With increasing internet penetration and digitalization, new era financial services like digital loans, e-wallets, phygital banking, BNPL and other fintech innovations are fueling financial inclusion in India.
However, access to credit is still clouded by archaic underwriting systems. It is an important pillar of an inclusive financial ecosystem that can support India’s growth, positively affecting economic development and GDP.
Restricted access to credit threatens the equitable distribution of income and wealth and affects macroeconomic stability. On the other hand, it is essential to have an equal chance of obtaining credit when needed.
It helps underserved people seize entrepreneurial opportunities, insure against risks, invest in education and take all other actions that contribute to individual growth. While 190 million people in India are still unbanked, these figures pose a significant barrier to financial inclusion.
The Indian government has taken key steps to improve access to credit and boost growth, especially for MSMEs through programs such as the Credit Guarantee Scheme (CGS), and for borrowers looking for real estate financing through the liquidity infusion facility (Lift). However, these measures have contributed more to solving the liquidity crisis than measuring access to credit itself. And that’s where traditional credit score comes under the spotlight.
Here’s why alternative credit score metrics are the need of the hour. They can in fact catalyze a positive transformation of the Indian financial ecosystem, fostering both inclusion and equity like never before.
Bottlenecks in traditional credit scoring models
scrutinize credit risk and usage, as well as repayment history, credit scoring isn’t quite the anti-hero it’s often made out to be. After all, these markers reveal ability and willingness to repay, thereby reducing defaults, making credit affordable for high scorers, and providing an unbiased system that expands access to credit. But does it really achieve these goals?
The roadblocks built into the current system inherently exclude thin-file borrowers who are new to credit, new to income, have limited or no credit histories, are underbanked, or simply unbanked. To empower these previously “credit-invisible” customers and bring them into the formal financial fold, the way financial institutions assess creditworthiness must undergo a dramatic change. This is where data can unlock terabytes of economic opportunity.
How data can change the game
Thanks to artificial intelligence (AI) and machine learning (ML), the two great strengths of digitization, fintechs are now focusing on formulating predictive models for alternative credit scoring, based on data collected from different behavioral attributes of potential customers.
Based on easily traceable factors, such as monthly utility bills, emails, social media usage, contact lists and GPS data in smartphones, as well as determined psychological factors through psychometric testing, this use of data has the potential to overcome the challenges of traditional credit reporting mechanisms.
This allows not only customers who have no prior experience with credit, but also opens up new lending avenues for financial institutions, resulting in a win-win situation. Moreover, these scoring models not only reduce loan risk but also increase revenue. In fact, the ability of data to create robust alternative credit scoring models based on digital fingerprints has been explored globally.
In 2015, a report by Omidyar Network found that big data is poised to help 325-580 million people gain access to credit for the first time across the world’s six most emerging markets, including India, Mexico, Brazil and Indonesia. In 2017, Thailand’s oldest and largest bank used non-traditional data to create new credit-scoring mechanisms to lend to borrowers with tight records. In Chile, Destacame, a digital and alternative credit scoring platform works with more than 35 financial institutions, serving more than 2.6 million customers! Thus, harnessing AI and predictive analytics to mine alternative data has already been shown to work wonders in fostering financial inclusion.
Implications of Alternative Credit Scoring from the “glocal” Lens
Although Indian fintechs have already started using alternative credit scoring systems, privacy is a significant concern. After all, creating digital dashboards to screen credit repayment involves getting permission to track data that customers might not want to share. Using historical data that may have its own bias in training ML/AI models can also pose a challenge, as companies will need to ensure that this does not exclude unserved or underserved customers. In India, women in particular may have lower scores if data on the number of mobile contacts are analyzed for example, because men enjoy higher social mobility.
Despite these concerns, alternative credit scoring that uses smartphone data is the way forward to greater financial inclusion. After all, there were 227 million active internet users in rural India and 205 million in urban India in 2020.
To navigate smoothly towards a more inclusive future, fintechs can and should seize every opportunity to ensure their alternative credit scoring mechanisms are transparent about how they determine creditworthiness, remain free of discrimination, and ensure privacy. and data security. By building confidence on both sides of the equation and enabling smart lending, Alternative Credit Scoring can lead to an unprecedented increase in the country’s Financial Inclusion Index.
The author is Vice President, MD CASHe
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