This is a Guest Blog by Mr. Raman Vig and Sudipta K Ghosh co-founders of Roopya
Digital lending is gaining significant ground in India. With the accelerated integration of technology into financial offerings, several fintech companies have made the borrowing process effortless. It involves both the parties – borrower and lenders digitally to expedite the loan disbursal process. Consequently, this has shown a momentous improvement in driving a financially inclusive economy. Recent stats suggest – India’s lending market is expected to touch USD 350 Bn by the end of 2023 from USD 270 Bn recorded in 2022. The tremendous growth is largely driven by industry stakeholders’ robust efforts, including the apex bank, to propel digital banking services in India.
Given the interdependence of the world on digital channels, the number of borrowers especially in the retail segment has multiplied in recent years. This has dramatically changed the dynamics of the debt market in India. As a result, credit distribution has increased profitability for financial institutions while also moving from traditional risk models to a data-backed approach for customer segmentation and personalization for collections.
Robust debt recovery ecosystem
The lenders get vast amounts of consumer data that are gathered by banking institutions in structured and unstructured forms. The abundance of data does not benefit the lenders in decision-making but a data-driven system. AI and ML technologies build robust data-driven approaches for lenders that further aid in weeding out problematic instances in much earlier stages.
Working with a specified user help lenders develop a digitally strong ecosystem for risk measurement. By using ML techniques, specified user fintech companies can transform large data sets into useful insights and build a reservoir of important credit information for the structured data required to build a robust loan distribution model. Furthermore, it facilitates lenders with a powerful recovery system to boost the rate of collection and create a win-win for borrowers, lenders and collectors.
Accessibility to Credit information
More fintech companies could get access to the credit information of millions of Indian users after the RBI has laid down new eligibility criteria for entities to be recognized as specified users of Credit Information Companies (CICs).
Earlier unregulated financial services companies such as NBFCs, regulated brokers, credit institutions, and others had limited access to credit information. However, the new eligibility criteria mandate these entities to become specified users of CIC to provide credit data for an uninterrupted, transparent and secure digital loan processing.
The new eligibility criteria highlight specified users to be incorporated in India or as a Statutory Corporation established in India. The company should have a net worth of at least Rs. 2 crores, as per the latest audited balance sheet to be a specified user of CIC. Further, the company should have not less than three years of relevant experience in running the business along with a clean track record in the activity of processing credit information.
The RBI has laid down stringent eligibility criteria to promote data protection from fraudsters and transparency in the exchange of credit information across companies.
Improved integrity and security
A diverse set of digital lenders require credit data to offer tailored products to their consumers. However, the acquisition of sensitive consumer data from reliable sources makes the loan disbursal a slow and highly exhaustive process. The move to have specified users in the ecosystem expedites the decision-making process for lenders while leveraging direct access to data. This provides better oversight on who and how someone is using sensitive credit data.
As per the new RBI mandate, specified user fintech companies possess a CISA certification that exhibits a robust and secure IT system for data security. This ensures the specified user is built on a healthy and secured data model and the lenders are accessing data from a company owned and operated in India and permitted by RBI.
Enhanced risk assessment
India ranks third in terms of total debt and the absolute high debt numbers are also expected to rise with surging population. Specified users help lenders adopt advanced data analytics tools to understand profound insights and evaluate the probability of default consumers. The transparency in data analytics help lenders establish consumer centricity. This can further help the lenders determine whether the consumer will be able to adhere to the payback plan.
Data-driven approach streamlines the lending journey at digital lending platforms. New technologies such as AI and ML back automation and real-time analysis of consumer data further prompt retailers with the right credit decisions. Lenders can look through the credit score, annual income, debt to income ratio of the consumer and determine loan success rate with the closest accuracy.
What’s next?
Traditional credit tools possess limitations pertaining to data models and credit information accessibility. Specified users in fintech embed a predictive analytical approach that examines various risk variables and move the lenders from the traditional approach to new-age credit models. The emergence of specified users is projected to strengthen the digital lending ecosystem across retail and other business segments with reduced risk of fraud and data breaches.
