Reported by: banking|Updated: September 2, 2020
Anuj Pandey, COO, U GRO Capital, explains how a solid digital strategy helped the company serve the MSME sector in a better manner
Mehul Dani: How was your digital strategy implemented in 2019-20, and what was the customer response?
Anuj Pandey: Most financial institutions while lending to MSMEs still insist on looking at physical documents like financials or bank statements. Our approach has been to use digital mindset and platforms as a credible and practical solution to real problems faced by the industry. Our digital strategy has been a combination of digitization and digitalization. Our endeavor has been to educate our customers and GRO partners on the advantages of going digital. To enable them we introduced our GRO+ app which helps digitize physical documents on the spot through ML based OCR tech. We have also developed GRO Score, which is a proprietary ML based credit underwriting rule engine customized for our selected MSME sectors. GRO+ app was made available even on hand-held devices and is now widely recognized has one of industry’s first application of its kind. Today we provide an in-principle decision for any loan application through GRO+ app within 60 minutes.
Post-covid, we find ourselves in a sweet spot thanks to our digital outreach philosophy. Pre-covid, we did a beta launch of our direct to customer application GRO Direct and received 5000+ customer logins in a very short period. We have made the journey completely paperless for low ticket unsecured loans for micro enterprises. While covid has brought a temporary halt in regular business, the period also brought with it an opportunity to relook at our customer engagement models and has led us to test a number of digital solutions such as chatbots and custom-built customer surveys. We even conducted customer sentiment surveys covering 1000+ customers across 9 locations using our chatbot and online survey tools, which have immensely helped us to implement the moratorium facility seamlessly for our customers in the most efficient manner possible.
As we gear up now to get back to business post-lockdown, we have launched an end-to-end digital offering – Sanjeevani – a cash flow assessment based digital loan product. This demonstrates our digital capabilities and the willingness to adopt digital first processes like video KYC, video based personal discussions as well as digital signatures/e-singing of loan agreements.
How have you leveraged data analytics?
Data driven decision making is the backbone of our business as well as the organizational culture. Generally, in the banking industry, consumer lending receives a lion’s share of the focus when it comes to data analytics; however, application of analytics in MSME lending is lesser and mostly in one-size-fits-all manner. We were the first organization to adopt a sector specific strategy; we realized that cashflows of an electrical equipment manufacturer were very different than that of an education institution or a pharmacy store – which implies that these entities need to be assessed in very different ways. We have consciously designed for a ‘zero data loss storage’ architecture, where every bit of customer data is stored for future analysis in a central repository. This is bolstered by the API partnerships where bank statements, tax reports and credit bureau reports are converted to machine readable data. We have invested in globally acclaimed statistics and machine learning software.
Analytics driven decision making helps increase throughput while keeping risk and costs in check. Use of scorecards enable us to reject 80% of high-risk applications by eliminating only 30% of all logins, thus also giving us crucial levers to monitor and fine tune strategies. Importantly, progressively trained models become better at taking decisions, offering a massively scalable solution in solving the unsolved credit needs of the Indian MSME. There are a wide number of case specific examples of analytics usage – generation of pre-approved leads, indicators of risk and propensity, pricing recommendations and fraud alerts – which are of special importance when we go direct to consumer and try to minimize touch.
We are a fast maturing analytics practice with vertical competencies on data engineering, portfolio analytics and on-boarding science/ predictive modelling. We are making rapid strides in taking advanced data science and ML/AI based applications to the market. We have developed an in-house ML deployment engine and are in final stages of implementing our first home-grown alternate data model for credit assessment. Work is underway to digitize processes that have always been physical – such as location assessment, alternate data-based fraud checks, facial recognition and object identification.
What are the marketing campaigns? How do you use social media?
We have used analytics and data driven decisions in marketing campaigns as well. We follow a very focused and sharply targeted marketing campaign strategy. Audiences are identified and targeted only if they fall under the sectors/sub-sectors which we service and with a high degree of personalisation in the communication and call to action. We have managed to get close to 5000 organic followers on LinkedIn within a year of becoming active on our social handles which tells us that our content strategy is resonating with our audiences. We will focus on building our Facebook handle likewise this year, as it is also a promising sourcing channel for us.