How Microfinance sector can leverage Big Data analytics for financial inclusion

12Dec - by aiuniverse - 0 - In Big Data


The rapid enhancement in technology, new players and huge investments coming up in the financial technology, mobile phone penetration are remodelling the financial services vista. With enhanced penetration of mobile devices globally, the opportunity to gain more understanding about consumer behaviour, comprising how they spend their money and time, has also enhanced. They can now target a distinct group of people using such knowledge.

Big data analytics market also relies on several mobile apps as their engine of information is stored in a data warehouse. Not just the mobile industry; Big Data influences other markets as well, such as micro finance institutions (MFIs). By incorporating digitisation, Big Data plays an innovative role in the unique ecosystem. It helps to fulfill the evolving customer demands & expectations.

The microfinance industry has seen rapid growth. This growth has become a reality as, a result of investors continued support to MFIs with equity infusion of around Rs 9,443 cr which is an increase of 55% from Q1 FY19-20.

With last-mile connectivity set up to reach a large number of clients, it is rapidly evolving into a potent channel to attain one of the national preferences -financial inclusion.

Considering, a large number of client accounts served under the umbrella of the microfinance sector, it is the hub of substantial granular data. This data set enriched with customer information comprising age, income estimates, occupation, attendance at meeting centres and others are leading to the growth of four key aspects.

With most credit institutions, functioning on IT-facilitated lending platforms and credit bureaus updated with all the data, four vital facets are emerging:

Making Reliable Credit Decisions Based on Data

It can help in the development of application scorecards for making an unbiased selection of customers for funding. Customer behaviour patterns and critical information derived from industry data integration into such scorecards help to derive quick credit decisions. In a few mins, at the front end, such credit decisions are attainable through digital channels of customer service officer’s handheld device.

Thus, this helps to save the time spent in verification, reference checks and validation by fulfilment executive. Adding up to, this big data drives customer loan approval, request processing and disbursement of the loan amount.  

Big Data-Driven Model Promises Psychometric Evaluations

Big data-driven model can also, be helpful for psychometric evaluations. Several psychometric tools help evaluate the applicant’s answers which aids to capture information that can help to predict loan repayment behaviour, comprising applicants’ beliefs, performance, attitudes, and integrity.

Product Build up and Service Positioning and Offering

With the help of Big Data, the Microfinance Industry will reach a position where they will have the ability to provide products that customers exactly need. Based on the customer needs visible through analytics such as price modelling, customer segmentation, and data modelling; MFIs will be able to service customers with just-in-time financial needs, with the right loan ticket size and insurance schemes.

Microfinance companies will be able to predict portfolio behaviours at various geographies and hence, rightly analyse defaults or credit losses more precisely. Accordingly, companies can select the right portfolio for their financial products.

Final Takeaway

There is a famous saying, “work smarter not harder”, and big data strongly validates this. Big data in union with various aspects of artificial intelligence (AI) has already begun to transform the decision-making process of not just MFIs but also, several other industries such as manufacturing, automobile, healthcare, communications, media.

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