evaluator-optimizer
Credit evaluation agent
Reviewers spend their day cross-checking loan documents by eye instead of deciding.
See how we build itAI agents · Financial services
AI agents for financial services in Malaysia & Singapore
Banking, lending and insurance run on documents, verification and risk that is priced to the cent — and most of the work is still done by hand. We design and build custom AI agents on Claude, human-in-the-loop, that cut the manual document and verification grind while a person keeps every decision. You get the throughput without giving up control or the audit trail.
The economics of financial services
Thin margins, priced to risk
Net interest margins and claims ratios leave little room for slack. Every hour an analyst spends keying data off a payslip, reconciling a statement or re-checking a claim eats directly into the spread. The unit economics reward speed and accuracy at scale, yet the processing that decides both is still overwhelmingly manual and expensive to grow.
Compliance is the cost centre
Obligations from BNM and MAS — AML, KYC, suitability, record-keeping — are non-negotiable and audited. Verifying an IC or NRIC, matching payslips to bank statements and screening names by hand is slow, inconsistent between officers, and prone to the exact errors regulators penalise. The control has to be right every time, not on average.
Document-intensive by nature
Loan files, claims packs, policy schedules, board resolutions and contracts arrive as PDFs, scans and photos in mixed languages. The value — and the risk — lives in cross-checking them: does the income support the limit, does the claim match the policy, do the figures reconcile. Done by hand, that is where the hours and the mistakes accumulate.
Disclosure and governance under scrutiny
Listed banks and insurers answer to Bursa Malaysia and SGX for what they disclose and when. Announcements, results commentary and investor responses must be consistent, accurate and defensible after the fact. Producing them under deadline while keeping every version auditable is a governance load that manual drafting and review handle poorly.
Where agents pay off in financial services
We map agents to the document- and verification-heavy work that repeats daily: credit evaluation, KYC onboarding, insurance claims, invoice matching, contract review and corporate communications. Each links to a worked example with the workflow, model choice and a cost estimate.
routing
Onboarding & KYC agent
Check that identity documents, proof of address and application details are consistent.
See how we build it
orchestrator-workers
Insurance claims agent
Match a claim against the policy, the report and the receipts — and flag what doesn't add up.
See how we build it
prompt chaining
Invoice matching agent
Three-way match of purchase order, delivery order and invoice before a payment goes out.
See how we build it
evaluator-optimizer
Contract review agent
Compare a signed contract against the agreed template and surface the clauses that changed.
See how we build it
evaluator-optimizer
Corporate communications consistency agent
Turn one approved message into on-brand, fact-consistent versions in every language — checked, flagged, and ready for sign-off.
See how we build itWhy agents fit this sector
Financial services work is structured, rule-bound and evidence-driven — which is exactly where a well-scoped agent earns its keep. The point is not to replace judgement but to do the reading, cross-referencing and drafting, then hand a human a clear recommendation with its receipts.
- Evidenced decisions: every recommendation cites the source document, figure and page it came from, so a reviewer can verify in seconds rather than re-read the file.
- Human-in-the-loop sign-off: the agent prepares and proposes; a qualified officer approves. Lending, claims and disclosure decisions stay with your people.
- PDPA- and PDPC-aligned data handling: we scope what data the agent sees, where it is processed and how long it is retained, built to your data-protection posture.
- Auditable trails and evals before go-live: every step is logged, and we gate launch behind Agent GPA evals against a golden set and a human baseline — no silent rollouts.
Why Anchor Sprint
We are a Malaysian AI agency and a member of the Anthropic Claude Partner Network. We build on the Claude Agent SDK and MCP, so agents connect to your real systems and documents rather than living in a chat box. We publish a directory of worked use cases and a cost calculator so you can see the shape of a build before you commit — and we will tell you plainly when an off-the-shelf Claude seat already solves the problem and a custom agent is not worth it.
Common questions
- Is it compliant with BNM/MAS and PDPA/PDPC?
- We design to your obligations, not around them. Agents run human-in-the-loop so a qualified officer owns every regulated decision, every step is logged for audit, and data handling is scoped to your PDPA/PDPC posture — what the agent sees, where it is processed and how long it is retained. The agent supports your BNM and MAS controls; it does not replace your compliance function or its accountability.
- Does the agent make lending or claims decisions?
- No. The agent reads the file, cross-checks the evidence and prepares a recommendation with its citations — but a person approves or declines. Credit and claims decisions stay with your officers and your policy. This keeps you inside regulatory expectations and means the agent is a force multiplier on judgement, not a substitute for it.
- Can it handle Bahasa Malaysia, English and Chinese documents?
- Yes. Claude reads Bahasa Malaysia, English and Chinese, so mixed-language loan files, claims packs and contracts — the norm in Malaysia and Singapore — are handled without a separate translation step. We tune extraction to your document types, including scans and photos, and validate accuracy per language before go-live.
- How do you prove it's accurate before go-live?
- We build an Agent GPA eval suite: a golden set of representative documents with known-correct answers, scored against a human baseline. We only launch when the agent clears the accuracy and error thresholds you agree to, and we keep those evals running so quality is measured continuously, not assumed. If it cannot meet the bar, we say so rather than ship it.
Drowning in document checks?
Tell us your volumes and the documents your team wades through, and we will say honestly whether an agent is worth building — or whether an off-the-shelf Claude seat already covers it.