught automatically.

Portfolio-tuned rules Your existing red flags are kept, refined and merged into a single scored output.

How it works

From raw claims to a queue your team trusts.

Connect the data

We ingest claims, policy, provider and payment data from the systems you already run, no rip-and-replace.

Score and rank

Each claim receives a fraud score with the reasons attached, ranked so the highest-risk work rises to the top.

Investigate with context

Investigators open an alert to see the network, the documents and the drivers behind the score, not a black box.

Feed back and improve

Confirmed and dismissed outcomes recalibrate the models, so precision improves with every cycle.

Under the hood

The signals we test on every portfolio.

No single signal proves anything. It is the combination — scored, weighted and explained — that separates a claim worth an investigator's afternoon from one that should be paid the same day.

Timing anomalies. Claims clustered just after inception, just before expiry, or straddling trip dates that do not match the itinerary.

Document reuse. The same invoice, receipt or medical report resurfacing across unrelated claims, policies or books.

Provider billing patterns. Clinics and facilitators whose invoicing sits far from peer benchmarks for the same treatment and geography.

Payment clustering. Multiple claimants resolving to the same account, beneficiary or payment fingerprint.

Identity overlap. Names, documents, devices and contact details shared across policies that should be strangers.

Threshold hugging. Amounts that sit persistently just below authority and referral limits.

Narrative similarity. Loss descriptions that repeat, near-verbatim, across supposedly unconnected claims.

Network topology. Rings of claimants, providers and intermediaries that only become visible when the portfolio is viewed as a graph.

Explainable by design

An alert you cannot explain is one you cannot act on.

Every score carries the specific signals that produced it. Your investigators can defend a referral, your compliance team can audit the method, and a regulator can follow the reasoning end to end.

WHY THIS SCORED 94

Shares a payment account with 5 other recent claims

Same supporting invoice submitted under two policies

Claim filed 2 days after policy inception

ILLUSTRATIVE · REASONING ATTACHED TO EVERY ALERT

Organised fraud is a portfolio phenomenon. You will never see it one claim at a time — and it is counting on exactly that.

THE TSP VIEW

Questions

What insurers ask us first.

Do we need to replace our claims system?

No. We work with the data and systems you already have and deliver alerts into your existing workflow. There is no rip-and-replace and no long integration project before you see findings.

How do you control false positives?

Alerts are scored and prioritised rather than simply flagged. Thresholds are tuned to your investigation capacity, and every confirmed or dismissed outcome feeds back to recalibrate the models, so precision improves over time.

Is the output explainable to a regulator?

Yes. Every alert carries the specific signals that produced its score, and the methodology is documented and auditable end to end. Your teams can defend a referral and a regulator can follow the reasoning.

How long before we see value?

A first diagnostic on historical claims typically surfaces findings within weeks. We confirm timelines at scoping, once we understand your data and priorities.

Can you detect organised networks, not just single claims?

Yes. Network analysis links claimants, providers, devices and payment details to expose organised rings that are invisible when claims are reviewed one at a time.

Who runs the investigations?

Your team does. We provide the prioritised queue, the reasoning and the supporting evidence; your investigators keep full ownership of every decision. Where useful, we help design the triage workflow around the scores.

Does this work on historical claims?

Yes, and that is usually where we start. A retrospective pass over 12–24 months of settled claims quantifies leakage, surfaces networks that are still active, and builds the evidence base for recoveries — before anything touches your live workflow.