Technical defensibility · regulated finance
We design, build, and assure the controls that carry the risk — traceable by design
Four lines, and they overlap on purpose. We write and assure fraud and AML detection rules; we design, build and deploy the AI and automation the decisions run on — and redesign the process around them; we build the models and controls those decisions rest on; and we produce the returns that report the result. A technical discipline grounded in how banks run detection and how regulated teams ship automation, extended to AI governance and cybersecurity. So when the FCA, the Financial Ombudsman, or a court asks, there is working to show.
Fraud & AML
Design, tune, and prove fraud and AML detection rules.
Since mandatory APP-fraud reimbursement, FCA-regulated firms must show their detection rules are adequate and defensible. The service spans APP scams, AML transaction monitoring, and card, application, and mule fraud, and works both ends: we design and tune the rules, then assure them, delivering a rule-by-rule defensibility scorecard, coverage gaps mapped across recognised UK typologies, an estimated false-positive reduction, and a regulator-ready documentation pack. For independence, build and assurance stay separate engagements — we don’t mark our own homework.
Concept sequence
AI & Automation
Design, build, deploy, and prove AI and automation that survives an audit.
AI and agents increasingly make or shape the decisions a business is accountable for — and often the harder half of the job is the process around them: redesigning a workflow, deciding what stays with a person, and rebuilding the roles that sit either side of it. We do that work with AI in it or without. What we deliver either way is compliance-grade automation for regulated operations — traceable, human-overridable, and reproducible — so each decision leaves the record an auditor, a regulator, or a customer challenge will accept. Start with a fixed-scope Audit-Ready Sprint or an embedded build.
Concept sequence
Models & Controls
Build the control, and the evidence that it works.
Scorecards, affordability, forecasting and detection models, and the controls a firm is judged on whether or not a model sits underneath them. Some of that is six months of work; some of it is a spreadsheet that was always going to be a spreadsheet, and saying so is part of the job. A different signer buys this and a different regime governs it — PRA SS1/23 and CONC 5.2A rather than the PSR. The firm owns the model, the code and the development record: purpose, population, assumptions, operating boundaries, limitations and tier. And as with the rule work, we cannot build a control and be its independent validation.
Concept sequence
Regulatory Reporting
The return, and the control around the return.
The submissions a firm has to produce to a deadline, accurately, with a name against them: IFRS 9 expected credit loss, the annual financial crime return under SUP 16.23, APP scams performance data the PSR publishes and ranks, and the periodic returns that go out whether or not anything happened. Nobody buys a report because they want one — they buy it because it has to be right. We build them reconciled to source, reproducible months later, and with “not recorded” kept distinguishable from “recorded as none” the whole way through, because a blank read as a number is nought.
Concept sequence
How they fit together
Fraud & AML is a domain a firm arrives already inside. The other three are disciplines we apply to any regulated space, including that one — which is why the same piece of work is reachable through more than one of them. A fraud rule’s logic and the evidence it works is models & controls; the workflow that runs it every day, and the process redesigned around it, is AI & automation; the figure it produces for a supervisor is regulatory reporting. Most of the control and automation work we do is nowhere near financial crime.
The same standard, applied wider
The engine behind the flagships applies to any automated decision that has to be defended. We extend the same method to these areas.
AI Governance & Compliance
Ownership and oversight for the AI and automated decisions a business relies on: who is accountable, how each decision is reviewed, what evidence is retained, and what can be shown when an outcome is challenged.
Cybersecurity & Operational Resilience
The controls that move money and keep services running — proven, owned, and mapped to the regulation each implements, so operational resilience can be evidenced on demand, not just asserted.
Core lens
Risk
We trace where the controls are exposed — the rules and decisions that could not be defended if challenged today.
Core lens
Consequence
We show what each gap means in practice: reimbursement cost, complaint risk, regulatory scrutiny, or operational failure.
Core lens
Solution
We build the evidence, ownership, and documentation that hold up when a regulator, the Financial Ombudsman, or a court asks.