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Your Reputation Hides within Your Mobile Phone

newsbtc
newsbtc
Last Updated: September 30, 2019 11:36 am
2 mins read
banking, financial inclusion, micromoney, mobile, banking, credit

Reason to trust

Strict editorial policy that focuses on accuracy, relevance, and impartiality
Created by industry experts and meticulously reviewed
The highest standards in reporting and publishing
How Our News is Made

Strict editorial policy that focuses on accuracy, relevance, and impartiality

Ad discliamer

Morbi pretium leo et nisl aliquam mollis. Quisque arcu lorem, ultricies quis pellentesque nec, ullamcorper eu odio.

A mobile phone is your friend, business assistant, a way to connect your dear ones, and even a boss sometimes if you set the alarm on. However, what if your phone can be a reputation tool able to give you an access to the services never available for you before?

MicroMoney, a global fintech blockchain company and lending services provider, has found a way to turn a mobile phone into a tool to build and prove your reputation that can make a revolution in the lending and many other industries. They designed a new scoring system based on all data received from a mobile phone and analyzed by machine learning and artificial intelligence tools. Therefore, the company does not need any paper documents from its borrowers and no collaterals, by the way. A customer should just complete an application form within a special mobile application. By ticking a certain box in the app client agrees to process and assess all the data from his or her mobile phone. The system approves a loan and sends the money to a borrower’s e-wallet.

That seems to be much easier and simpler way to get a loan, isn’t it? However, behind the scenes are some sophisticated technologies making all the work done. One of them is neural networks technology.

When the agreement received, the system gets all data from all the sources available from a mobile phone: contacts, messages from banks, all the information from the user’s social accounts and even games and apps downloaded and the music playing often. Almost everything. The system compiles all these components and processes them through neural networks and Big Data tools, assigning each piece of data some points of a credit score, drawing an individual picture of a person applying for a loan.

Has a job? High points. Has the same job in the online application form completed and in your Facebook account? Higher points! Listening to hip-hop? Fewer points (sorry, hip-hop fans). Completes the form very slowly, doubting what to write in each field? Very low points.

Then the system counts all the points achieved altogether. If the score reaches the certain rate set by the company, the system approves the loan automatically and sends the money out.

There is no way to cheat the system. For example, if a client gives false information about age, occupation or loan purpose, the system will check all customer’s accounts to compare the data given and in case they are different a client will get a lower score or even a signal for the AI to reject the application immediately.

With the ability of the company’s system to capture data, the company can be secured and work conscientiously with responsible borrowers, who get benefits from using this application. And this way obviously makes it convenient for both.

It’s time to think about a new role for your mobile phone and start to respect it as a key to your reputation asset!

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Disclaimer: The information found on NewsBTC is for educational purposes only. It does not represent the opinions of NewsBTC on whether to buy, sell or hold any investments and naturally investing carries risks. You are advised to conduct your own research before making any investment decisions. Use information provided on this website entirely at your own risk.

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Reason to trust

Strict editorial policy that focuses on accuracy, relevance, and impartiality
Created by industry experts and meticulously reviewed
The highest standards in reporting and publishing
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Strict editorial policy that focuses on accuracy, relevance, and impartiality

Ad discliamer

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