The entry of modern fintech lenders within the last decade caused a transformation of the MSME lending landscape in India
NPAs for the lending industry are just like the dark lord, Voldemort – person who should not be named. Made uglier by the recent multi crore defaults in the primary line banks which were much in the news headlines recently. In line with the CARE Rating Report of December 2017, India’s NPA ratio is fifth highest on the globe, behind only the 4 European economies – Portugal, Italy, Ireland & Greece. And we were holding the economies that have been the worst hit following the Eurozone Debt crisis. The 21 Indian PSUs have a gross bad loans of Rs 7.33 lakh crore (as on December 31, 2017). The need for controlling the NPAs can hardly be overemphasised.
The good thing ironically is that with Rs 80,000 crores in NPA, the MSME segment includes a relatively cleaner record compared to the larger corporations. The contribution of the MSME sector to the NPA is low not surprisingly sector having been the hardest hit by the consequences of demonetisation and GST implementation. Yet the organized lenders have greater comfort with the bigger corporations. There are 6.4 Crore MSMEs (MSME Annual Report 2017-18) when compared with 32 Lakh large corporations. The Economic Survey 2017-18, demonstrates large enterprises got 82.6% of the full total credit disbursed by Banks, as against 17.4 % to the MSME.
The MSMEs, more specifically the micro enterprises have already been ignored by Banks and formal lending institutions because they don’t maintain standard documents for his or her business and their banking and frequently haven’t any credit histories, making their credit assessment a challenge. Also the tiny loan requirements demands a minimal unit cost of servicing, a thing that formal lenders have not developed their procedures for. That is a vicious cycle, as having less formal lending provides no incentive to micro enterprises to boost their business documents and banking records.
The entry of modern fintech lenders within the last decade caused a transformation of the MSME lending landscape in India. They attended armed with innovative solutions to measure the risks of the lending to micro and small scale enterprises. They have started delivering customised credit solutions with shorter turnaround times and provide better customer engagement. And these lenders are managing to handle the credit requirements of the underserved albeit credit worthy enterprises without compromising on the fitness of their portfolio.
HOW DO Fintech Players Make Lending Immune to NPAs?
Robust data aggregation and underwriting – The Fintech Lenders utilize a selection of data types well beyond what’s utilized by traditional lenders. Usage of socio demographic data or behavioural data along with digital extractions of insights from credit reporting agencies and bank statements gives them advantage in assessing ‘non standard’ customers. The usage of machine algorithms and big data analysis complemented by the original credit assessment methods, can offer better assessment of the working model and cash flows of the micro enterprises. These alternate data models helps the lending company gauge both, the payback ability and intent of the borrowers to honour their obligations. They have thus moved beyond the traditional approaches of risk assessment predicated on Cibil Scores and financial documentation review and created a holistic method of risk assessment which includes not merely deepened credit penetration but also helped the lending company maintain an excellent quality portfolio.
Default Management using Predictive and Psychometric Models – The data-driven analytics led fintech players are also leveraging technology to create predictive models to pre-empt the occurrence of default to keep up the standard of their portfolio. Some of the lenders are also using psychometric analysis, which is normally conducted to pre-screen applications. These tools come handy in mitigating the cases of overdues and if the overdue occurs, they often predict the chance and quantum of likely loss. Such tools can significantly enhance the confidence of a lender when lending to first-time borrowers so when screening high-risk segments
Last mile connect to borrowers – Recognising that relying purely on a distance relationship with the clients might increase the threat of default as well as customer attrition, many of these fintech lenders also have created an optimal network of branches at hand contain the borrowers through the pre and post loan process. Lots of the borrowers are first-time borrowers and are unaware of the repercussions of defaulting on the repayment obligations and how it adversely impacts their credit histories. Through the branch sales and servicing teams the Fintech Lenders have created multiple customer touchpoints with the borrowers to teach them on the advantages of making timely payments which includes reduced the incidence of default and increased customer retention rates.
There is absolutely no silver bullet to slay the NPA monster. The nice old discipline of consistent and focussed efforts on managing the loan book remains the main element. The fintech revolution however has taken to the table new weapons that use data based insights and offer early warnings and predictions to greatly help lenders respond speedily and focus their efforts in effectively coping with defaults.