Pillar 3 of 8

Multi-Source Data
Reconciliation

Integration and normalization of claims data, contract formularies, and pricing benchmarks across disparate healthcare data sources for actuarial analysis.

Data Sources
14
Systems integrated
Records Processed
2.4M
Per month
Match Rate
99.7%
Automated
Processing Time
4.2s
Average

Universal Healthcare Data Integration

Automated Schema Mapping

AI-powered field mapping across 837, 835, flat files, and custom PBM formats. No manual configuration—system learns structure from headers and validates against healthcare standards.

Real-Time Validation

Every ingested record validated against NDC directories, ICD-10 codes, provider NPIs, and contract formularies. Errors flagged with specific remediation steps before processing continues.

Cross-System Deduplication

Fuzzy matching algorithms identify duplicate claims across PBM, TPA, and carrier systems. Resolves conflicts using hierarchical trust scoring—actual adjudicated claim data wins.

Universal Data Model

All data normalized into actuarial-grade common format. Compatible with industry simulation tools, fiduciary reporting standards, and regulatory submission requirements.

Data Quality Engineering

1

Completeness Enforcement

Reject incomplete records upstream before they corrupt analysis. Required fields enforced per claim type—Rx claims need NDC, medical claims need procedure codes, all need member IDs.

2

Pricing Benchmark Integration

Enrich claims with AWP, WAC, NADAC, and MAC pricing from First Databank and Medi-Span. Historical pricing tracked—catch retroactive spread adjustments and AWP inflation schemes.

3

Contract Terms Matching

Map every claim to its governing contract provision. Automated lookup tables link NDCs to formulary tiers, providers to network rates, and specialty drugs to carve-out terms.

Turn Data Chaos Into Actuarial Truth

Manual reconciliation takes weeks and introduces errors. Automation delivers perfection in hours.