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When a mortgage defaults nobody wins, so it continues to remain in the best interest of lenders to predict the likelihood of a mortgage defaulting before approving it. According to Marketwatch, there were approximately 300,000 foreclosures in the US in the first half of 2019 alone. Foreclosures are usually never profitable, and cost mortgage lenders approximately $50,000 per loan. Other costs incurred from foreclosures are distributed across loss in property values of nearby homes and loss in tax revenue for local governments. Predicting the likelihood of a mortgage defaulting continues to be a widespread problem for mortgage lenders globally.
AI will allow your organization to predict the likelihood of a mortgage defaulting before approving it. By leveraging historical default data, AI will be able to easily identify the characteristics that point to an increased likelihood of a mortgage defaulting. Using AI models to supplement the decision of a loan officer will allow your organization to incur fewer mortgage defaults. Decreasing the likelihood of a mortgage defaulting will result in a greater value of your mortgage portfolio, and reduce any foreclosure related expenses. Increasing accuracy in mortgage default predictions will also empower your organization to increase the size of its loan portfolio as a result of increased stability in cash flows.
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