Workflow Architecture
Auto claims, commercial underwriting, and subrogation — each exposing different seams where translation debt accumulates when AI inserts into the flow.
How the three workflows connect
Claims is the spine. Subrogation hangs off the far end of it. Underwriting runs in parallel, feeding the same agents and the same organizational context.
Auto Claims
FNOL intake to closure, with two pipelines — AI for simple claims, human for moderate and complex. The most mature, most deeply modeled workflow. It is the largest surface for AI insertion and the source of the subrogation cases downstream.
Underwriting runs parallel. Separate value stream, but shares agents, metrics, and the same company context.
Subrogation Recovery
Post-claim recovery from at-fault parties. Originates from a closed claim, so it inherits every upstream failure. Highest seam risk in the model — recovery depends entirely on documentation it never produced itself.
Commercial Underwriting
Application to bind. Guidewire PolicyCenter-aligned. Models the sales cycle and the broker → underwriter → actuary translation chain. AI augments risk scoring but can’t do the actuarial sign-off or the quote.
The stakes of the connection: underwriting is a separate value stream, so its failures don’t contaminate claims. But subrogation is downstream of everything — a sloppy settlement decision in claims destroys recovery potential weeks later, and Tommy has no standing to fix it.
Auto Claims — the primary workflow
FNOL intake → triage → investigation → damage estimation → coverage verification → liability → settlement → approval → payment → subrogation → closed. Two pipelines split at triage.
COVERAGE 0.8 Policy-language interpretation. Pat’s expertise is a black box — AI reads exclusions literally that specialists know are never enforced.
DAMAGE ESTIMATION 0.7 AI uses database labor rates 6–18 months stale; adjusters mentally correct for it. When AI bypasses that, supplement requests spike.
APPROVAL 0.7 Sanjay trusts Diana’s informal review implicitly — rejection rate jumps 18% when AI skips her.
SUBROGATION 0.9 Downstream of everything. Incomplete files and missing liability documentation compound here.
Commercial Underwriting — the parallel stream
Application submission → data gathering → risk assessment → actuarial pricing → quote generation → bind/issue. Guidewire PolicyCenter-aligned. The translation chain is broker → underwriter → actuary → carrier.
vs replaces
RISK ASSESSMENT 0.8 The Type 2 absence: AI doesn’t know to check adjacent-building risk, prior-carrier non-renewal reasons, or application fill time. AI-written risks run 4–8% worse loss ratios after 18 months.
APPLICATION INTAKE 0.7 Broker language → underwriter language. AI prices “well-managed restaurant” the same as any restaurant.
BIND 0.7 “Full coverage” to the broker is six exclusions in the policy. AI-generated language may not match negotiated terms.
PRICING 0.6 Technical price → quoted price. Greg won’t sign off on a rate that isn’t actuarially justified, but the market may need a different number.
Subrogation Recovery — the downstream seam
Post-claim recovery from at-fault parties, originating from a closed claim: recovery assessment → liability review → demand package → negotiation → collection → closed.
seam risk
ASSESSMENT 0.9 The core Type 2 absence. 12–18% of claims with recovery potential close with $0 because the system never asked who else is liable.
UPSTREAM DEBT Incomplete files and missing police reports kill demand strength — recovery rate drops 30% when files lack evidence.
AI inserts screening and demand-package assembly from structured data — but can’t do liability review or negotiation.
Carrier tactics Rachel’s team knows which at-fault carriers pay fast and which fight everything. AI treating all carriers the same drops the recovery rate.
complexity
Handoff to legal (0.6): claims → legal is a domain boundary with different priorities — the slowest, least flexible seam in the model.
How they interact
The handoffs that define the whole experiment.
| Workflow | Position | AI insertions | Peak seam | Headline metric |
|---|---|---|---|---|
| Auto Claims | Primary value stream | Both pipelines, nearly every step | Subrogation 0.9 Coverage 0.8 | Cycle time, cost per claim, loss ratio |
| Underwriting | Parallel value stream | Augments scoring; cannot replace quote or actuarial sign-off | Risk assessment 0.8 | Written-book loss ratio, adverse selection |
| Subrogation | Downstream of claims | Screens recovery, assembles demand; liability and negotiation stay human | Assessment 0.9 | Recovery amount, recovery rate |
The thesis in one line: AI transforms each workflow at its seams — and the seams that matter most are where institutional judgment, informal controls, and downstream dependencies live. Subrogation is where that thesis bites hardest.