Integrating Federated Learning and Blockchain for Enhanced Financial Portfolio Management

Financial portfolio management receives secure and efficient processing through the combination of Federated Learning (FL) with blockchain technology. FL protects data privacy through its distributed training capabilities that prevent financial data exposure. Blockchain secures operations and maintains transparency through the creation of unalterable model change logs on its ledger systems. A proposed approach reaches 91.3% model accuracy level and a 1.27 Sharpe Ratio and delivers a 14.3% return on investment which surpasses conventional approaches. The training duration reaches 4.8 hours while security enhancements and increased efficiency become available in the system. The designed framework supports 200 transactions per second at 250 ms response time while maintaining complete security with 0.10 USD transaction fees. It demonstrates the ability of FL and blockchain technology to boost security measures and risk-adjusted performance metrics and computational capability. Future Work will concentrate on blockchain performance optimization while testing practical applications of algorithms and revising algorithms to optimize financial applications.

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Publication Details

Published
2025-02-21
DOI
https://doi.org/10.1109/icicacs65178.2025.10968394
Citations
2
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
6.49
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article

Integrating Federated Learning and Blockchain for Enhanced Financial Portfolio Management

V. G. Murugan, Sudhansu Sekhar Nanda, Niranjan Kumar, Vijaya Chamundeeswari et al.
2 citations
Blockchain Technology Applications and Security
6.49
article

Integrating Federated Learning and Blockchain for Enhanced Financial Portfolio Management

V. G. Murugan, Sudhansu Sekhar Nanda, Niranjan Kumar, Vijaya Chamundeeswari, V. R. Sudindra, Gajendra Naidu Jatty
article en
2 citations

Abstract

Financial portfolio management receives secure and efficient processing through the combination of Federated Learning (FL) with blockchain technology. FL protects data privacy through its distributed training capabilities that prevent financial data exposure. Blockchain secures operations and maintains transparency through the creation of unalterable model change logs on its ledger systems. A proposed approach reaches 91.3% model accuracy level and a 1.27 Sharpe Ratio and delivers a 14.3% return on investment which surpasses conventional approaches. The training duration reaches 4.8 hours while security enhancements and increased efficiency become available in the system. The designed framework supports 200 transactions per second at 250 ms response time while maintaining complete security with 0.10 USD transaction fees. It demonstrates the ability of FL and blockchain technology to boost security measures and risk-adjusted performance metrics and computational capability. Future Work will concentrate on blockchain performance optimization while testing practical applications of algorithms and revising algorithms to optimize financial applications.

University of Botswana (BW), Sri Sri University (IN), ICFAI Business School (IN), Institute of Chartered Financial Analysts of India (IN), Saveetha University (IN)
Openalex Percentile: Top 4%
Blockchain Technology Applications and Security
6.49
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