Playbook
AI in Underwriting: Early Proof Points in 2025
How AI tools are being applied to covenant tracking, monitoring, and deal screening.
TL;DR
- Covenants, monitoring, and screening are producing the clearest ROI.
- Time saved (40–70%), earlier variance detection, and 2–4× screening throughput are realistic.
- Control hallucinations with strict schemas + validators; ship audit logs and citations.
1) Where AI is working now (and why)
Best-fit workflows are repetitive, document-rich, and have crisp acceptance criteria. That’s covenants, portfolio monitoring, and high-volume screening.
Operator note: Success = constrained outputs + deterministic guardrails + page-level cites.
2) Proof points teams actually believe
- 40–70% faster covenant extraction with sub-3% post-validation miss rates.
- Monitoring alerts days earlier, fewer “surprises” in OC pressure.
- 2–4× more teasers/CIMs triaged with fewer non-fit meetings.
3) Common failure modes
- Unbounded prompts → hallucinations; enforce schemas and validators.
- Low-quality scans/tables; run OCR and table repair first.
- No audit trail; record model/prompt/version + doc hash with every field.
- Over-automation; keep human-in-the-loop on high-impact fields.
4) Implementation playbook (90-day cut)
- Weeks 0–3: Pick one workflow; define JSON schema; build validator + cites on 50–100 gold examples.
- Weeks 4–8: Reviewer UI with side-by-side PDF, confidence, one-click edits; push to trackers/BI.
- Weeks 9–12: Monitoring jobs + alert routing; start time-saved and miss-rate scorecards.
5) Data, governance, and security
- Source control (doc hashes, page refs), PII handling in-tenant/VPC, model registry, and acceptance logs.
6) What to watch into H2 2025
- Multimodal parsing for tables/exhibits, tuned legal RAG, and scenario helpers for covenant headroom.