Build it so the decision trail survives the examination
AI for banks and insurers built inside model risk governance: claims, onboarding, crime triage and the evidence a supervisor will ask for.
Model risk
We build to the model risk framework you already run — inventory, tiering, conceptual soundness, outcomes analysis, monitoring — and produce the validation pack as a by-product of the build. Assembling it retrospectively is where programmes die.
Claims
Türkiye Sigorta runs notification of loss, document capture, policy verification and agent matching on WhatsApp. Indemnity and declinature stay with the adjuster.
Türkiye Sigorta
50%
faster policy approval and agent matching on the published claims deployment
Claims cost
30%
lower claims operations cost on the same Türkiye Sigorta deployment
Financial crime
Analysts drown in alerts nobody can clear. We assemble the case file and draft the narrative with every claim cited, and leave escalation and reporting to the analyst.
Integration
Change data capture where currency matters, entitlements mirrored from the source system, idempotent write-back, and residency built to the strictest applicable regime.
Model in production
Core systems
Model risk
Regulation
Data protection
Channels
3–4 weeks
Which journeys are automatable inside your framework, what tier each lands in, and the evidence each one would require.
Use case tiering, evidence map, residency constraints, costed shortlist
12–20 weeks
One journey built end to end with the validation pack produced alongside it and outcomes analysis against a measured baseline.
Working journey, validation pack, challenger baseline, fairness test results
Ongoing
Rollout across business lines, operation under an SLA with drift monitoring, and support through supervisory examinations.
SLA operation, monitoring plan, periodic revalidation, audit support
By producing the artefacts your framework already expects: an inventory entry and tier, conceptual soundness, lineage from source system to output, a challenger baseline on your historic cases, outcomes analysis, drift monitoring and a tested fallback. We write them during the build, in the form validation reviews.
Yes. We deploy in-country on your infrastructure or an approved regional cloud, and where hosted APIs are excluded we run open-weight models on hardware you control. Across the Gulf, Türkiye and Europe we design to the strictest applicable regime. We have worked with Doha Bank, BNP Paribas and the NYSE.
When the constraint is data rather than intelligence. If policy data lives in three systems that disagree, or entitlements are not modelled well enough to say who may see which account, an assistant will surface the inconsistency to customers at speed. Do the data engineering first, and say so before the examination.
Regulator, budget, deadline, legacy core, a board that has been burned once already. Tell us what you are working around.
