The future of AI in investment banking will focus on:
● Blockchain-based deduplication for secure and immutable transaction records.
● Federated learning for decentralized data processing, ensuring privacy compliance.
● Quantum computing integration to accelerate transaction matching speeds.
● AI-driven compliance automation to meet evolving regulatory demands.
● Real-time predictive analytics to anticipate potential reconciliation issues before they impact operations.
● Advanced AI-driven fraud detection to identify suspicious patterns and mitigate financial risks proactively.
Owing to rapid AI advancement, financial institutions must begin to incorporate scalable and adaptive deduplication frameworks for eventual efficient and secure processing.
AI-based deduplication is changing the landscape of investment banking with the improved integrity of data, reconciled optimally, and compliance with regulations. In other words, using machine learning, NLP, and advanced pattern recognition will significantly mitigate operational risks and enhance transaction accuracy for financial institutions. Automation, real-time analytics, and security frameworks are the next breath of fresh air for automation-based financial operations, even as Swamy Biru puts it. The inference is that this will support sustainable operations and excellence.
