ARCHIVES
Year 2026 · Volume 5 · Issue 3
Review Article
A Comprehensive Review of Applications, Challenges, and Future Directions of Artificial Intelligence in Mortgage Lending
Amit Kurchania1
1 AVP - Digital Solutions, Marlabs LLC, Texas, USA
Published Online: September-December 2026
Pages: 196-204
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20260503025References
1. Chan, L., Hogaboam, L., & Cao, R. (2022). Artificial intelligence in credit, lending, and mortgage. In Applied Artificial Intelligence in Business: Concepts and Cases (pp. 201-211). Cham: Springer International Publishing.
2. Garcia-Teruel, R. M. (2022). Integrating artificial intelligence into the mortgage credit market. Available at SSRN 4304716.
3. Kumar, V., Saheb, S. S., Ghayas, A., Kumari, S., Chandel, J. K., Pandey, S. K., & Kumar, S. (2023). AI-based hybrid models for predicting loan risk in the banking sector. Big Data Mining and Analytics, 6(4), 478-490.
4. Kowsar, M. M., Mohiuddin, M., & Mohna, H. A. (2023). Credit decision automation in commercial banks: a review of AI and predictive analytics in loan assessment. American Journal of Interdisciplinary Studies, 4(04), 01-26.
5. Lee, M. S. A., & Floridi, L. (2021). Algorithmic Fairness in Mortgage Lending: from Absolute Conditions to Relational Trade-offs: MSA Lee, L. Floridi. Minds and Machines, 31(1), 165-191
6. Spiess, J. (2022). Machine learning explainability & fairness: Insights from consumer lending. FinRegLab Whitepaper.
7. van Zetten, W., Ramackers, G. J., & Hoos, H. H. (2022). Increasing trust and fairness in machine learning applications within the mortgage industry. Machine Learning with Applications, 10, 100406.
8. Jagtiani, J., Lambie-Hanson, L., & Lambie-Hanson, T. (2021). Fintech lending and mortgage credit access. The Journal of FinTech, 1(01), 2050004.
9. Amarnadh, V., & Moparthi, N. R. (2023). Comprehensive review of different artificial intelligence-based methods for credit risk assessment in data science. Intelligent Decision Technologies, 17(4), 1265-1282.
10. Ramakrishnan, R., Rohella, P., Mimani, S., Jiwani, N., & Logeshwaran, J. (2024, March). Employing AI and ML in risk assessment for lending for assessing credit worthiness. In 2024 2nd International Conference on Disruptive Technologies (ICDT) (pp. 561-566). IEEE.
11. Wang, Z. (2024). Artificial intelligence and machine learning in credit risk assessment: Enhancing accuracy and ensuring fairness. Open Journal of Social Sciences, 12(11), 19-34.
12. Pal, P., Wang, Z., Zhu, X., Chew, J., Prus, K., & Wei, X. (2025). AI-Based Credit Risk Assessment and Intelligent Matching Mechanism in Supply Chain Finance. Journal of Theory and Practice in Economics and Management, 2(3), 1-9.
13. Peddamukkula, P. K. (2024). The Impact of AI-Driven Automated Underwriting on the Life Insurance Industry. International Journal of Computer Technology and Electronics Communication, 7(5), 9437-9446.
14. Nagamani, N. (2025). AI-driven risk assessment models for health and life insurance underwriting. IACSE–International Journal of Computer Science and Engineering (IACSE-IJCSE), 5(1), 8-25.
15. Kurva, R. (2026). Intelligent Underwriting Systems in Insurance: A Technical Review. Journal of Computational Analysis & Applications, 35(1).
16. Joshi, S. (2024). Artificial Intelligence Applications in Mortgage-Backed Securities: A Comprehensive Review. Available at SSRN 5341000.
17. El Sayad, I., Chong, F. H. L., & Gosal, B. (2026). Risk assessment in mortgages: a comparative study of AI models. PeerJ Computer Science, 12, e3494.
18. Fonkem, B. N. (2025). AI-powered risk scoring models for real-time fraud detection in digital banking ecosystems. Journal of Computational Analysis and Applications, 34(11), 349-371.
19. Oko-Odion, C. (2025). Ai-driven risk assessment models for financial markets: Enhancing predictive accuracy and fraud detection. International Journal of Computer Applications Technology and Research, 14(04), 80-96.
20. Sarna, N. J., Rithen, F. A., Jui, U. S., Belal, S., Amin, A., Oishee, T. K., & Islam, A. M. (2025). AI driven fraud detection models in financial networks: A review. Ieee Access.
21. Chitturi, N. (2025). Agentic artificial intelligence: Architectural paradigms and transformative impact of autonomous financial assistants across the mortgage lending lifecycle. Journal of Computer Science and Technology Studies, 7(8), 1155-1165.
22. Tewari, R. (2025). A Multi-Modal AI Framework for Detecting Document, Identity, and Income Fraud in Mortgage Lending. Identity, and Income Fraud in Mortgage Lending (December 18, 2025).
23. Tavakoli, M., Chandra, R., & Bravo, C. (2025). Capsule Network-Based Multimodal Fusion for Mortgage Risk Assessment from Unstructured Data Sources. arXiv preprint arXiv:2510.22987.
24. DANJUMA, S., Kassim, S., Sharofiddin, A., & Ahmad, M. (2026). Exploring Artificial Intelligence integration in mortgage financing solutions: A study of non-interest banks in Nigeria. International Journal of Islamic Economics and Finance Research, 9(1), 107-119.
25. Babaei, G., Giudici, P., & Wu, L. (2025, July). Explainable fairness in mortgage lending. In World Conference on Explainable Artificial Intelligence (pp. 378-398). Cham: Springer Nature Switzerland.
2. Garcia-Teruel, R. M. (2022). Integrating artificial intelligence into the mortgage credit market. Available at SSRN 4304716.
3. Kumar, V., Saheb, S. S., Ghayas, A., Kumari, S., Chandel, J. K., Pandey, S. K., & Kumar, S. (2023). AI-based hybrid models for predicting loan risk in the banking sector. Big Data Mining and Analytics, 6(4), 478-490.
4. Kowsar, M. M., Mohiuddin, M., & Mohna, H. A. (2023). Credit decision automation in commercial banks: a review of AI and predictive analytics in loan assessment. American Journal of Interdisciplinary Studies, 4(04), 01-26.
5. Lee, M. S. A., & Floridi, L. (2021). Algorithmic Fairness in Mortgage Lending: from Absolute Conditions to Relational Trade-offs: MSA Lee, L. Floridi. Minds and Machines, 31(1), 165-191
6. Spiess, J. (2022). Machine learning explainability & fairness: Insights from consumer lending. FinRegLab Whitepaper.
7. van Zetten, W., Ramackers, G. J., & Hoos, H. H. (2022). Increasing trust and fairness in machine learning applications within the mortgage industry. Machine Learning with Applications, 10, 100406.
8. Jagtiani, J., Lambie-Hanson, L., & Lambie-Hanson, T. (2021). Fintech lending and mortgage credit access. The Journal of FinTech, 1(01), 2050004.
9. Amarnadh, V., & Moparthi, N. R. (2023). Comprehensive review of different artificial intelligence-based methods for credit risk assessment in data science. Intelligent Decision Technologies, 17(4), 1265-1282.
10. Ramakrishnan, R., Rohella, P., Mimani, S., Jiwani, N., & Logeshwaran, J. (2024, March). Employing AI and ML in risk assessment for lending for assessing credit worthiness. In 2024 2nd International Conference on Disruptive Technologies (ICDT) (pp. 561-566). IEEE.
11. Wang, Z. (2024). Artificial intelligence and machine learning in credit risk assessment: Enhancing accuracy and ensuring fairness. Open Journal of Social Sciences, 12(11), 19-34.
12. Pal, P., Wang, Z., Zhu, X., Chew, J., Prus, K., & Wei, X. (2025). AI-Based Credit Risk Assessment and Intelligent Matching Mechanism in Supply Chain Finance. Journal of Theory and Practice in Economics and Management, 2(3), 1-9.
13. Peddamukkula, P. K. (2024). The Impact of AI-Driven Automated Underwriting on the Life Insurance Industry. International Journal of Computer Technology and Electronics Communication, 7(5), 9437-9446.
14. Nagamani, N. (2025). AI-driven risk assessment models for health and life insurance underwriting. IACSE–International Journal of Computer Science and Engineering (IACSE-IJCSE), 5(1), 8-25.
15. Kurva, R. (2026). Intelligent Underwriting Systems in Insurance: A Technical Review. Journal of Computational Analysis & Applications, 35(1).
16. Joshi, S. (2024). Artificial Intelligence Applications in Mortgage-Backed Securities: A Comprehensive Review. Available at SSRN 5341000.
17. El Sayad, I., Chong, F. H. L., & Gosal, B. (2026). Risk assessment in mortgages: a comparative study of AI models. PeerJ Computer Science, 12, e3494.
18. Fonkem, B. N. (2025). AI-powered risk scoring models for real-time fraud detection in digital banking ecosystems. Journal of Computational Analysis and Applications, 34(11), 349-371.
19. Oko-Odion, C. (2025). Ai-driven risk assessment models for financial markets: Enhancing predictive accuracy and fraud detection. International Journal of Computer Applications Technology and Research, 14(04), 80-96.
20. Sarna, N. J., Rithen, F. A., Jui, U. S., Belal, S., Amin, A., Oishee, T. K., & Islam, A. M. (2025). AI driven fraud detection models in financial networks: A review. Ieee Access.
21. Chitturi, N. (2025). Agentic artificial intelligence: Architectural paradigms and transformative impact of autonomous financial assistants across the mortgage lending lifecycle. Journal of Computer Science and Technology Studies, 7(8), 1155-1165.
22. Tewari, R. (2025). A Multi-Modal AI Framework for Detecting Document, Identity, and Income Fraud in Mortgage Lending. Identity, and Income Fraud in Mortgage Lending (December 18, 2025).
23. Tavakoli, M., Chandra, R., & Bravo, C. (2025). Capsule Network-Based Multimodal Fusion for Mortgage Risk Assessment from Unstructured Data Sources. arXiv preprint arXiv:2510.22987.
24. DANJUMA, S., Kassim, S., Sharofiddin, A., & Ahmad, M. (2026). Exploring Artificial Intelligence integration in mortgage financing solutions: A study of non-interest banks in Nigeria. International Journal of Islamic Economics and Finance Research, 9(1), 107-119.
25. Babaei, G., Giudici, P., & Wu, L. (2025, July). Explainable fairness in mortgage lending. In World Conference on Explainable Artificial Intelligence (pp. 378-398). Cham: Springer Nature Switzerland.
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