Machine Learning for Risk Compliance Automation in India’s Financial Sector
DOI:
https://doi.org/10.36676/irt.v8.i4.1509Keywords:
Risk Compliance, Automation, Machine LearningAbstract
The automation of risk compliance through machine learning (ML) has become essential for Indian financial institutions to ensure adherence to regulatory standards. This paper explores the use of ML algorithms such as Decision Trees, Random Forest, and Support Vector Machines (SVM) to automate the process of risk compliance. The study evaluates how these algorithms can analyze large volumes of financial data to detect compliance violations, fraud, and money laundering activities. The research also examines the role of AI in enhancing transparency and reducing operational costs in the Indian financial sector.
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