3 Ways to Use Big Data in FinTech
Financial technology, or FinTech, applies to any novation in the financial areas including investments, retail banking, lending and many other segments. With the internet and mobile revolution FinTech has turbulently grown. There has been an enormous breakthrough in nearly every single aspect of the financial technologies. It gets more investments, media coverage and adoption as never before.
Financial technology, or FinTech, applies to any novation in the financial areas including investments, retail banking, lending and many other segments. With the internet and mobile revolution FinTech has turbulently grown. There has been an enormous breakthrough in nearly every single aspect of the financial technologies. It gets more investments, media coverage and adoption as never before. Today I would like to focus on the role of Big Data when it comes to innovating the financial sector and I am going to describe the three uses of the data from the companies I am mostly familiar with.
This type of Application Programming Interface (API) is a way of communication with an online banking system, where a third-party can use the information about a customer stored in the banking system. A client should simply log in into the bank account and banking API does the rest of the work; it checks the balance of the account or extracts the summary of his transactions over a certain timeframe. Then this data is surpasses to a third party, a company that is interested in getting this type of data. The best thing about banking APIs is that all of the data is only passed through the user consent.
If you have not heard about this technology, you should definitely take a closer look into it. In the modern dynamic era, data sharing data is essential for the progress. Nevertheless, many financial organisations are still conservative and tend to skew the possibilities to share data with the outer world. With the help of such technologies as Kontomatik banking API, any financial institution is able to progress by obtaining an account holder’s KYC and transactional data. This information is a way to speed up many processes.
The biggest advantage of using such technologies, is that it provides a new level of comfort for the consumers, while the companies are able to bring in their financial services fully online. Another benefit of this technology is that the data is used to build a precise profile of a customer. One of the main challenges of big data is its quality, yet the information supplied via a banking API is of a prime quality, as it is already verified by a trusted party – the bank.
There are various companies that are benefiting from the banking API technologies already now. The main usage is seen in the online lending sector, as these companies need to perform credit scoring and KYC in a matter of seconds, and banking data is the best sort of big data for this purpose.
Market Sentiment Data For Investments
Another field where big data gets useful is trading. We all know that knowledge is power and, when used correctly, this power can lead to profits. Wealth management and trading are certainly important aspects of the financial innovation, these sectors have not used big data. Until now.
Investor sentiment, or market sentiment is crucial for measuring the investors’ attitude towards a security. It is vital to ‘feel’ the market and its participants’ sentiment to reveal the price motions.
With the help of Admiral Markets Sentiment widget it is possible to see the relations between short and long positions held by the other participants of the financial market. With this data and an investor is able to gather a good insight of the market’s mood. Such widgets work rather simple. A broker aggregates its own data based on the positions its traders hold. And then the broker displays this data in a form of charts. Typically each of the trading assets comes with its own sentiment chart, so it is possible to see the current “beliefs” of the investors.
With the help of big data aggregation in trading it is possible to achieve a better understanding of the market. This results in a more detailed analysis. Consequently, a broker that supplies such data may count for a larger success rate of its traders and, hence, obtain higher trading volumes. These volumes translate into profits.
Social Media In Credit Scoring
You should know that 73% of the world population is not scored in the credit bureaus. And those ones scored are mostly scored using some primitive factors. In most of the cases, only repayment history (the ability to make payments) is taken into account. Kreditech in its nature is placing the focus on your underlying personality based on a richer set of data. It uses the data from social networks and makes its analysis based on many personal factors. By scoring big data it is possible to actually achieve higher acceptance rate, while sustaining lower default rates.
Kreditech is aiming for the financial freedom by the use of technology. With the help of its unique scoring technology, the company is able to serve the people with little or no credit history as long as they are registered on facebook and other social networks.
Summing it all up
We live in the times when data becomes new oil. Some of the data is easily accessible, but hardly used. This is why such innovative fintech companies as Kreditech are able to design market-leading products simply by pulling the data from the social media. Other companies may be losing an opportunity by hiding their own data. Unlike those, Admiral Markets releases aggregated positions of its traders to offer additional information for investment decisions. Finally, while banks held the information of their clients under lock and key, there are such technologies as banking API that take this data away from the banks and power up financial organisations with the data of supreme quality.
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