“MicroMoney for People and Big Data for Business” is how we start the microfinance business.
MicroMoney has sharpened the business to become a decentralized Open Source Credit & Big Data Bureau on the Blockchain. Our goal is to bring these people to the new global decentralized crypto economy. At the same time, we aggregate large sets of data reflecting our customers’ needs and their online behavior. By sharing and exchanging this Big Data we thus enable banks, financial institutions, e-commerce, and retail businesses worldwide to efficiently scale. They will get access to new customers unserved before, reduce risks while expanding to new markets, and understand their customers’ needs. MicroMoney ecosystem is constituted by combining financial services, Big Data, Blockchain technology and A.l. scoring for business. In giving Micromoney money to people, we use an app which gathers 10, 000 parameters and we analyze this Big Data using our Al Neural Network Scoring to approve loan within 15 seconds. Our products represent a digital financial identity encrypted on the Blockchain and Big Data gathered from borrowers’ smartphones. We are able to provide microloans to the unbanked and underbanked without a credit history, aggregating Big Data simultaneously. We are seeing a strong market uptake for this type of Big Data analytics from the financial, e-commerce, insurance and telecom industries. Therefore, Big Data is one of the main features in the implementation of microfinance business for MicroMoney.
Sai Hnin Aung — Founder of MicroMoney
Before stating the benefits of Big Data, it is important to know what Big Data is. Big Data is a collection of data from the traditional sources and digital sources that are inside and outside your company and represents a source for ongoing discovery and analysis. In other words, Big Data means an infrastructure to process large amounts of data in a fast way parallelized over a cluster of machines. In old days, it was not possible to work with a large amount of data. Year on year, with the proliferation of the internet, smartphones and other devices, more and more companies recognize the massive potential in using Big Data to bring real value for customers and improve efficiency. The usage of Big Data can be occurred in industries like Banking and Securities, Communications, Media and entertainment, Healthcare Providers, and Education. In the sector of Banking, every banking transaction deals with the massive amount of data so the banking industries maintain vast stores of information. By using data science to collect and analyze Big Data, almost all aspects of banking can be improved. The current Big Data projects in banking revolve around customers by driving sales, boosting retention, upgrading services and identifying needs. Data science can also lower risks in the areas as cards fraud detection, financial crime, credit scoring and stress testing.
Most companies believe that Big Data will make an impact to revolutionize their business. In banking and financial services, you can see how big data can make an impact in this sector. Big data analysis is helping them to know about the demographic details, transaction details, and personal behavior. Based on these data, banking companies can target their customers according to their interest and behavior. Almost all businesses involve risks. Risk management is one of the key areas where banking sector can save themselves from any fraud. For this case, the most important thing is to take help from the Big Data technology that gathers the previous record of the customers like loan data, credit history and the background data. According to the machine learning analysis, banking companies can detect the unusual behavior of customers and can blacklist their cards in time. One main task for banking and financial services is to regularly do compliance and audit for the data and finance. Big data can help them analyze the data and find the financial crisis and security issues. Banks have already started using Big Data to analyze the market and customer behavior.
It could be beneficial for e-commerce, telecom, and insurance industries as well. The data at MicroMoney’s disposal helps to facilitate access to a new audience, segment potential customers by interests, and effectively target consumer offers. Thus, the business gets an opportunity to reduce risks, and MicroMoney customers receive more advantageous consumer offers.
