FIG. 01 — FINTECH OPERATIONS
Tuesday standup. The growth dashboard is up on the shared screen — signups up and to the right, the board is thrilled. You’re refreshing the other chart: a KYB queue at nine days and climbing, two analysts, and Reg E deadlines living in a spreadsheet.
The board sees the growth chart. You see the other one — the queue that grows with it.
Signups up and to the right; KYB backlog right behind them. We build the AI your roadmap promised — KYC review, disputes, recon, support — production-grade, audit-ready, live in weeks. The controls ship with the code.
FIG. 02 — WHERE THE BACKLOG LIVES
Five queues growing faster than headcount. You didn’t build them — volume did.
Every one of these scales with signups. None of them scales with your team. Here’s where the backlog lives:
KYB queue keeps growing
Document checks and sanctions/PEP screening scale with signups; your two analysts don’t. False positives eat the day while clean applicants drop off mid-onboarding.
Reg E clocks in spreadsheets
Dispute intake, provisional-credit deadlines, and evidence assembly live in a tracker somebody updates by hand. One missed 10-business-day clock is a finding, not an inconvenience.
Recon breaks eat the close
Daily ledger-vs-processor breaks get investigated one by one, mostly the same known patterns. Month-end close stretches into week two.
Alert backlog is context work
Every AML alert means re-gathering the same account history, counterparties, and prior dispositions. The backlog itself becomes something to explain to your BSA officer.
Tier-1 can’t see accounts
Support agents lack safe, scoped access to account data. Tickets escalate for questions the system could answer, and regulated topics get answered from memory.
FIG. 03 — WHAT CHANGES
Five systems, built inside your control framework — five before-and-afters.
KYC Document Agent
Today: analysts drown in false positives while clean applicants wait. After: the agent validates documents, summarizes screening hits with source links, and drafts the decision file — your analysts decide, same day.
Dispute Management System
Today: federal deadlines live in a spreadsheet. After: Reg E timelines are hard system constraints with escalation — intake, representment evidence, and outcome letters drafted for review. A clock cannot silently pass.
Recon-Break Triage Agent
Today: the same known break patterns, investigated by hand, every day. After: known patterns auto-cleared with full logging before your team sits down; true exceptions arrive packaged with investigation context.
AML Alert Copilot
Today: every alert starts with an hour of context-gathering. After: account history, counterparties, and prior dispositions arrive as a structured narrative. The disposition stays human — the copilot kills the gathering hour.
Scoped Support Agent
Today: tier-1 escalates what the system could answer, and regulated topics get answered from memory. After: scoped, audited read access; drafts on regulated topics held for human approval; clean escalation with full context.
TARGETS ARE TARGETS — SET IN THE OMEGA STATEMENT, MEASURED FROM WEEK 1. NOT CLAIMED RESULTS.
FIG. 04 — THE OMEGA METHOD, UNDER AUDIT CONDITIONS
You’ll see it graded on your own cases before you pay to build it.
- WEEK 0Endgame
Your Omega Statement, signed: e.g. “90% of clean applications decisioned same-day; analysts touch only true exceptions.”
- WEEK 1▪ DEPLOYEvidence + Blueprint
We run a sample of your real (redacted) case files through the agent and measure precision. Kill/go verdict, then the Build Blueprint — including the model-risk documentation your auditors will ask for.
- WEEK 2▪ DEPLOYBuild
First Friday deploy: decision files drafting on historical applications, screening provider wired in, sandbox data.
- WEEK 3▪ DEPLOYBuild
Second Friday deploy: audit trails, human-in-the-loop gates, exception queues — your analysts running the parallel queue on live volume.
- WEEK 4▪ DEPLOYBuild + Launch
Cutover with controls sign-off, monitoring, and the Launch Runway: go-live checklist, metrics dashboard, compliance documentation pack delivered.
Working software every Friday — and the paper trail your next exam expects.
FIG. 05 — THE ANSWERS YOUR AUDITOR WILL ASK FOR, ALREADY WRITTEN
Your auditors are our spec. The documentation ships with the build.
You shouldn’t have to reverse-engineer your controls after the request letter arrives. Every fintech build ships inside these rules — in writing, from day one:
- [✓]SOC2-friendly architecture. Role-based access, encryption, audit logging, environment isolation — built to SOC2-aligned practice. We claim no certification we don’t hold; we build so your audit passes.
- [✓]PCI-DSS scoping respected. Card data stays out of AI paths entirely. The agents work from tokens and processor references, never PANs.
- [✓]GLBA safeguards honored. Customer financial data is access-controlled, logged, and never used to train shared models.
- [✓]Reg E timelines are system constraints. Provisional-credit and investigation clocks are encoded as hard deadlines with escalation — not calendar reminders.
- [✓]Model-risk documentation delivered. Model inventory, validation notes, and human-in-the-loop points ship as part of the Build Blueprint — exam-ready, not reverse-engineered later.
- [✓]Full audit trails on every agent action. Every read, draft, and decision support step is logged and exportable.
COMPLIANCE COMMITMENTS REVIEWED BY ENGINEERING LEAD BEFORE PUBLISH
FIG. 06 — A FIRST SPRINT, WORKED
A first Sprint for a shop like yours, worked end to end.
The situation
Picture a Series A payments startup: 2 compliance analysts, a 9-day KYB backlog, clean businesses stuck behind false positives, onboarding drop-off climbing with the queue.
The Omega Statement
“90% of clean applications decisioned same-day, analysts touch only true exceptions.”
What shipped
Week 1, their real (redacted) cases go through the pipeline and precision is measured — before any build commitment. Four Fridays later, the KYB agent is live: document validation, screening-hit summaries with source links, and a decision file the analyst signs. Exceptions route to humans. Everything logs.
Metrics tracked
- TIME-TO-DECISION
- BACKLOG DEPTH
- ANALYST THROUGHPUT
- FALSE-POSITIVE HANDLING TIME
This is a worked example of a first Sprint — illustrative, not a client result. It’s stamped TEMPLATE until a real engagement replaces it.
FIG. 07 — THE PLAN AND THE PRICE
Three steps. Fixed price. Published.
DISCOVERY FEE CREDITED 100% AGAINST THE SPRINT
FIG. 08 — THE QUESTIONS YOUR AUDITORS WILL ASK
Straight answers, before the meeting.
Where does customer financial data live, and what touches the model?
Data stays in your cloud tenancy with role-based access and full audit logging; nothing trains shared models. Card data never enters an AI path at all — agents work from tokens and processor references, keeping your PCI-DSS scope unchanged. The data-flow diagram ships in the Build Blueprint before we write code.
How does this survive our next exam?
Because the exam is part of the spec. You get a model inventory, validation notes, documented human-in-the-loop points, and exportable audit trails on every agent action — delivered with the build, not reconstructed after the request letter arrives. Decisions that matter to a regulator always terminate with a human.
Reg E deadlines are non-negotiable. How are they handled?
As hard system constraints. Regulation E requires investigation within 10 business days of a dispute notice — or provisional credit while you take longer — so the dispute system encodes those clocks with escalation, and a deadline cannot silently pass. The spreadsheet tracker retires.
What if we shouldn’t build this at all?
Then the Evidence Ledger says so and you stop at $7,500. About the most expensive thing in fintech is a half-built compliance tool your auditors have questions about — the kill verdict exists to prevent it. If you go, the Discovery fee credits 100% against the Sprint.
Is AI making compliance decisions?
No. The agents assemble, summarize, and draft — with sources linked. Every disposition, decision file, and outcome letter terminates with a human, and that boundary is documented as a control, not a preference. AI does the fast 70%; senior engineers own architecture, security, and the last mile.
A question we didn’t answer? Ask it in a Product Session.
FIG. Ω — THE END STATE
The workflow, the controls, and the audit trail — scoped together.
Book a Product Session. We’ll scope the workflow, the controls, and the audit trail in the same conversation — because for you they’re the same thing. You leave with a one-page scope and a fixed price.