AI for Financial services

Your regulator will ask how the machine decided. Design so you can answer.

Onboarding takes days because every document is read by hand, risk decisions live in a spreadsheet nobody can explain, and the same product questions arrive all day. AI fixes each of those, and in a regulated business the design has to be able to say how it decided.

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controls tested withBe Secure

Where AI pays first

Three things AI does in financial services before anything else

Document AI

Onboarding and KYC document intelligence

Identity documents, proof of address, bank statements and application forms read, cross-checked and summarised for a person to verify. Onboarding drops from days to the time it takes a human to review the exceptions, and every check is recorded.

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Predictive AI

Risk scoring with explanations a person can read

Applications, claims or accounts scored and prioritised from your own history, with the factors that drove each score written in plain language. The adviser or underwriter makes the decision; the model shows its working so the decision can be defended.

See Predictive AI

AI Agents

A customer-service agent that knows your products and nothing else

Product questions, statement requests and process queries answered from your approved material only. The agent does not give advice, says so, and hands the customer to an adviser the moment the conversation needs one.

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Start here

AI Governance

Explainability, record-keeping and human oversight have to be in the design before the first sketch, because your regulator will ask for them after the fact. Governance first, then the build.

AI without the risk. Policy, controls and oversight in writing.

Governance in this sector. Every automated decision is explainable in plain language, every action leaves a record you could put in front of a regulator, and a person approves anything with a consequence for a customer. We design and report against ISO/IEC 42001 and the NIST AI Risk Management Framework, we say “aligned” rather than “certified”, and we do not cite an obligation we cannot show you.

How AI Governance works See the packages

The six stages for financial services

1 Discover. where AI already is
2 Define. where it pays
3 Design. the architecture
4 Deploy. into real workflows
5 Defend. govern and control
6 Develop. measure and expand

Questions

What financial services leaders ask us

Can an AI model make lending or underwriting decisions?

It can score, prioritise and recommend. Whether it decides is a governance choice, and for anything with a consequence for a customer we design a person into the decision. The model’s reasoning is recorded either way, so the decision can be reviewed later.

How do we stop the agent giving financial advice?

By limiting what it may know and what it may say, and by testing that limit before it goes live. The agent answers from approved product material, recognises advice-shaped questions, and hands them to a licensed person. Be Secure tests the limit as part of the build.

What records does a regulator expect from AI?

Who asked, what the AI saw, what it produced, who approved it, and what changed. That is the audit layer of the architecture, and it is designed in from the start rather than bolted on when someone asks.

Other industries

How AI pays elsewhere

Professional servicesLaw, accounting and consulting firms.ConstructionBuilders, subcontractors and project offices.HealthcarePractices, allied health and aged care.RetailStores, online shops and distributors.ManufacturingProducers, processors and fabricators.Financial servicesAdvisers, lenders and insurers.Small businessUnder fifty people.

Faster onboarding, defensible decisions, and a record of every one.

Start with governance. Thirty minutes with an AI architect, then a written note on what we would design first.

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