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  • Kapil Patil

Micro-lending business and alternate data models for underwriting

Updated: Apr 23

Understanding use of alternate data to accelerate financial inclusion of next billion


The increasing popularity of the microcredit industry has changed the way people avail micro-loans. As per Sa-Dhan and MFIN report, India alone has more than 100M microcredit borrowers and a gross loan portfolio of more than $40B. However, despite getting multiple loans, an average ticket is around $400. One of the critical reasons for not getting higher credit or value-added financial products due to limited use of data. In traditional credit markets, lending institutions like banks use credit scoring such as CIBIL to assess the individual's creditworthiness. This Credit scoring system looks into the past credit history of the borrower, their income and other quantifiable, Which means that credits are accessible only to those with prior credit and repayment history with a structured income stream.


This approach of financial assessment leaves a massive set of people financially handicapped. The financial inclusion of these "Left-out" people is the main reason for the existence of microfinance institutions. For the left-out or missing middle, these institutions should take a new approach to assess the creditworthiness of their target segments who do not fit the traditional definition.


According to the world bank report, only 22% of adults are covered by the credit bureau in India. Non-availability of the credit history leads to alternative credit scoring methods that use non-traditional data points to assess the customers' financial health.


One of the benefits laid out by the digitally emerging world is that almost every aspect of a person's digital activity leaves a digital footprint that can provide many insights. A digital footprint can become a proxy and lead to a comprehensive way for a lending institution to access their customer's financial health. They can now analyse their small bills payment pattern, social media usage, spending pattern, e-commerce data etc., to create a whole new module of the credit assessment.


Alternative data-led lending will help new-to-credit or thin-file customers to start availing formal credit starting with micro-loans or EMI products. It enables credit access to the people who were previously ignored by the credit market.



New ways of credit scoring are not something of the near future but rather a current reality. More and More companies are getting involved in alternative scoring, using behavioural, psychometric and other big data to get a comprehensive picture of the borrower. Some of the key players are Tala, CreditVidya and Lenndo.


A common theme around the emerging alternative scoring is AI and deep machine learning, which uses multiple data points. Data points such as customer mobile phone use, SMS, Bill payment, digital payment, e-commerce purchase etc., become proxy for a financial behaviour assessment. Besides, gamified psychometric assessment fills the gap, particularly users with a low/minimal digital footprint.


Data and Privacy


One primary concern that arises with any data usage for business is privacy and security. The alternative credit domain uses significant individual behavioural and private data, which leads to the question regarding the safety of these data and how ethically the companies are using private information. Every company involved in this domain explicitly needs to disclose what data they will collect from their users. This explicit, informed consent with customer & privacy policy should not hide in convoluted terms and condition or other implicit ways. Instead, the alternate credit rating agency should take a straightforward stand on what data is collected, how it is used, and how they ensure the privacy and security of the data. Even the less educated (who is also the primary target segment) should understand what they about to consent. All collected data needs to be stored in a highly secure manner and should not be used other than mentioned purpose with personal identity data encrypted or not accessible for anyone. Also, following local data regulation acts such as General Data Protection Regulation (GDPR) in Europe, Data Empowerment and Protection Architecture (DEPA) in India and similar. Most of the alternate data scoring companies do have strict data collection and safety policies to which they adhere. Still, third-party independent certification of the privacy policy and data protection will add more confidence among users and potential partners.


Challenge for micro-lending segment


Alternative data relies heavily on proxy indicators and sources to collect this data depending on customers' digital presence. Particularly for low-literate and less tech-savvy users, digital engagement becomes a challenge. If MFIs not having a digital presence among their borrowers, then collecting alternate data becomes a challenge. A model that asks for additional data collection by the agent or field staff of MFIs then it becomes an extra burden. Often acceptance of such credit model where MFIs need to engage in data collection is limited. The first stepping stone for creating an alternate credit score for MFI borrowers is to bring borrowers on a digital platform and offer micro-loan through the mobile platform. The primary objective of microfinance and all of these new credit assessment techniques is to make finance accessible to underserved people. As technology and data become increasingly accessible, micro-lending institutions need to help in bringing their borrowers on digital platforms to avail micro-credit services through engaging digital platform.


Alternative scoring will shed light on the customers who remained invisible due to the old assessment method. It also proves to be a much reliable method of credit assessment as it provides a comprehensive financial stand of the customer. All the big players in this segment have a well-proven track record, further proving that it works. Alternate scoring has potential in the microcredit domain and the mainstream financial market by supplementing the traditional credit scores. An efficient alternative scoring combined with a borrower centric micro-lending mobile platform is the recipe to revolutionise the micro-lending sector. With all of these new and emerging organisations in this domain, this revolution is closer than ever!

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