Who Owns the Technology, Owns the World

The phrase “He who owns the information, he owns the world” became famous thanks to the desire of the Rothschilds to be the first to know the news. Winston Churchill loved to repeat the same phrase. But all the great men said the phrase knew that information is only precious if you know how to use it further.

Our world thirsts for information. Just a couple years ago the worldwide market went crazy about Big Data and possibilities they might open but dreams became phantoms – no one knew how to work with all the collected information. Now the situation is totally different. There are a lot of tools to analyze the raw data and to turn them into the useful statistics and accurate forecasts now on the market. Companies can use this information to enhance their services, to automate processes, to gain insights into their target market and to improve the overall performance using the feedback they get.

For example, the online retail giant Amazon has access to a massive amount of data about its customers, what kind of purchases they make and what are they searching for. While this data is obviously put to advertising algorithms, Amazon also uses the information to improve customer relations, the area that many Big Data users overlook. General Electric uses the data from sensors on machinery like gas turbines and jet engines to identify ways to improve working processes and reliability. Starbucks uses Big Data to determine the potential success of each new location.

One more innovative and promising tool to transform the data from raw to useful is neural networks. Even though they have been established as the well-known method in business, there is enormous space for additional research, and here is the case to show it. In the Southeast Asia, the fintech company MicroMoney uses the neural networks and Big Data tools in its own scoring system for a rapid creditworthiness assessment of a client with no credit history. Instead of papers, certificates, and cross-checking scoring system analyzing personal data from a borrower’s smartphone. All that’s needed is to install the MicroMoney application, sign the agreement to use the personal data and to complete the loan application online. Then the scoring system analyzes all the available data, sets a credit rate and identifies potential credit risks with an accuracy of more than 95%. In case a customer reaches the certain credit score points the system approves the loan automatically and sends the money to a user’s e-wallet.

Scoring system constantly reviewing data within its increasing database. The more data processing, the faster and more accurate is the result of customer’s creditworthiness evaluation. In future self-learning algorithms can provide people with all kind of services even before they think about it. For example, a man announces in his social account that his wife is pregnant. This man is known as a reliable client of the MicroMoney, he has a high credit rating. The scoring systems catch this fact, correlate this information with his recent searches for houses to rent in search engines, evaluate his credit rate and he receives a special offer of mortgage for house buyers, with all interests and payments specified due to his monthly income. Or, let’s say, a girl is graduating with a bachelor’s degree with her marks higher than average score and searches for other universities to continue her education. The systems are able to analyze her bank account, to find that she has not enough money to enroll and offer her a student loan.

There is no doubt that these technologies can change not only banking industry but the way people consume, spend and save their money. We already face all benefits of targeting advertising but it is only beginning of the integration of smart technologies in our everyday life.

Disclaimer: The opinions expressed in this article do not represent the views of NewsBTC or any of its team members.  NewsBTC is not responsible for the accuracy of any of the information supplied in Sponsored Stories/Press Releases such as this one.

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