Use case selection
A short list of use cases ranked by value, data readiness and risk, each with a baseline to measure it against.
Industry context
AI solutions in financial services
Hosn Al Tomoh takes AI in financial services into production with model risk documentation, bias and fairness checks, and private inference patterns that internal audit and regulators can review.
Model risk teams need lineage from training data through deployment gates, not ad hoc notebooks. We build evaluation harnesses, rollback criteria, and a clear owner for each model before it touches customer-facing decisions.
We align retrieval and agent patterns to data classification, so prompts and tools do not expose cross-border or cross-entity data that your legal team has not approved.
Inference cost is budgeted alongside accuracy, so leadership sees unit economics and risk trade-offs in the same steering forum.
What the work covers
We design, deliver and stay until operation is stable, with evidence your procurement and risk teams can rely on.
Evaluation and human review
Test sets, accuracy and bias checks, and review steps for outputs that affect people, agreed before launch.
Production operation
Private hosting or a managed service, monitoring for drift and cost, and a rollback route if a model stops performing.
Regulatory landscape
We map delivery evidence to the expectations of the regulator you answer to: the Central Bank of the UAE or, for capital market firms, the Securities and Commodities Authority; in Saudi Arabia, the Saudi Central Bank (SAMA), including its Cyber Security Framework, or the Capital Market Authority.
Data preparation
Training and test data sourced, labelled and classified, with personal data handled under the applicable data protection law.
Cost and usage control
Usage limits, cost reporting for each use case and a regular review of whether each model still earns its place.
Signs you are ready to start
An AI use case is ready to start when there is a process to compare against, data you are allowed to use and someone who will act on the results.
- A risk or compliance sponsor has agreed to review the design before build starts.
- Each candidate use case has a named business owner and a measurable baseline from the current process.
- Privacy or legal has cleared the data for each use case for this purpose.
Plan AI solutions in financial services
Share your current systems, compliance themes and timeline. We will return a phased plan, a staffing model and a risk register for your stakeholders to review.