For the prosper of Micro-credit finance businesses; Big data analytics is an element not to be missed!

February 23, 2018

Big data analytics could bring microfinance to hundreds of millions of individuals and businesses in need of short-term credit. Using big data to support decision making is the core concept of this section. This enables lenders to accurately predict borrower payment behaviour, helping them making informed and more profitable credit decisions in real time.

About Micro-credit

Micro-credit relates to the provision of small, short-term loans and this segment is ripe for digital disruption. Micro –credit business has tended to be local and a small-scale activity. Studies revealed that Worldwide, the microfinance sector reaches less than 20 % of its potential market, according to the International Finance Corporation. Therefore this market has more to be exploited.

Integrating Big Data Analytics in Microfinance

Inclusive financial product using big data through which even small businesses with incomplete credibility records and light assets can be granted credit by virtue of various data generated on their own to get credit at a lower cost.

Credit is built on data which establishes a credit scoring model of a customer through fitting in multiple dimensions such as settlement, transaction, taxation, hydropower and asset by mining massive data of small and micro enterprises scattered in systems like banking, administration, public service, e-commerce platform and so on.

Secondly, proactive credit granting is combined with automatic approval. For qualified businesses customers may complete online application, which is automatically approved by the system model. The fund will be transferred into customers’ accounts on real-time basis. Thirdly, the credit line can be used flexibly featuring borrowing and repaying at any time within the credit line, which can save the loan occupation time of small business customers and reduce financing costs.

More accurate underwriting helps lenders issue more loans, better manage credit quality and fight fraud. The fully automated scoring engine returns credit decisions in real time and removes the risk of human error or personal judgement work with lenders of all kinds – some of the largest banks in the world, payday lenders, P2P lending platforms, microfinance providers, leasing companies, insurance providers, e-commerce platforms and telecoms.

 Data/Information. Using big data to support decision making is the core concept of this section. Simply put, data is raw material. Once it has been analyzed and interpreted, it becomes information; taking on definition and context. Information, along with the corresponding wisdom, lays the foundation to make data-driven decisions and improve results.

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