Upon completion of this course, participants will be able to:

• Differentiate between **RegTech and SupTech** and analyze their complementary roles in achieving regulatory compliance and oversight efficiency.
• Evaluate and select appropriate **RegTech solutions** (e.g., automated AML/KYC, compliance monitoring) for specialized financial institutions (NBFIs, MSBs).
• Design the technical and policy requirements for **digital regulatory reporting** (DRR), enabling automated data submission and validation.
• Develop a strategic roadmap for the **implementation and integration** of both RegTech and SupTech, managing organizational change and system compatibility.
• Master the use of **AI/ML and Natural Language Processing (NLP)** for automated compliance checking and analysis of regulatory documents.
• Establish clear **standards and protocols** for data exchange (e.g., APIs, common data models) between RegTech and SupTech platforms.
• Address the **cybersecurity and data governance** challenges associated with increased automation and the use of shared data platforms.
• Formulate policy recommendations to foster a collaborative ecosystem for the adoption of RegTech by specialized institutions.

• Regulatory and Supervisory Technology (RegTech/SupTech) Project Managers.
• IT and Data Architects at Regulatory Authorities and Financial Institutions.
• Compliance Officers and Chief Risk Officers (CROs) at NBFIs and MSBs.
• Internal Auditors focused on Automated Compliance Controls.
• Regulatory Policy Developers specializing in Digitalization and Data.

• RegTech/SupTech Strategic Implementation Roadmap Workshops
• Workshops on Designing a Digital Regulatory Reporting (DRR) Data Model and API Specification
• Case Studies on Automated AML/KYC and Transaction Monitoring Systems
• Group Activities on Developing Data Governance and Cybersecurity Protocols for a Shared Data Platform
• Expert Lectures on AI/ML and NLP in Regulatory Compliance and Oversight
• Individual Exercises on Calculating the Implementation Cost vs. Efficiency Gain for a RegTech Solution

Unit 1: The RegTech and SupTech Ecosystem

• Defining **RegTech** (compliance and reporting automation by FIs) and **SupTech** (oversight automation by Regulators).
• Analyzing the drivers for adoption in specialized sectors: high transaction volume, complex rules (AML), diverse data.
• Review of key RegTech use cases: automated KYC/CDD, transaction monitoring, sanctions screening.
• Review of key SupTech use cases: automated compliance checking, real-time risk scoring, predictive analytics.
• The concept of regulatory harmonization and the use of common data models.

Unit 2: Digital Regulatory Reporting (DRR) and Data Exchange

• Designing the technical framework for **Digital Regulatory Reporting (DRR)** (e.g., XBRL, APIs).
• Protocols for automated data validation, quality checking, and real-time feedback on submissions.
• Establishing **data standards and ontologies** to ensure common interpretation of regulatory terms.
• The role of distributed ledger technology (DLT) in enhancing the security and immutability of regulatory data exchange.
• Legal and policy requirements for mandatory digital submission of specialized reports (e.g., MSB transaction data).

Unit 3: AI/ML in Automated Compliance and Surveillance

• Implementing **AI/ML** in RegTech for enhanced transaction monitoring and reducing false positives in AML.
• Using **Natural Language Processing (NLP)** to automatically check legal documents and internal policies against regulatory requirements.
• Applying ML in SupTech for anomaly detection and predictive risk modeling based on automated data feeds.
• The use of **RPA** for automating routine compliance tasks and internal regulatory reporting.
• Managing the model validation and governance requirements for both RegTech and SupTech AI applications.

Unit 4: Implementation Challenges and Risk Management

• Developing a strategic implementation plan, managing legacy systems, and ensuring system interoperability.
• Addressing the **cybersecurity and data governance** risks of automated data sharing and cloud deployment.
• Protocols for managing the **vendor risk** associated with third-party RegTech/SupTech providers.
• The challenge of cost allocation and setting appropriate regulatory requirements for RegTech adoption by smaller NBFIs.
• Compliance and legal challenges related to data residency, privacy, and cross-border data flows.

Unit 5: Policy and Regulatory Alignment

• Formulating a regulatory sandbox or innovation hub to test and promote effective RegTech/SupTech solutions.
• Developing a policy on the adoption of common data standards and open APIs for regulatory purposes.
• Strategies for enhancing the technical competence and data literacy of both supervisory staff and specialized institutions.
• Measuring the impact of RegTech/SupTech on compliance costs and supervisory effectiveness.
• Future trends: fully automated real-time regulation (R2R).