Building a Cash Flow Underwriting System: Insights from Implementation |
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| © 2024 by IJCTT Journal | ||
| Volume-72 Issue-2 |
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| Year of Publication : 2024 | ||
| Authors : Amol Gote, Vikas Mendhe | ||
| DOI : 10.14445/22312803/IJCTT-V72I2P113 | ||
How to Cite?
Amol Gote, Vikas Mendhe, "Building a Cash Flow Underwriting System: Insights from Implementation," International Journal of Computer Trends and Technology, vol. 72, no. 2, pp. 70-74, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I2P113
Abstract
In the evolving landscape of financial services, a pioneering implementation of a cash flow underwriting system is aimed at expanding credit access and enhancing risk assessment. This approach leverages the convergence of open banking, machine learning analytics, and dynamic underwriting rules to provide a more nuanced evaluation of creditworthiness beyond traditional credit scoring methods. The system consists of four critical components: (1) a partnership with a financial data aggregator to securely link customers' bank accounts, utilizing both open banking APIs and traditional integration techniques; (2) collaboration with a specialized third-party vendor that employs machine learning models to analyze transaction data, generating a comprehensive cash flow score and identifying verifiable income; (3) the development and implementation of underwriting rules that integrate the cash flow score and income data to make informed lending decisions; and (4) the seamless integration of these components into a mobile application and backend infrastructure, ensuring a user-friendly experience and efficient loan processing. This paper discusses the cash flow underwriting system's design, implementation, and strategic significance, highlighting its potential to democratize credit access by transcending traditional credit scores and opening new avenues for financial inclusion and risk assessment. This paper introduces a technical implementation approach for cash flow underwriting through collaborative specialized partners, providing a viable alternative to traditional credit evaluation methods.
Keywords
Cash Flow Underwriting, Financial Technology (Fintech), Open Banking, Credit Risk Analysis, Machine Learning in Finance.
Reference
[1] FinregLab, "The Use of Cash-Flow Data in Underwriting Credit: Empirical Research Findings," Report, 2019.
[Google Scholar] [Publisher Link]
[2] Asli Demirguc-Kunt et al., The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution, World Bank Publications, pp. 1-148, 2018.
[Google Scholar] [Publisher Link]
[3] Sumit Agarwal et al., "Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech," Indian School of Business, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Ying Lei Toh, "Addressing Traditional Credit Scores as a Barrier to Accessing Affordable Credit," Economic Review, vol. 108, no. 3, pp. 21-42, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Jung Hyun Choi et al., "Reducing the Black-White Homeownership Gap through Underwriting Innovations," Urban Institute, Research Report, 2022.
[Google Scholar] [Publisher Link]
[6] Danielle Antosz, Cash Flow Underwriting: 5 Ways Lenders Can Drive Growth, Plaid. [Online]. Available: https://plaid.com/resources/lending/cash-flow-underwriting