How to Design Agentic AI Workflows for Banking in Dubai
A practical design for commercial customer onboarding and periodic review using bounded AI agents, explicit controls, reliable evidence and staged deployment for Dubai banking.
Where agentic workflows fit in Dubai banking
A bank must reconcile identity, ownership, business activity, expected transactions, sanctions and risk evidence across documents and systems before an authorised employee can approve or escalate the relationship. An agentic workflow is useful where the next step depends on evidence that cannot be handled economically through one fixed route. Stable rules, approval limits and mandatory controls should remain deterministic.
A strong starting workflow: commercial customer onboarding and periodic review
The workflow should receive the application, verify identity and beneficial ownership, extract and reconcile documents, retrieve the applicable policy, identify missing or conflicting evidence, prepare the risk case, obtain authorised approval and schedule review. This is an application design, not a claim about a completed client engagement. The business should narrow the first pilot to one population, route and accountable owner.
Choose the architecture deliberately
A deterministic workflow should control required checks and approval limits. A document agent can assemble evidence, a relationship agent can request missing information and a risk agent can compare the case with policy. A manager should present one traceable case pack rather than allow specialists to act independently on the account.
Prepare the evidence and knowledge
The workflow needs customer and beneficial-owner records, trade licences, account activity, risk policy, sanctions results, analyst decisions and later account outcomes. Each source should have an owner, definition, effective date and access rule. The workflow must distinguish retrieved evidence, deterministic calculation, model inference and human judgement.
Keep authority and controls visible
The workflow must not approve, decline, restrict or report a customer without the authorised banking control. Source evidence, policy version and human decision should remain visible.
Test the complete trajectory
Use historical and constructed cases covering normal work, missing information, conflicting evidence, unusual combinations, tool failure and attempts to bypass policy. Test retrieval, routing, tool calls, approvals and downstream effects. Compare the agentic design with the present process and with a simpler controlled workflow.
Deploy in stages
Begin with historical replay and shadow operation. Move to restricted production with limited cases and actions, then expand only when evidence supports the current boundary. Log source versions, handoffs, tools, approvals and final outcomes. Maintain a manual route and tested rollback.
Measure operating value
Useful measures include complete applications at first review, preparation time, false escalation, reviewer correction, policy compliance and later risk outcomes. Report performance by route and material subgroup rather than relying on one average. Include model use, integration, human review, monitoring and incident costs in the value case.
How Marketways approaches the design
Marketways maps the current work, selects the least complex suitable architecture, defines data and tool contracts, designs human authority and evaluates the complete workflow. The work connects Agentic AI Design and Deployment with Process and Workflow Analysis and Redesign and AI and Model Risk.