01USE CASE
Regulatory intelligence
Interpret changing requirements and connect questions to relevant source material.
Evaluate this use case ↗Policy-grounded intelligence. Accountable decisions.
Without enterprise AI,
will staff turn to risky public AI?
Regence AI automates risk-sensitive workflows using AI agentsgrounded in up-to-date regulations with human oversight.
Evaluate a defined workflow against agreed evidence and measurable outcomes.
BankingPayments & fintechRisk & complianceFinancial supervision
01 / Banking use cases
AI applications across
banking functions.
Evaluate a defined banking workflow. Scope, data requirements and acceptance criteria are agreed with your institution before environment preparation.
02USE CASE
AML & KYC
Explore onboarding reviews, risk indicators and exceptions that need human attention.
Evaluate this use case ↗03USE CASE
Credit & fraud review
Surface missing evidence, review credit files and support structured investigations.
Evaluate this use case ↗04USE CASE
Treasury & ALCO
Evaluate liquidity questions, policy constraints and decision-support workflows.
Evaluate this use case ↗05USE CASE
Governance & reporting
Bring evidence, assessments and review actions together for governance teams.
Evaluate this use case ↗06USE CASE
Trade finance
Explore document and policy review through the existing advisory experience.
Evaluate this use case ↗Enterprise integrations
Enterprise integrations
Enterprise integrations connect Regence AI workflows to customer, account and transaction data in Oracle FLEXCUBE and Finacle, and to payment processes through Mojaloop, enabling controlled access and reducing manual handoffs.
Built around accountable decisions
AI assistance.
Human accountability.
A POC should demonstrate both useful outcomes and the controls your institution needs.
Grounded in evidence
Evaluate responses against relevant regulations, institutional policies and source references.
Designed for review
Identify exceptions, define accountable reviewers and agree what requires human approval.
Institutional deployment requirements
Confirm data residency, model access and integration requirements before environment preparation.
Regulatory evidence ↗Proof-of-concept evaluation
Structured evaluation.
Informed deployment decisions.
Institution and evaluation requirements
Provide institutional requirements and identify the proposed workflow and evaluation objectives.
Define acceptance criteria
Document functional requirements, data constraints, accountable reviewers and measurable outcomes.
Confirm scope and approval
The proposed scope is reviewed with institutional stakeholders. Environment preparation follows approval and resolution of outstanding requirements.
Validate agreed outcomes
Prepare approved test data and access controls, execute agreed scenarios and assess results against acceptance criteria.
Open channel
Build the next standard
with us.
Share a regulatory question, operational challenge or recently issued circular, and we will demonstrate how the relevant module produces a clear, source-cited response.
regence@leapsoftconsulting.comReplies within two business days · NDAs welcome · proof-of-concept implementations scoped on request
Request a POC ↗