Intelligent Mortgage Optimization: Leveraging AI for ‎Personalized Lending and Risk Assessment

  • Authors

    • Tamilselvan Selvamani M. Tech in Artificial Intelligence, SRMIST, Kattankulathur, Chennai – 603203
    • Prabhakaran Arjunan M.Tech in Artificial Intelligence, SRMIST, Kattankulathur, Chennai – 603203
    • Dr. Poovammal E Department of Computing Technologies, Professor of Engineering and Technology, SRMIST, Kattankulathur, Chennai – 603203
    https://doi.org/10.14419/psrwrt75

    Received date: May 6, 2025

    Accepted date: May 18, 2025

    Published date: June 10, 2025

  • Artificial Intelligence; Financial Technology; Credit Risk Assessment; Loan Personalization; Mortgage Optimization

  • Abstract

    Artificial Intelligence plays a key role in the Mortgage Industry, assisting financial institutions to elevate efficiency, accuracy, and ‎personalization in loan management. The transformation in the strategies and focus of financial institutions is significantly enhanced by AI. ‎The traditional style of the Mortgage process is rigid, chances to inefficiencies, and is subject to human biases. This paper presents a ‎comprehensive framework derived with AI, aiming to optimize the mortgage cycle. Our approach to integrating machine learning models ‎enhances borrower profiling, credit risk assessment, and loan personalization. We can also improve the model in the future with regulatory ‎compliance and security support in the process of the mortgage industry. The architecture that is proposed here consists of data acquisition ‎and preprocessing, borrow profiling, and risk assessment. The learning techniques that are provided by AI-powered risk assessment models ‎help to improve loan default predictions and ensure fair and transparent lending processes. In addition, the reinforcement learning and ‎clustering techniques enable loan personalization to be more dynamic, improve borrower satisfaction, and create an inclusive environment for ‎the borrowers. Studies also suggest that privacy-preserving methods such as federated learning and security measures based on blockchain‎, safeguard borrower data. With the Implementation of AI AI-driven mortgage optimization process, financial institutions may achieve minimal ‎risk, high operational efficiency, and offer customized lending solutions. This research work surely contributes to the growing AI ‎applications in the financial sector and can provide a scalable framework for mortgage processing‎.

  • References

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  • How to Cite

    Selvamani, T. ., Arjunan, P. ., & E, D. P. . (2025). Intelligent Mortgage Optimization: Leveraging AI for ‎Personalized Lending and Risk Assessment. International Journal of Basic and Applied Sciences, 14(2), 113-118. https://doi.org/10.14419/psrwrt75