In regulated work, the prize isn't automation - it's the decision.
The market that runs on rule-bound decisions - how it works, who's playing, how big it is, and the product to win it.
Illustrative estimates - full method & sources below.
How the money - and the decisions - flow
Toggle lending vs insurance. Highlighted boxes are where Arbiter overlays.
The lender rarely keeps your loan - it makes it, then sells it. The decision is the moment of truth. Arbiter overlays the decision points - the highlighted boxes - without replacing the systems around them.
TAM · SAM · SOM
Drag the assumptions to re-run the model. Every figure is reproducible.
Selling into top IMBs, banks and credit unions is a long enterprise cycle; a realistic 3-5yr capture is ~4% of the $22B SAM ≈ $0.9B. Cross-check: ~5.1M loans x ~25% automation penetration x ~$700 effective price-per-decision ≈ $0.9B.
Sources: mba.org · sf.freddiemac.com · mba.org · statista.com
The competitive landscape, by layer
Who sits where in the stack - and how Arbiter wins each fight.
The platform of record where a loan or policy actually lives end-to-end: application data, documents, workflow, conditions, closing, servicing. It is the operational backbone lenders/insurers build everything else around. High switching cost, deep integrations, slow to rip out. The insurance equivalent is the "core" suite (policy admin, billing, claims).
Their edge: Owns the system of record for a huge share of US originations; data gravity, deep third-party integrations, regulatory entrenchment, and very high switching cost. Distribution moat: AI ships to an installed base rather than needing new sales.
Arbiter: We render and warrant the decision ICE deliberately keeps humans on - as a neutral overlay that runs on Encompass and its rivals. ICE monetizes the seat; we monetize the decision.
Their edge: Massive proprietary training data from one of the largest US originators; vertical integration of tech + capital + brand + servicing; AI tuned to Rocket's own unit economics. Now extending toward lending-as-a-service.
Arbiter: Rocket's flywheel is captive - it can't sell judgment to rivals. We federate anonymized cross-lender judgment that out-breadths any single captive dataset, and we actually sell it.
Their edge: Patented expert-systems IP and a buyback/repurchase warranty that puts money behind the decision - a differentiated risk-transfer moat few competitors match; truly autonomous decisioning rather than copilot.
Arbiter: Candor proved a decision warranty wins in mortgage. We generalize that liability transfer horizontally across lending and insurance, with a closed learning loop Candor's expert system lacks.
Their edge: Embedded POS at many regulated banks/CUs with deep core/LOS integrations and account-opening footprint; multi-product (mortgage + consumer + deposit) gives cross-sell and stickiness.
Arbiter: Blend's Autopilot reviews the docs and data and builds the needs list, but it does not own the final credit decision. We render that decision, cite it and warrant it - as an overlay that runs on top of Blend and the system of record underneath it.
Their edge: The system of record for a large share of P&C carriers; enormous switching cost, ecosystem of partners/integrators, and data gravity; AI distributes to a captive installed base. Core-system entrenchment is the strongest moat in insurance tech.
Arbiter: We overlay the core instead of replacing it, automating the FNOL/underwriting decision past the ceiling a core suite is structurally unwilling to cross.
Coverage vs. autonomy
Coverage vs. how much of the decision each player automates. Top-right is the prize.
The wedge & the moat
A newcomer can't out-distribute ICE or out-data Rocket head-on. So we don't.
Every override and outcome flows into versioned policy + memory + recalibrated thresholds. Incumbents capture data - not structured judgment lineage with a closed loop to convert it.
Their guidelines, overlays, RBAC, approval matrices and audit history live in our ledger. Leaving means rebuilding their control framework and losing the immutable trail exams depend on.
We stand behind decisions with an insurer-backed warranty - selling de-risked outcomes, not automation. That requires a clean eval + outcome history rivals don't have.
Who wins, long-run
An honest read - including the limits of our own concept.
System of record + data rails, AI to a captive base. Slow and under-automated, but hard to dislodge.
Decades-deep captive data flywheel + capital + brand - but can't sell its judgment without arming rivals.
Win on the one thing generalists can't fake: transferred liability and fair-lending defensibility.
Not 'topple ICE' - land a beachhead, prove warranty + governance lock-in, federate cross-lender judgment, expand vertical by vertical.
Bar = illustrative probability of capturing value · ★ marks Arbiter's honest path