Counterparty EDD autopilot for money-movement fintechs, turning ownership sprawl into bank-ready evidence files.

1. AI in fincrime is now being sold on regulator-ready case files and complete audit trails, so counterparties are newly open to accepting machine-assembled diligence evidence instead of only human-built binders.
2. The clearest pain is still the manual work after an alert or review begins, which makes repeated ownership and EDD packet assembly an immediate workflow to automate rather than a speculative future feature.
3. Beneficial ownership and enhanced due diligence are explicitly in the first production workflow set for agentic fincrime platforms, so this wedge matches what the market is already proving buyers will test.
4. Transparent source-traced reasoning and private-cloud or air-gapped deployment remove two of the biggest historical blockers to automating sensitive counterparty diligence.
5. Live deployments across banks, fintechs, and government suggest this is not a niche pain point but a broad control problem that can support a venture-scale company.

Catalyst. Tangos' funding and commercial deployments around autonomous investigations, beneficial-ownership workflows, regulator-ready case files, and source-traced reasoning show that counterparties are finally willing to trust AI-built diligence packets when every claim is cited and reviewable.

The product creates a living evidence graph for each regulated entity rather than a static folder of diligence documents. It syncs legal-entity records, investor and board updates, licenses, prior questionnaire answers, and supporting files, then uses source-traced agents to assemble partner-specific beneficial-ownership maps, source-of-funds narratives, and exception explanations. Each output links every assertion back to an underlying document, highlights stale or contradictory evidence, and keeps a reviewer log of what changed since the last submission. When a sponsor bank or card network sends a new template, the team starts from a reusable case file instead of rebuilding the packet by hand. Over time, the company becomes the system of record for how a fintech proves its identity and control posture to every critical counterparty.

What's different. Screening vendors tell compliance teams where to look, and outside counsel packages findings after the fact, but neither maintains a reusable evidence graph that answers recurring partner reviews. This company owns the ongoing assembly layer between entity records, ownership changes, risk data, and counterparty-specific templates. Its moat comes from template libraries for real bank and network requests, structured ownership-resolution workflows, and a growing corpus of which evidence packages clear which counterparties fastest.

Jobs to be done

flowchart LR
  Buyer[Fintech compliance lead] --> Pain[Repeated bank EDD and ownership reviews]
  Pain --> Product[Counterparty EDD autopilot]
  Product --> Outcome[Faster approvals with cited evidence files]

Executive takeaways

• Counterparty diligence is becoming an evidence-assembly problem, not just a screening problem: Tangos, Sumsub, Hawk, and Moody's all now market agent-assisted, audit-friendly workflows around investigations, ownership, and KYB.[1][23][26][28][29]
• Sponsor-bank scrutiny remains the forcing function. OCC, FDIC, Fenwick, Sidley, Lithic, and DataVisor all describe tighter lifecycle oversight, fragmented responsibilities, and heavier documentation burdens in bank-fintech arrangements.[7][8][9][10][17][19][20][35]
• The wedge is under-served because onboarding vendors, data providers, and investigation platforms each solve a slice of the workflow, but few are built to maintain a reusable internal evidence graph that can answer recurring bank- and network-specific templates.[21][22][23][25][26][29][30]
• The broader category is growing, but the venture case depends on winning a narrow, high-complexity buyer set rather than the full AML software market: public reports put adjacent AML and KYC markets in roughly 11% to 14% CAGR territory.[31][32][33][34]

Market definition

The market is counterparty EDD automation for regulated money-movement fintechs: software that maintains ownership, control, licensing, and source-of-funds evidence and then assembles partner-specific diligence files for sponsor banks, correspondents, networks, and regulators. It sits between classic CDD/KYB onboarding and bank-side investigations.[4][8][17][21][23][26]

Customer and buyer

The daily user is the head of compliance, MLRO/BSA lead, or legal-ops owner who must answer annual reviews, new-program diligence, and change-of-control questions from bank or network partners. The economic buyer is usually the CCO, GC, or COO because the pain spans compliance, partner management, and launch risk.[17][18][19][22][27]

Buying triggers

• A sponsor bank, network, or correspondent requests an annual review or enhanced due diligence refresh just as the fintech is launching a new rail, corridor, or program. [8][10][17][19]
• A new investor, cap-table change, or control change forces the team to update beneficial ownership narratives and evidence across multiple counterparties. [5][13][25]
• Heightened supervision or remediation pressure causes a sponsor bank to demand clearer role allocation, audit trails, and reusable evidence from its fintech partners. [7][9][20][27][35]

Willingness to pay

Buyers already absorb this cost through delayed launches, manual analyst time, outside-counsel work, and enterprise verification tools. Lithic says wrong bank-partner choices can delay launches by months, Middesk says manual KYB slows approvals and drives drop-off, and Sumsub publicly prices paid compliance plans while reserving business verification for enterprise tiers. That supports a meaningful annual software budget for teams facing recurring partner reviews. [17][22][23][24]

Category dynamics

Growth signal 11.1% CAGR

Validation signals

• Tangos' seed round and live deployments show buyers will evaluate autonomous, evidence-backed financial-crime investigations today.
• Sponsor banks and fintechs are already co-buying or co-designing transaction-monitoring and oversight tooling, which supports a joint review-workflow wedge.
• Verification vendors now market UBO checks, questionnaires, audit trails, and AI-driven business verification, confirming demand for automation even if their focus is onboarding rather than recurring EDD reuse.

Regulatory & technical constraints

• Banks cannot outsource accountability for third-party arrangements; any tool must preserve auditable lifecycle controls and role clarity.
• Legal-entity beneficial-ownership verification still requires written procedures and risk-based identity verification rather than simple registry lookup.
• UK PSC data and true UBO evidence can diverge, so the product must support independent-source verification and chain unwrapping.
• AI outputs in compliance workflows need risk assessment, human review, and provenance if they are to survive internal or regulatory scrutiny.

Middesk and Sumsub own business-verification flows, Kyckr and LSEG sell external-company and screening data, Tangos and Hawk automate institution-side investigations, and Moody's sits higher in the KYC/AML stack. The gap is a counterparty-owned evidence system that can reuse internal corporate records and prior answers across recurring bank or network templates.[21][23][25][26][28][29][30]

Why incumbents do not win by default

• KYB onboarding vendors. They reduce friction at initial business onboarding, but their center of gravity is pass/fail verification rather than long-lived, counterparty-specific EDD packets.
• Data and screening incumbents. They provide broad external coverage and reliable lists, but they do not own the internal document graph, approval history, or partner-specific narrative assembly the fintech still has to manage.
• Bank-side investigation platforms. They automate investigators' work and case files inside institutions, but they are not optimized for the company being investigated to maintain a portable evidence dossier across many counterparties.
• Advisory and sponsor-bank infrastructure. Banks, counsel, and consultants can define control expectations and review programs, but recurring evidence maintenance still wants software instead of bespoke spreadsheet and memo work.

Counterparty EDD Autopilot sells to money-movement fintechs that must repeatedly prove ownership, control, licensing, and source of funds to sponsor banks, correspondents, and card networks. The beachhead is U.S. and UK remittance, payroll, and card-program fintechs with 3-10 counterparties and frequent annual reviews or corridor launches, because these teams bear the highest cost of rebuilding evidence packs from shared drives, cap tables, and counsel memos. The initial product is a living evidence graph plus export layer that ingests internal entity records and external risk data, then produces bank-specific cited beneficial-ownership and source-of-funds files with reviewer sign-off and change logs. The why-now is credible because Tangos and adjacent vendors show evidence-backed AI workflows are now being commercialized in fincrime, while bank-fintech supervision is increasing the need for audit-ready counterparty packets. The go-to-market system is a paid design-partner motion triggered by an upcoming annual EDD refresh or change-of-control event, sold to the CCO, GC, or COO on avoided analyst and counsel time plus faster partner approvals. The strategic choice is to win one narrow workflow, first-pass bank-review packets, before expanding into continuous KYB monitoring, bank-side shared review workspaces, or broader AML investigations. The biggest disconfirming risk is whether sponsor banks will accept fintech-generated evidence packs as first-pass input; if they still force full manual re-keying, the product becomes a productivity tool with weaker pricing power and a smaller market. Market sizing, ROI, and buyer-budget ownership are still estimate-driven because the sources do not disclose named customers, quantified time savings, or procurement data, so the first 6-12 months must validate acceptance, review frequency, and willingness to pay directly.

Problem

• Sponsor banks and networks reopen diligence whenever an annual review, corridor launch, ownership change, or new partner relationship occurs, forcing compliance teams to rebuild beneficial-ownership and source-of-funds files from fragmented internal records.
• Existing KYB, screening, and investigation tools surface external risk data or investigator workflows, but they do not maintain a reusable counterparty-owned evidence graph or partner-specific answer pack.
• Slow or inconsistent responses can delay launches, strain sponsor-bank relationships, and increase outside-counsel spend, yet the current sources do not quantify rejection rates or time saved.

Solution

• Build a living evidence graph across cap-table records, entity charts, board materials, licensing documents, prior questionnaires, and external risk sources, with every assertion linked to source evidence.
• Generate sponsor-bank- and network-specific EDD packets, beneficial-ownership maps, and source-of-funds narratives with human sign-off, stale-evidence alerts, and change logs.
• Expand from one live review workflow into continuous change monitoring and multi-counterparty reuse only after first-pass acceptance is proven.

Why we win

• We are centered on the investigated counterparty's recurring evidence-maintenance problem rather than generic onboarding or bank-side investigations, so reuse across many counterparties is the core workflow rather than an add-on.
• A template library, follow-up-question history, and acceptance analytics can compound into proprietary knowledge of what evidence clears which sponsor banks and networks fastest.
• Human-reviewed cited exports and private deployment options fit the audit, security, and model-governance constraints that slow broader AI adoption in compliance.

Milestones

flowchart LR
  Wedge[Annual EDD refresh at one fintech] --> MVP[Cited evidence graph and export pack]
  MVP --> Proof[Faster submission and fewer follow-up questions]
  Proof --> Expansion[More counterparties per logo and bank-side workspace]

Founding team

Experiment roadmap

Risk assessment

What must be true

• Target customers experience at least 3 recurring annual or trigger-based counterparty reviews per entity each year.
• Sponsor banks or networks will use a cited exported packet as real first-pass input rather than treating it as prep work only.
• At least 70% of required ownership and source-of-funds evidence is already digitized or can be digitized quickly at target customers.
• Buyers will pay at least $60k ARR once one live review proves faster submission and lower follow-up burden.
• Template reuse and acceptance analytics improve enough across counterparties to create defensibility before KYB incumbents bundle a similar feature.

Open diligence questions

• How many annual or trigger-based counterparty reviews does a typical beachhead fintech complete per entity each year?
• What percentage of required evidence currently lives in structured systems versus counsel memos, email attachments, and shared drives?
• Will sponsor banks accept exported packets, or will they still require full portal or questionnaire re-entry?
• Which executive actually owns budget first, the CCO, GC, COO, or a sponsor-bank relationship lead?
• How much overlap exists across sponsor-bank and network templates, and where does fragmentation make reuse weak?

Model sanity

• Revenue engine. Base revenue is driven by moving from 3 paid design-partner accounts at Y1 exit to 30 paid review-pack subscriptions by Q4Y3 while annualized value per account approaches about $98K.
• Must go right. Sponsor banks must treat cited exported packets as real first-pass input so pilots convert after one live review and expansions inside each logo follow quickly.
• Model breaks if. If sales cycles stretch toward 150 days or gross margin stalls below 68%, the downside case pushes the cash floor toward roughly $0.1M before the company has clear seed proof.
• Next-round proof. The seed story is 6-8 production logos, 10 reusable sponsor-bank templates, and evidence that accepted packets reduce submission time and follow-up burden enough to justify broader rollout.

Scenarios

Sensitivity

flowchart LR
  TargetAccounts[Money-movement fintechs] --> DesignPartners[Paid design partners]
  DesignPartners --> AcceptedPackets[Accepted live review packets]
  AcceptedPackets --> ProductionAccounts[Production review-pack subscriptions]
  ProductionAccounts --> Expansion[More counterparties and monitored entities]
  Expansion --> Revenue[Revenue]
  Revenue --> GrossProfit[Gross profit]
  GrossProfit --> Cash[Cash and runway]

Flags: customersEop counts paid covered-entity subscriptions and review packs, so unique production logos are lower than the headline paid-account count. · The base case assumes one GTM lead plus referral channels can drive enough within-logo expansion to reach 30 paid accounts by Q4Y3. · Gross margin only reaches the 72% target if at least 70% of customer evidence is already digitized; otherwise onboarding becomes services-heavy and EBITDA compresses quickly. · The model still depends on sponsor-bank acceptance of fintech-generated packets as first-pass input; if banks force full re-keying, pricing power and expansion both weaken. · A $2.3M pre-seed leaves the cash low point around $0.52M, so a materially slower conversion cycle would force an earlier seed process.

• Counterparty format fragmentation. Banks and networks often use bespoke questionnaires and may resist a standardized packet from a fintech vendor. Mitigation: Start with export layers for the most common partner templates and prove faster first-pass acceptance with design partners on both sides of a review.
• Evidence freshness decay. Ownership and source-of-funds files become unsafe quickly if cap tables, entities, or corridor exposure change without being captured. Mitigation: Integrate with cap-table, entity-management, and internal approval systems, then force change attestations and stale-document alerts before any packet ships.
• Incumbent bundling. KYC data vendors, onboarding tools, or outside counsel could add lightweight dossier-generation and reduce willingness to buy a new standalone product. Mitigation: Win on reusable multi-counterparty workflows, counterparty-specific acceptance data, and a living evidence graph that spans internal records plus external risk data.