Course Objective & Scope
Banks, brokerage houses, asset managers, payment firms and regulated enterprises in Türkiye must navigate overlapping requirements from BDDK, SPK, MASAK and KVKK when deploying AI. This course translates rules on domestic hosting of primary/secondary systems, cloud and outsourcing restrictions, banking/customer secrecy, investment-advice boundaries and AML explainability into concrete architecture and governance decisions.
Participants evaluate a real AI initiative from their institution through the lens of all four regulators, producing an audit-ready compliance assessment matrix and a draft internal AI directive.
Who Should Attend?
- Regulatory compliance, legal counsel and data protection (KVKK) teams
- Information security (CISO), IT governance, architecture and vendor-management specialists
- Internal audit, internal control, operational risk and model-risk managers
- Business and technology leaders running AI projects in regulated institutions
Key Takeaways
- Assess how BDDK and SPK information-systems regulations apply to LLM and cloud AI services
- Select anonymisation and deployment patterns that protect banking secrecy, customer secrecy and PII
- Define guardrails around robo-advisory, research summaries and investment advice under SPK rules
- Maintain explainability and audit trails for AI tools used in MASAK KYC and AML workflows
- Build an AI approval dossier ready for regulatory inspection and independent IT audit
Curriculum
AI Regulatory Map for Regulated Sectors in Türkiye
- Where BDDK, SPK, MASAK, TCMB and KVKK intersect on AI initiatives
- Aligning local regulations with the EU AI Act and ISO/IEC 42001
- Data classification: public data, PII, customer secrecy and banking secrecy
BDDK Framework: Information Systems, Cloud and Outsourcing
- IT Systems Regulation and the domestic hosting rule for primary/secondary systems
- Trade-offs between foreign LLM APIs, private cloud and on-prem model hosting
- Customer-secrecy exceptions, traceability and mandatory logging
SPK Framework: Capital Markets, Investment Advice and Algorithmic Controls
- Red line between general market commentary and personalised investment advice
- Guardrails for research-report summaries, market bulletins and client communications
- SPK independent IT audit expectations and model-control requirements
MASAK and KVKK Framework: AML, KYC and Personal Data Protection
- Using AI in remote onboarding, KYC and suspicious transaction (STR) analysis with human sign-off
- Explicit consent, privacy notices, cross-border data transfer and retention rules under KVKK
- Handling data deletion and right-to-erasure across model training and RAG indexes
Internal AI Approval Workflow and Audit Readiness
- Joint Legal–Compliance–CISO–Risk assessment template for new AI projects
- Mandatory vendor contract clauses (DPA, zero data retention, audit rights)
- Evidence-pack checklist for independent IT audits and regulatory inspections
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