India is one of the countries where the people who receive or use credit are only a small percentage of the earning population. Credit is the new discount, as only time can replace money. With the majority of credit seeking consumers in India being in the 20-25 age group with minimal or no credit history to begin with, traditional models of credit underwriting which rely a lot on past credit history end up declining the applicants.
Alternate decisioning is a powerful indicator of an individual’s purchasing power, more importantly, “intent to pay”, which makes it an emerging tool for deciding credit-worthiness. It is called “alternate” because it studies consumer information that doesn’t feature on bureau credit reports. While independent alternate decisioning models are being developed in a major way, there has yet to be an official adaption and effect of their use on the socio-economic fabric of our country.
Moreover, these alternate decisioning models can be executed at various stages of the credit line funnel, to prioritize applications or within the present underwriting model as complementary data points to reduce risk of lending or to increase the volume of processed applications. This additional supply of data works, because it works completely on non-traditional data derived from a customer’s social data, purchasingbehaviour and online behaviour. When alternate decisioning models are added to the traditional credit history based underwriting it makes the score much more robust and accurate, as it completes the consideration set of deciding one’s credit worthiness.
Alternate decisioning is fast evolving into an executable service that can be integrated into an online or mobile application process, with permission of the applicant, enabling lenders to quickly check the credibility of information provided by an applicant. Moreover, Alternate decisioning truly is futuristic because of (1) The credit worthiness need not be binary, but can be on a spectrum, minimizing out-right rejections and (2) It is paperless, which is a huge benefit in the future of digitized India.
Alternate decisioning models can also be very robust in detail, with various digital inputs that can be recorded, ranging from address, contact details, education, career details, utility purchase behaviour to biometric data verification. All this built into a platform that is accessible, both by lenders and applicants, from the comfort of mobile screens.
The future of the Fintech space in India is definitely moving towards complete digitalization of credit processes. With the Fintech space being on a growth spurt, we see credit being extended to a larger percentage of our people, and many fintech platforms in the country are actively in the process of making that a reality. We also see more and more financial processes becoming paperless, and alternate decisioning is soon becoming the new norm of assessing credit worthiness.
At RupeePower, the mantra is that “Algorithms built on digital footprints will revolutionize lending”. This is where Big Data is going to be of utmost importance. It is a big requirement for companies to provide FinTech Services in a segment as complex as credit decisioning. Consumer behaviour has always been the basis of understanding the pain points in the system and developing accurate solutions, and partnering with various entities to develop and research alternate credit decisioning models is a practice that is already underway in our country.
The author, Tejasvi Mohanram is Founder and CEO, RupeePower.