Financial services
Banks and insurers do not have an AI ideas problem. They have an assurance problem: every use case has to clear model risk, data protection and audit before it reaches a customer. We design for that review from day one rather than retrofitting controls after a successful demo.
Licensed institutions and intermediaries
Banks, insurers, takaful operators, asset managers and licensed intermediaries — organisations where a wrong answer to a customer is a reportable event, not a support ticket.
You will recognise yourself if
- A second line of defence that can stop any deployment
- Product and policy documents that change faster than staff can read them
- An obligation to reconstruct, years later, why a customer was told something
What actually hurts
The policy is current. The answer at the counter is not.
Product terms, eligibility rules and fee schedules are revised centrally and absorbed unevenly. Front-line staff fall back on what they learned at induction, and the gap between the approved document and the spoken answer is where complaints are born.
Pilots die at second-line review, after they are built.
A demo impresses the business, then model risk asks how the answer was derived, data protection asks where the content went, and audit asks for the trail. With no answers, twelve months of work is shelved.
Explainability is not a feature request. It is the licence.
When a customer disputes what they were told, "the model said so" is not a defence. You need the source, the version and the date — for an exchange that happened long enough ago that nobody remembers it.
What it reads.
The corpus is already written, already approved, and already the thing staff are supposed to be quoting. AIMY Expert indexes it in place.
- Product terms and policy manuals
- Regulator circulars and guidelines
- Credit and underwriting criteria
- AML/CFT and onboarding procedures
- Fee schedules and delegation matrices
- Complaint handling precedents
One question, answered
A representative exchange for this sector. Every figure and instruction is traced back to the document it came from — including the revision and the date it took effect.
Customer is 62, retired, no fixed income. Is she eligible for the flexi home financing product?
Not under the standard tier. Applicants above 60 at application require a guarantor or a pledged deposit covering 12 months of instalments.1 Retirement income counts as income only where it is documented for the preceding 6 months.2 Maximum tenure is capped so financing ends by age 70.1
Illustration only. This exchange is a written example of how AIMY Expert behaves — not a recording of a live system, and not a claim about any real organisation's data.
What changes, and what we would measure.
The figures below are what a deployment is scoped against, not audited results from your organisation. Each one states its basis, because a number without one is marketing.
Same answer
at every branch and every counter
Basis: consequence of one governed index replacing local interpretation
100%
of answers carry a source, section and effective date
Basis: architectural guarantee — an answer without a citation is not returned
Full
retrieval and conversation trail, exportable
Basis: logged by default in every deployment
What it means for the business
- Fewer complaints traced to inconsistent front-line answers
- Second-line review becomes a design input rather than a late veto
- New products reach the counter correctly on the day they launch
- Evidence for disputes reconstructable years after the conversation
Where the work usually starts.
Not an exhaustive list — these are the engagements that most reliably clear the value-versus-risk bar in this sector.
Policy and procedure assistant
Front-line staff get cited answers from current policy instead of guessing or escalating.
Credit and underwriting file review
Criteria and precedent retrieved alongside the file, with the decision left to the officer.
Complaints and dispute triage
Classification and drafting grounded in regulatory wording, with the human decision preserved.
Regulatory change tracking
Circulars mapped to the internal controls and procedures they affect.
Designed around the constraints, not despite them.
These requirements shape the architecture from the first design session. Retrofitting them after a successful pilot is the most common reason AI programmes in this sector never reach production.
- Model risk management sign-off (SR 11-7 style validation evidence)
- Data residency and no third-party training on customer content
- Explainability sufficient for complaint and dispute defence
- Retention and audit trails matching existing recordkeeping obligations
One organisation. Every department. This is the order.
Your organisation is in one sector, and inside it sits every department below. The platform is the same for all of them — what the sector decides is which one goes first, and that choice matters more than any model decision.
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01 Legal & Compliance Usually first
Second-line risk has to bless the platform before anything customer-facing ships. Starting here turns the blocker into the sponsor.
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02 Customer Service Then
Highest query volume and the clearest measurable baseline — branch and contact-centre policy lookups.
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03 Finance & Accounting Then
Approval thresholds and delegation limits, read by people outside Finance.
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04 Administration Fast follow
Low risk, high volume. Usually live within weeks of the platform existing.
And then the rest of the organisation.
These departments exist in your organisation too. Once the platform is live and reviewed, each one is a scope and an evaluation set — not another procurement cycle.
What we would deploy.
If the constraints above rule out anything leaving your premises, the same platform ships on hardware you own.
Talk to someone who has shipped in financial services.
A first call is a working session, not a pitch. Bring your constraint list and we will tell you which parts are genuinely hard.