Recommendation & Personalisation for Financial Services

Orqent Labs builds recommendation systems evaluated by controlled experiment, reported against revenue or engagement rather than a leaderboard metric.

In financial services, every automated decision must be explainable and reproducible months after the fact. That single fact reshapes how recommendation & personalisation has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is regulatory report assembly, usually integrated against SAP and Oracle financials. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

Multi-model by default, so a provider outage is a routing decision rather than an incident. We hand over with runbooks, tests and a team that knows how it works, not a dependency.