Big Data is a platform for getting into new markets

When in use, MicroMoney deploys the most advanced technologies, which could be possibly available for markets. This means the techniques for collecting and handling of data on borrowers, as well as statistics on payday loans issued are processed by neural networks, and by artificial intelligence algorithms — while the maintenance of personal data and valuable information on the market in each region is based on the blockchain technology.
Since the company provides unsecured payday lending with no papers required — while working, in 90% of cases, with people who are taking credit for the first time in their life — it makes use of Big Data analytics tools to collect data about a future borrower from all available alternative sources. Instead of the dozens of inquiries and documents which are typically required in Asian countries to take out a loan, it’s enough just to gain an access to a customer’s mobile phone — since this contains lots of very precise and multi-detailed information.

Smartphones were chosen for several reasons. Firstly, smartphones have a high level of market penetration, even in countries with low banking facilities presence. For instance, while in Africa 80% of the population don’t have bank accounts, 63 in every 100 people do own mobile phones. Secondly, smartphones are more popular than laptops and desktops, and not only because they are cheaper — but also because each new smartphones generation is more powerful and functional than the previous one, which means that present-day laptops and smartphones have capabilities which are practically equal.
From a borrower’s perspective, the whole scoring process is rather simple: a client downloads the special MicroMoney app to his or her smartphone and signes an agreement with the company for personal data processing. The app helps to collect and integrate all available data from various sources. Firstly, these are money transactions (it’s very helpful here that each SIM-card owner in Southeast Asia equally owns an e-wallet), bank balances (in case SMS-banking is enabled), types of expenses, a search history on certain products in local online-retailers and many others things. Secondly, in many Asian countries Facebook is very popular, and for 95% users the whole Internet confines itself to Facebook. People literally live on there, posting about every little details of their lives — and this makes social network sites the most valuable source of information on all matters: about borrowers’ job situation (some people post even the cause of their dismissal), interests, date created (which proves that the person is real), trips, family status, relatives (who are persons of contact), accounts in other social networks etc.
When all the information is gathered together, the time comes to analyze it. The data is run through neural networks, while such BigData tools as statistics and analytics are put into operation automatically to prove a decision on the client’s reliability. If the evaluation is positive, the client can get a loan even without any paper records. The question of identification is resolved just as simply: money is deposited on a plastic card, which can be opened with just the original copy of a passport.
The entire operation — and hence the whole application processing — takes less than 5 minutes all in all. This should be also considered as a competitive advantage of MicroMoney. Technologies most notably let the companies cut their risks. Correlations, drawn by the Big Data-platform are rather precise: for example, someone who wastes money on alcohol, parties and fancy-yet-optional stuff like a new iPhone, is more likely to default on a loan. Yet the most valuable thing, when dealing with our borrowers’ problems (people who are often simply short of money for food) is not just a loan approval — it’s the creation of a high-profile client database for various regions. Absolutely all significant information about borrowers, as well as applications, granted loans and transactions the MicroMoney company keeps through a blockchain technology-driven database. This allows building a trusted and protected resource, which provides a basis for our own pool of credit histories — accelerating the process of decision-making while reducing risk.
The core of our user database is made up of reliable borrowers — those who take new loans in addition to successfully paying off their existing ones. Information on different customer segments can be extracted from this list — on gender, age, a purpose of the loan, etc. It also permits tracing correlation of these segments with borrower acquisition costs and service charges, as well as with risks (percent of overdue loan payments and defaults in each specific segment).
This information along with positive loan histories is available not only for MicroMoney but also for every financial and insurance company which would like to tap into a new market. Currently they have to spend immense amounts on new markets research and soft probes of borrowers, many of whom — from 65% to 80% — have no access to financial services due to the lack of credit history.
Meanwhile, the ‘unbanked’ (people who don’t have access to bank services) are a promising target audience for the lending industry. The fact is that its , according to Worldbank information, are people from 25 to 64, 35% of them are urban residents, with the majority having daily incomes of no more than 5$. 59% of them live in emerging countries with low or medium income, which are acknowledged to be the most interesting segment for involvement. With that, getting into such markets for financial companies is usually more problematic, since heavy risks and poor awareness of local clients hold them seriously back.
Thus, by utilising a platform for clients’ personal data collection and analysis MicroMoney shapes the legal market for creating and maintaining credit histories from scratch — and this will help other financial companies to gain entry into untapped markets. The client meanwhile not only gets a decision on their pressing issues — but also gets a start by means of a positive credit history, which allows them to go to any other bank with any other request. Lack of a credit history does not mean the client is unservable — and financial companies realize that.
The emergence of such products could lead to the possibility that banks and microfinance companies will start cutting rates — as soon as their risks reduce, and the cost of entering new markets (in Asia, Africa, or the Middle East) decreases. Access to the same credit histories can be given simultaneously to different players — which means quality-based competition for credit products will increase. New formats and new conditions for financial products may well emerge. For example, it’s likely there will be more opportunities for cash operations (account opening, quantity surveying for confirmation of credit etc), since salaries in emerging countries are prevalently paid out weekly and in cash.
After our credit histories product is finalized, we expect a surge of interest from banks, financial and insurance companies, since we’ll be doing their most risky job for them by sorting the informational wheat from the chaff.

Today BigData from MicroMoney is facing a new challenge. The company plans to emerge in the Initial Coin Offerings (ICO). A developed platform, databases of reliable clients and practical experience in blockchain technology will provide the basis for this program when raising funds.
