Every national health insurance scheme pays out through third-party administrators. The money that leaks between the provider invoice and the payout - upcoding, unbundling, duplicates, limits that were never applied - is invisible unless every row is checked. AI can now check every row, on-premises, before a dirham leaves the account.
KEY TAKEAWAYS
- 1Fraud alone is estimated at 3% to 10% of total health spending - before waste and abuse are counted.
- 2An AI gatekeeper validates, reconciles three ways and audits every TPA invoice before payout, with humans deciding exceptions.
- 3Build it TPA-agnostic, so a successor administrator can be onboarded without rewriting the platform.
3-10%
of total health care spending estimated lost to fraud
NCSL estimate, via Highmark [1]
7 / 7
emirates where basic health insurance for private-sector and domestic workers is mandatory since 1 Jan 2025
Gulf News [2]
<60s
to reject an invalid TPA submission with a structured bilingual error log
HCT platform design target
The leakage problem
What one percent is worth
| Scheme payouts a year (illustrative) | Leakage at 1% | Leakage at 3% | Leakage at 5% |
|---|---|---|---|
| AED 500 million | AED 5 million | AED 15 million | AED 25 million |
| AED 1 billion | AED 10 million | AED 30 million | AED 50 million |
| AED 3 billion | AED 30 million | AED 90 million | AED 150 million |
Illustrative arithmetic only, to show scale. Actual leakage depends on the scheme, its providers and its controls.
The process
How an AI claims gatekeeper works
1
Ingest
Flat file, JSON, XML or secure REST from the TPA.
2
Validate
Schema, duplicates, signatures and medical codes.
3
Reconcile
Three-way match against independent sources.
4
Audit
Rules and anomaly scoring on every row.
5
Approve
Exceptions to a human auditor, by authority.
6
Pay out
Signed payout file to the treasury system.
The core control
Three-way reconciliation
A claim is paid only when three independent records agree: the adjudicated claim from the official claims exchange, the encounter or referral token from the health information exchange, and the TPA's invoice row for that provider and batch.
Audit rules
What the audit catches
| Check | What it catches |
|---|---|
| Unbundling and upcoding | Procedures split or coded higher than the encounter supports |
| DRG complication patterns | Unusual complication coding that lifts the payment group |
| Historical duplicates | The same service billed again across batches or providers |
| Benefits and limits | Exclusions, sublimits and annual limits exceeded |
| Tariffs and rebates | Negotiated prices, volume discounts and rebates not applied |
| Provider outliers | Statistical outliers by specialty and region, with Z-score thresholds |
Visibility
Dashboards oversight teams actually use
⏳
Aging and states
Every invoice from ingestion to disbursement, with 0-15, 16-30, 31-45 and 46+ day buckets.
📊
TPA performance
Adjudication turnaround, financial accuracy and integration uptime against target.
💰
Leakage and recoveries
Recovered amounts, discounts and rebates applied, and fraud, waste and abuse heatmaps.
“Pay on evidence, not on trust - and keep the auditor, not the algorithm, as the one who decides.”
Design principle of the HCT claims gatekeeper
Future-proofing
Do not lock yourself to one TPA
- ✓An open data contract for identifiers, batches, timestamps, signatures and coding.
- ✓Visual schema mapping, so a successor TPA is onboarded without core-code changes.
- ✓Dual-running of old and new pipelines during transition waves.
- ✓Unrestricted export of registers, invoices, matching logs and audit evidence.
FAQ
Frequently asked questions
Can AI audit health insurance claims without sending data to the cloud?
Yes. The gatekeeper runs on-premises inside the payer's environment, and identifiable health data is visible only to roles with explicit clearance.
Does AI decide which claims are rejected?
AI rejects only technically invalid submissions automatically. Every disputed claim goes to an audit exception ledger with reasoning, confidence and evidence, and a human auditor decides.
How many claims can it handle?
The architecture scales horizontally for national schemes processing millions of claims a year, and is sized against the scheme's real volumes during discovery.
See the claims gatekeeper on your own data model
We run a proof of concept on synthetic data in days, inside a UAE environment, with no external AI calls.
Explore the platformTalk to our team