The combined impact of blockchain and AI in finance, connecting with industry experts and researching how these technologies can amplify each other’s value.
Here are some insights into how they’re transforming finance, particularly in securities services:
• Enhanced Data Security and Privacy: Blockchain’s secure, immutable ledger perfectly complements AI’s analytical capabilities, especially in areas like identity verification, AML, and fraud detection. Together, they ensure that sensitive data is both accurate and protected.
• Boosted Data Quality for AI Models: AI needs reliable data, and blockchain offers transparency and verifiability. In securities services, for example, blockchain’s shared ledger supports accurate trade reconciliation, allowing AI to quickly spot and address discrepancies.
• Smarter Automation: Blockchain and AI together bring new levels of automation. AI-enhanced smart contracts in securities lending or repo transactions can dynamically adjust to real-time market data, reducing counter party risk and increasing efficiency.
• Transparency and Accountability: As AI increasingly supports decision-making, blockchain’s auditability provides an essential audit trail. In areas like custody and asset servicing, blockchain helps document every data point feeding into AI models, aligning with regulatory standards and ensuring accountability.
• Transforming Tokenization and Digital Assets: With AI analyzing market trends and sentiment, and blockchain enabling secure asset tokenization and tracking, this combination is set to streamline asset servicing, custody, and post-trade.
• Building Ethical AI: Blockchain’s data provenance features help verify data, reducing bias in AI models. This is key for fair, ethical AI in areas like credit scoring and risk assessment.
In finance, and especially in securities services, blockchain and AI’s synergy is creating efficiencies, transparency, and trust. Their combined strengths present enormous potential to transform processes, strengthen compliance, and support ethical AI applications.
Written By: Gunsel Topbas, PhD
