FinTech & Surety · AI Underwriting
AI underwriting platforms — document intake to risk output.
InWork Global builds complete AI underwriting workflow platforms for insurance companies, surety agencies, and specialty finance firms. AI assists and flags; human underwriters keep control of every material decision.
What we build
Complete AI underwriting workflows, built around the underwriter.
We build complete AI underwriting workflow platforms — from document intake through risk output — for insurance companies, surety agencies, and specialty finance firms.
Regulators require human underwriter review on material decisions, so we design for it from the start. AI extracts, spreads, scores, and flags; a human underwriter reviews and makes the final call. Every underwriting decision is traceable, with documentation of the input data and the model version that produced each output.
Platform architecture
A five-phase pipeline from raw documents to a reviewed decision.
Our typical platform architecture moves an application through five phases. Each phase produces structured, confidence-scored output that the next phase consumes.
Phase 1 — Document ingestion: Multi-format support (PDF, DOCX, XLSX, JPEG, PNG, TIFF scanned), an OCR layer combining Azure Form Recognizer, AWS Textract, and a PaddleOCR fallback, and document-type classification across balance sheets, income statements, bank statements, work-on-hand schedules, and references.
Phase 2 — AI extraction & normalization: Field extraction with confidence scoring per field, currency normalization (thousands/millions/actuals), date normalization and period identification, entity resolution across document types, and missing-field detection and flagging.
Phase 3 — Financial analysis: Liquidity ratios (current, quick, cash), leverage ratios (debt-to-equity, debt-to-assets), profitability (gross margin, net margin, EBITDA), multi-period working-capital trend analysis, revenue trend and growth-rate calculation, and surety-specific bonding capacity estimation using the 10x working-capital rule.
Phase 4 — Risk scoring: A normalized 0–100 score with A/B/C/D tier classification, a confidence interval per score, exception flags when any critical ratio falls below threshold, and peer benchmark comparison where data is available.
Phase 5 — Output: Structured JSON for system integration, a formatted PDF underwriting report, CRM/AMS push to Applied Epic, AMS360, or HubSpot, and an exception queue that routes flagged files to a human reviewer.
Case study · Surety MGA
AI-native surety underwriting platform.
Anonymized engagement for a surety MGA processing contractor bond applications. The team needed to scale volume without scaling analyst headcount. Available for reference under NDA.
6-agent pipeline
ArchitectureIngestion → Extraction → Enrichment → Scoring → Narrative → Recommendation. Agents operate autonomously within defined scope, confidence thresholds, and escalation protocols.
Document intelligence
Extraction94%+ extraction accuracy on financial PDFs and Excel workbooks, with automated financial spreading: balance-sheet normalization, working capital, current ratio, and revenue trend analysis.
Parallel enrichment
Third-party dataAn enrichment pipeline pulling FMCSA compliance, credit bureau, and court records in parallel — the manual data-gathering steps that previously consumed days of senior analyst time.
Human-controlled decisions
GovernanceUnderwriters review AI-generated recommendations; final credit decisions remain human-controlled throughout. FCRA-compliant adverse-action language is generated automatically.
Regulatory-ready audit trail
ComplianceA full audit trail on every decision — timestamped, immutable, and regulatory-ready. Explainability, non-discrimination, and audit requirements are built into the architecture, not added after.
Result
Outcome75% reduction in time-to-decision on standard applications (3–5 days to under 4 hours). Consistent scoring across all applications, with analyst time redirected to exception handling and client relationships.
Compliance architecture
Compliance-by-design, not bolted on.
<4 hours
Time-to-decision on standard applications
Down from 3–5 days of senior analyst time per file. Consistent scoring across every application, with humans in control of every final credit decision.
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