Home loan is a very important financial product for developers, consumers, and lenders. However, the process as we know it can be extremely tedious, time-consuming, and frustrating for the borrower, requiring numerous checks and lengthy documentation. Such delays in loan processing keep the productive capital away from the system for real estate developers and sellers resulting in loss of profitability. Further, not having a proper solution and section of the right lending bank may lead to sales not materialising or losses caused by significant delays in loan processing.

The pandemic has brought about a fundamental change in the way we go about our day-to-day lives and business. With work from home becoming a norm for most, there is demand from customers looking to invest in a bigger home and in turn looking for a home loan to enable this investment. Unable to provide services from its “brick and mortar” branches due to the lockdowns, the home loan industry is experiencing a wave of technological innovation as new-age start-ups and traditional lenders are adopting technology to automate, simplify and speed up the process.

Here is a very strong use case for the data-driven Artificial Intelligence (AI) toolkit leveraging machine learning in the home loan ecosystem in India. Fintech start-ups like Easiloan are transforming traditional processing and making it smart by using data-driven engines, machine learning, AI, and predictive analytics in transforming the processes, reducing processing time, and automating decision making.

Technology is a game-changer for loan providers. The loan process usually involves filling in several personal and financial details by the applicant. As per existing practice, the loan provider still requires human intervention even after they have all the documents scanned for classification and inputting in the Loan Origination System (LOS). AI can change this and eliminate the manpower currently required to get the data from documents into LOS for further processing.

Optical Character Recognition (OCR) is transforming paper-based processes into digital, multiple verification details can be extracted and verified through OCR making it simpler and faster for customers. Tech solutions can then auto-fill, fetch, and validate customer information. ML can boost the accuracy on validation of multiple data points such as income, outgoings, other loan payments, investment earning. This process is completely automated offering higher accuracy, speed, and minimize the need for human interference. This way the process is much more efficient with lower human errors, higher productivity, and lower need for resources. In the end, the customer saves time, the bank saves resources and the real estate developer or the seller gets cash flow much earlier.

Data and AI-based tools will play a big role in improving efficiency in the financial lending space. With machine learning, mortgage lenders and underwriters are going to be more efficient, more profitable, and capable of delivering a much better customer experience.

The author is Co-founder & CEO, Easiloan

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