Case Study · Claims & Operations

Leading TPA Cuts Claim TAT from 14 Days to 18 Hours with AI Adjudication

Zealthix Team · February 2025 · 7 min read
93%
TAT Reduction
78%
Claims Auto-Adjudicated
4%
Rejection Rate (from 22%)
₹2.4Cr
Annual Savings
⚙️

Customer Snapshot

Organisation
Mid-size TPA, Delhi NCR (name withheld)
Segment
Payer Third-Party Administrator
Products Used
ZyncFlo, Zudy AI Adjudication
Claim Volume
50,000+ claims processed per month
Insurer Partners
8 insurance companies across health and corporate
Implementation
45-day phased deployment

The Challenge

This TPA was processing over 50,000 health insurance claims per month across 8 insurer relationships a mix of individual health policies, group corporate plans, and government scheme claims. Despite a large operations team of 120+ claims executives, average claim turnaround time had ballooned to 14 days, well above IRDAI's prescribed timelines.

The operational pain points were severe:

  • Manual review bottlenecks: Every claim regardless of complexity passed through at least two human reviewers before approval. Standard, low-risk claims consumed the same staff time as complex, high-value cases
  • 22% rejection rate: A significant portion of claims were being rejected and resubmitted, creating rework cycles that compounded TAT issues
  • Non-standard data formats: Different hospitals submitted claims in different formats some via email PDFs, some through their own portals requiring manual data extraction and validation before processing could begin
  • Fraud detection gaps: With manual review spread thin across high volumes, the team was missing patterns that indicated duplicate billing or inflated procedure costs
  • Staff burnout: The claims team was under constant pressure, with high attrition creating institutional knowledge loss

The TPA's CEO recognised that scaling staff headcount was not a sustainable solution. The unit economics of manual adjudication would only worsen as claim volumes grew.

The Solution: AI-First Claim Processing with ZyncFlo and Zudy

Zealthix deployed a two-layer solution. ZyncFlo standardised all incoming claim data regardless of source format into a single structured pipeline. Zudy's AI adjudication engine then processed these standardised claims automatically, routing complex cases to human reviewers while handling routine claims end-to-end without manual intervention.

Phase 1 (Days 1–15): Data Standardisation with ZyncFlo

ZyncFlo connected to the TPA's existing claim intake channels email, portal, EDI, and paper scan and applied AI-assisted extraction to convert all incoming claims into a standardised FHIR-structured format. Key validations ran automatically: patient eligibility, policy coverage dates, provider network status, and document completeness checks.

Before ZyncFlo, 35% of claims were rejected at intake due to missing or incorrect information. After ZyncFlo, pre-submission validation caught these issues and returned them to providers for correction before they entered the adjudication queue eliminating re-work cycles downstream.

Phase 2 (Days 16–35): AI Adjudication with Zudy

Zudy's adjudication engine was configured against each insurer's policy rules, fee schedules, and benefit structures. The training period used 18 months of historical claim decisions as ground truth teaching the model what constitutes an approvable claim for each insurer-product combination.

The system classifies every claim into one of three tracks:

  • Auto-approve: Standard claims within policy limits, verified providers, complete documentation processed immediately without human review
  • Assisted review: Claims with minor anomalies or unusual patterns flagged with AI annotations for a reviewer to approve or query
  • Manual investigation: High-value claims, suspected fraud patterns, or complex multi-procedure cases routed to senior reviewers

Phase 3 (Days 36–45): NHCX Integration and Go-Live

The final phase connected the adjudication output to NHCX for standardised communication with insurer systems eliminating manual status update emails and enabling real-time claim status visibility for provider hospitals.

Results at 90 Days

Measured Outcomes

18 hrs
Average claim TAT (down from 14 days)
78%
Claims fully auto-adjudicated without human review
4%
Rejection rate (down from 22%)
₹2.4Cr
Annual operational savings (staff redeployment + fraud detection)

Beyond the headline metrics, the quality of human reviewer work improved significantly. By routing only genuinely complex claims to the team, reviewers were better rested, more focused, and producing better decisions. The fraud detection rate also increased Zudy's pattern recognition identified ₹38L in suspected duplicate billing in the first 60 days alone.

The TPA's insurer partners reported a measurable improvement in provider satisfaction scores with hospital cashless desks frequently citing faster approvals as a differentiator when recommending this TPA to patients.

What's Next

Encouraged by the results, the TPA is now expanding Zudy's adjudication coverage to IPD claims a more complex category that currently still relies heavily on manual review. They are also evaluating Zlake for payer analytics building the longitudinal claims data foundation for risk-based product design and population health reporting.

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