GCC sovereign bank deploys AI underwriting in…

9 days → 14 min

Median loan decision

−47 pts

Digital drop-off reduction

USD 38M

Annualised incremental originations

11 months

Kickoff to first regulated decision

Client

Leading GCC Bank

Sector

Banking & Financial Services

Duration

11 months

Team

34 specialists

01 · The challenge

Problem

Personal-loan decisioning averaged 9 working days. Digital channel drop-off exceeded 60%, and the risk committee lacked an explainable view of model behaviour. Regulatory pressure was growing on opaque scorecards.

02 · How we delivered

Solution

Joint squads with the bank designed and built an end-to-end AI underwriting platform on AWS — feature store, decisioning service, model-risk workbench, and a regulator-facing explainability layer. Live-parallel run for 9 weeks before cutover.

03 · Outcome

Impact

Decision time compressed from 9 days to 14 minutes. Digital drop-off down 47 percentage points. Annualised incremental originations of USD 38M. Regulator passed the platform first time and named it as an exemplar to peers.

How we delivered

Programme phases.

Five phases. One accountable team. Every phase had a named decision point and a measurable outcome.

Discovery & alignment

2–3 weeks

Workshops with the Leading GCC Bank executive team, baseline metrics, target outcome tree, programme governance set up.

Design & architecture

4–6 weeks

Reference architecture, security blueprint, joint squad model agreed. Data model and integration contracts published.

Build & live-parallel

Q2 onwards

Vertical slice built and run live-parallel against the existing system. Continuous integration, daily deploys, weekly business demos.

Cutover & scale

Mid-programme

Phased cutover, audit-aligned reconciliation, scaling out of squads, capability transfer to Leading GCC Bank teams.

Run & continuous improve

Steady state

Managed run with named SLOs, quarterly value reviews, and a 15% optimisation budget reserved for improvement work.

Engineering view

Architecture overview.

Foundations

Cloud landing zone, identity, network, security baseline. Data fabric with lineage-by-default. Audit-grade observability stack from day one.

Application & integration

Domain-aligned microservices behind a published API surface. Event-driven core with CDC into the data fabric. Live-parallel capability built in, not bolted on.

Trust & governance

RBAC, audit logs, lineage, policy-as-code. Model risk records for every production model. Compliance posture on the executive dashboard, not in a quarterly slide.

Built on

Technology stack.

Production-grade choices, defended by track record. The stack is one engineering decision among many — but a load-bearing one.

AWS Snowflake Tecton Anthropic Claude Datadog Terraform

Trust by design

Governance & assurance.

Programme assurance

Independent assurance reviews at each phase gate. Findings tracked in a single risk register with named owners and remediation deadlines.

Security & data

ISO 27001, SOC 2 Type II controls applied throughout. Data lineage captured by default; sensitive data tokenised at the edge.

Audit-grade evidence

Every change tracked; every release reproducible. Audit packs assembled automatically for internal and external review.

Continuous compliance

Policy-as-code scans on every commit. Compliance posture surfaced on the executive dashboard, not in a quarterly report.

A 9-day decision became a 14-minute decision. The regulator passed it first time — that is unusual.

C Chief Risk Officer · Leading GCC bank

What we learnt

Three things we would do again.

01

11 months from kickoff to first regulated outcome — squad density and decision velocity matter more than headcount.
02

Joint squads with Leading GCC Bank engineers stayed in place after go-live. Ownership did not transfer in a hand-off — it grew in place.
03

Live-parallel for a meaningful window before cutover bought us trust. The cutover itself was a flag flip, not a war room.

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GCC sovereign bank deploys AI underwriting in 11 months