Problem Description
Financial institutions must consistently demonstrate compliance with internal policies and external regulatory requirements. Ensuring adherence across accounts, activities, and policy documentation is typically a manual and error-prone process. As oversight demands grow, organizations struggle tomaintain accuracy, audit readiness, and rapid reporting.
Using Syncloop’s multi-agent architecture, regulatory oversight becomes automated, scalable, and traceable—allowing compliance teams to perform continuous monitoring with high precision and minimal effort.
Working of Template
This template deploys four specialized AI agents coordinated through Syncloop APIs. Each agent fulfills a dedicated oversight function—retrieving regulated data, interpreting policy rules, performing regulatory checks, and compiling official oversight summaries.
The Team Manager (Morgan) orchestrates the workflow end-to-end, ensuring structured execution, task delegation, and final closure of the regulatory oversight cycle.
Who Can Use This
- Internal compliance teams
- Governance & risk officers
- Regulatory audit teams
- RegTech engineers
- Financial oversight departments
Agents Required
Agent Name: Morgan
Role & Capabilities: Manages the full oversight cycle by generating oversight IDs, assigning tasks to Chole, Derek, Wani, and Austin, and overseeing progress through final sign-off.
Agent Name: Chole
Role & Capabilities: Retrieves necessary profiles and policy materials, consolidates insights from all agents, and generates the official oversight report.
Agent Name: Derek
Role & Capabilities: Fetches account, customer, and transaction information, supports Austin by providing requested regulatory data, and supplies real-time system timestamps when needed.
Agent Name: Vaani
Role & Capabilities: Provides policy references and regulatory rule sets, ensures oversight decisions follow existing standards, and supplies rule interpretations when invoked.
Agent Name: Austin
Role & Capabilities: Performs regulatory assessment and analysis, validates adherence based on policy data from Wani, and uses Derek’s outputs to identify compliance gaps or risks.
Syncloop API Usage
| API Endpoint |
Method |
Input Parameters |
Output Format |
Agent Name |
| /initiate/oversight |
POST |
{"entity": "FinOrg", "initiator": "OpsUser"} |
{"oversightId": "OVS-001"} |
Morgan |
| /assign/agent |
POST |
{"oversightId": "OVS-001", "agent": "Derek"} |
{"status": "Assigned"} |
Morgan |
| /data/accounts |
POST |
{"oversightId": "OVS-001", "accountId": "ACC001"} |
{"data": {...}} |
Derek |
| /policy/reference |
POST |
{"oversightId": "OVS-001", "dataset": {...}} |
{"complianceStatus": "Flagged", "notes": [...]} |
Austin |
| /report/compile |
POST |
{"oversightId": "OVS-001", "include": ["data", "policy", "analysis"]} |
{"reportUrl": "https://..."} |
Chole |
| /finalize/oversight |
POST |
{"oversightId": "OVS-001", "status": "Completed"} |
{"confirmation": "Success"} |
Morgan |
Flow Summary
- User submits a regulatory oversight initiation request.
- Morgan (Team Manager) creates an oversight ID and assigns Chole, Derek, Vaani, and Austin through Syncloop APIs.
- Derek (Data Agent) retrieves necessary account and operational data.
- Vaani (Policy Agent) provides policy rules, regulatory standards, and guidance.
- Austin (Reg Agent) analyzes data against regulatory and policy frameworks to spot compliance gaps.
- Chole (Reporting Agent) compiles all insights and prepares the final oversight report.
- Morgan reviews the outputs, finalizes the oversight cycle, and delivers the results to the requester.
Optional Enhancements
- AI Extraction Agent for pulling data from scanned compliance or policy documents.
- Regulation API Integration for continuous real-time updates to oversight rules.
- Learning Feedback Agent to improve regulatory accuracy from prior oversight outcomes.
- Oversight Dashboard with live monitoring, centralized reporting, and visual analytics
Ideal KPIs to Measure Success
- Oversight Completion Time: Reduced from days to hours
- Regulatory Alignment Accuracy: > 95% policy compliance.
- False Alert Rate: <3% false positives.
- Risk Identification Accuracy: > 90% detection of non-compliant activities.
- Stakeholder Satisfaction: > 4.5/5
- Automation Coverage: 85% + tasks fully automated