AI-first solutions for the work behind every account, investigation and report. Built around your bank's rules, with evidence your reviewers can check and decisions your people own.
Designed for regulated work
Compliance is not a claim added before launch. Access, approvals, records, data handling and failure procedures need to be part of the design. We turn requirements agreed with your risk and compliance teams into controls that can be tested.
Name the bank owner for each workflow and decision. Agree what AI may prepare, what must be reviewed and what it must never do.
For each obligation, define a control, an acceptance check and the evidence required. Keep unresolved questions visible.
A model, hosting region or software feature does not make a bank compliant. Legal interpretation, operating procedures and regulatory approvals remain separate responsibilities.
Four banking solutions
Build around one real banking process, not a general-purpose assistant with access to everything. Each solution has defined inputs, source-linked outputs and an accountable reviewer.
Read identity documents, compare customer and company records, identify missing evidence and prepare KYC or KYB review packs. Screening uses approved sanctions and watchlist providers, not a language model's memory.
Approval boundary. Compliance staff approve onboarding, enhanced due diligence and risk classification.
Gather related transactions, customer history and source documents for an alert. AI summarises the evidence and drafts a case narrative. Your monitoring rules remain separate from the model.
Approval boundary. Investigators decide alert outcomes. Authorised officers approve and submit suspicious activity reports.
Extract financial statements, calculate ratios with tested code and check applications against the bank's lending policy. Prepare a source-linked review for the underwriter and route servicing exceptions.
Approval boundary. Accountable staff approve lending decisions, pricing exceptions and changes affecting a customer's rights.
Match ledger and settlement records, identify unexplained differences and assemble reporting schedules from approved data. Each number links to its source and calculation.
Approval boundary. Finance staff approve adjustments and authorised reporting owners sign off submissions.
How AI fits into the process
AI handles document reading and evidence preparation from the start. Policy checks, calculations and permissions are enforced by software outside the model. Staff review the result before any consequential action.
Document permitted tasks, prohibited actions, review points and exception rules before choosing a model. AI reads and prepares; tested software applies calculations and approved business rules.
Link statements to records the reviewer is allowed to see. Preserve source versions, model versions and relevant policy references. A generated explanation is not proof of why a model produced an answer.
Give each task only the records and tools it needs. Check access at retrieval and action time. Separate preparation from approval, and never let a prompt change permissions.
Missing evidence, conflicting sources and failed checks send the case to a person. Uncertainty is not permission to continue. Disable AI assistance without blocking the bank's manual process.
Register models, owners, intended uses and dependencies. Test changes against representative cases, document limitations and require approval before release. Monitor errors and changing data after launch.
The proposed workflows do not let AI release funds, approve credit, close accounts or submit regulatory reports. Named bank staff retain these decisions and approvals.
Regulatory scope
We begin with your licence, regulator, activities and markets. These are examples of requirements to assess, not a statement that every rule applies to every bank.
Map the bank's applicable supervisory requirements to governance, customer protection, technology risk, outsourcing and AI controls. Record which rule applies, who owns the control and what evidence demonstrates it.
CBUAE AI guidanceAssess the permissions and rules that apply to the specific DFSA-authorised firm. Review systems and controls, operational risk and outsourcing with its compliance team. DFSA supervision is distinct from CBUAE supervision.
DFSA RulebookSupport the bank's obligations for customer due diligence, transaction monitoring, investigations and reporting. Keep approved screening sources, case evidence, escalation rules and accountable reporting officers in the process.
CBUAE transaction monitoring standardsWhere DIFC data protection requirements apply, assess lawful processing, access, transfers and the provisions for personal data processed through autonomous and semi-autonomous systems. Legal review determines applicability and additional duties.
DIFC Regulation 10Assess the EU AI Act where it applies. AI used to evaluate natural persons' creditworthiness or establish credit scores is listed in Annex III, with an exception for financial fraud detection. Confirm classification, role and applicable requirements before deployment.
EU AI ActRegulatory scope must be confirmed by your legal and compliance teams against current rules and supervisory guidance. We provide engineering controls and evidence, not legal advice or a certification of compliance.
Data, security and resilience
Agree the data boundary and deployment model before implementation. Controls must cover the complete workflow, including retrieval, providers, tools, logs and support access.
Choose approved cloud, private infrastructure or self-hosted models after reviewing secrecy, outsourcing, access and data-transfer requirements. A hosting region alone does not establish compliance.
Minimise and mask personal and account data where possible. Agree model-provider retention, subprocessors and contractual protections. Client data does not train general-purpose AI without express written agreement.
Record input references, model and policy versions, tool calls, reviewer, decision and timestamp. Protect logs against unauthorised changes and agree retention with legal and compliance teams.
Test timeouts, duplicate requests, unavailable providers, recovery and rollback. Keep existing transaction systems authoritative, with controlled writes and a documented manual fallback.
Test access isolation, prompt injection, document uploads, secret handling and attempted data extraction. Assess vendors and dependencies, and retest changes before release.
Test outputs for unsupported statements, unequal treatment and misleading advice. Route complaints and consequential decisions to accountable staff, with review and challenge procedures.
Connected to your existing systems
Connect core banking, document stores, customer records, screening providers and case management through approved interfaces. Read access comes first. Any write is separately scoped, validated and recorded.
Use the bank's identity provider and role model. Enforce record-level permissions and separation of duties at every integration.
Use agreed data contracts and tested calculations. Handle duplicates, stale records and mismatches explicitly rather than asking a model to resolve them.
Send evidence packs into existing queues where possible. Preserve case IDs, approvers, decision history and links back to source records.
Delivery and review
Identify the licensed entity, regulator, markets, data categories and accountable bank owners. Legal and compliance teams confirm which obligations apply.
Map the current process and integrations. Agree access, approval points, retention, failure handling and measurable acceptance criteria before implementation.
Use authorised, appropriately protected records. Test extraction accuracy, source support, calculations, access boundaries and exceptions. Document failures as well as successful results.
Compare AI-prepared work with the team's existing decisions without authorising new actions. Risk and business owners review the evidence and decide whether to proceed.
Provide the control register, evaluation results, integration documentation and operating procedures. Agree monitoring, incident response, change approval and support responsibilities.
Questions before we start
No. We build and test technical controls against requirements agreed with your bank. Compliance depends on the licensed entity, operating procedures, contracts and regulator expectations. Your legal, compliance and risk teams determine adequacy and any approvals required.
Yes. We can design a private deployment or self-hosted model where suitable. We still assess hosting, support access, subprocessors, retention, model quality and the controls needed for your specific workload.
No. Core banking, payments, ledgers and existing case systems remain authoritative. We connect through approved APIs or controlled data interfaces. New writes need validation, permissions and reconciliation.
We agree pass criteria with the bank, then test representative and difficult cases for factual accuracy, evidence support, calculation correctness, access control and escalation. We also test security attacks, provider failures and regression after model changes.
Named bank staff. Our proposed workflows prepare evidence and recommendations. Credit decisions, funds release, account closure and regulatory submissions remain under the bank's approval process.
We provide an estimate after reviewing the workflow, access approvals, systems and control requirements. We do not promise a banking production date before the bank's review and release dependencies are known.
The agreed code and configuration, control mapping, test evidence, model limitations, operating procedures and integration documentation. Ownership, access, support and licensing terms are recorded in the engagement agreement.
Start with one process
Tell us about the workflow, the systems it touches and the rules it must meet. We will help define a useful first release and the evidence needed to review it.