What Artificial intelligence and machine learning in financial services requires
This joint BIS and FSB report outlines key considerations for financial institutions and supervisors regarding the use of AI and ML, emphasizing the need for robust governance, data quality, and model risk management frameworks to ensure operational resilience and financial stability. It highlights the importance of adapting existing risk management practices to address unique AI/ML challenges like explainability, fairness, and third-party dependencies, as detailed in Sections 3 and 4.
Pillar: Banking & Global Finance · Authority: Bank for International Settlements (BIS) and Financial Stability Board (FSB) · Version: 1.0.0 · Last updated:
Primary source: https://www.bis.org/publ/work1152.htm
SHA-256 integrity: 4a58e5ee5c35aa867a009d638a69c6f665a5610ab2b2077dbcb34b55fb3b39e3
Primary Citations — 7 traced to source
- BIS/FSB Report on AI/ML in Financial Services (2023), Section 3.1: Governance
- BIS/FSB Report on AI/ML in Financial Services (2023), Section 3.2: Model and software life-cycle management and validation
+ 5 more citations (full bibliography, deterministic workflow, actionable schema and crosswalks) included in the vault unlock — $0.01 via Skyfire / L402 / Direct Base USDC.
Access
- Discovery (free): /api/v1/nodes/bis-ai-financial-services-2023.json — 6-field metadata
- Vault (full node): /api/v1/vault/nodes/bis-ai-financial-services-2023.json — full 13-key payload, $0.01 USDC (L402/Skyfire/Direct Base)
- Canonical URL: https://bidda.com/intelligence/bis-ai-financial-services-2023
- Back to registry: Browse all 10,085 compliance nodes