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How Bots/algos decide the Eligibility Criteria for Lending Firms

Manavjeet Singh, Founder & CEO, Rubique
Monday, February 13, 2017
Manavjeet Singh, Founder & CEO, Rubique
Headquartered in Mumbai, Rubique is the leading lending platform in India that empowers individuals & SMEs with an easy & smoother access to finance through wide range of loan & credit card products.

Do you need to get a loan sanctioned soon? If so, all you need to do is convince an algorithm. It may sound fictional, but the day has come when credit institutions are relying heavily on a customer's educational background and professional potential for granting loans. Gone are the days when a customer had to wait for months to get a loan sanctioned or borrow against collateral. Without a robust financial history, most financial institutions hesitated to approve a loan to either start a new business or to buy a property.

The marketplace for financial products in India has been highly inefficient, time consuming and uncertain for customers as well as financial institutions. To avail a loan, customers usually approached banks, loan aggregator websites or direct selling agents. There was a constant challenge witnessed with respect to finding the right fit of consumer profiles and high turnaround time. Hence, the rejection rates are quite high in the loan ecosystem. Fortunately, that scheme of things is now history. Algorithms have now made the whole procedure of sanctioning a loan less daunting and less painful. Several startups have mushroomed in the lending service space, promising improved customer experience, streamlined processes, competitive rates and instant loan approvals by leveraging this technology. They are no longer sticking to traditional methods such as evaluating credit scores, learning more about your occupation, work experience, age, income source and others. Banks and other financial institutions used to deny loans to low-income groups, women and to those who did not have bank accounts or collaterals. But, the vast amount of data amassed by a person's mobile phone or internet activity has now driven a new generation of banking.

Software bots running on algorithms are in place to predict exactly what size of loan is suitable for a customer. Bots have the ability to perform very mundane tasks as well as highly sophisticated ones that would be time-consuming or impossible for a human to perform more efficiently at large scales, and, at low costs. They are helping to reduce the processing time significantly ensuring certainty for a customer's loan application which was completely missing in the traditional practices. Imagine bots filtering operations instead of a salesman or generating payrolls or sanctioning loans and streamlining tasks you'd have to do yourself. Yes, a major tech revolution is already here that is using algorithm and pieces of information from several spheres to study customers and to quickly decide whether to grant a loan or not. These bots are not only helping to cut response time but are also focusing on more value addition and customer-related functions.

Lending startups, which do not demand collateral or use credit scores, are using machine learning and novel methods like psychometric tests to ensure loans don't sour. Psychometric testing helps to assess the credit worthiness of applicants by revealing personality traits with a series of subtle questions that need not necessarily have the right answers. In the U.S., The Texas Higher Education Coordinating Board gives students loans via bots. The entire process of loan application, eligibility check, and disbursal or rejection is based on specific algorithms operated by bots. Unlike the conventional process of researching only a borrower's credit history, bots scan a person's savings accounts, track the cash-flow patterns and corroborate findings with the borrower's credit score. The data received also includes getting to know a customer's job stability through LinkedIn or his/her lifestyle patterns through Facebook and other social media platforms.


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