One of the biggest advances in big data in recent years has come from the financial sector. This should come as no surprise to most, as there is incredible amounts of money to be made in finance. World markets run on data, with investors, funds, and governments all trying to use the information at hand to value investment and risk. Interpretting the data correctly can lead to billions of dollars in instant profits, while incorrect interpretations can ruin entire companies. A good exampe of this is Delta Airlines, who recently reported nearly half a billion dollars in losses after they misjudged oil data and made some bad hedges.
So how has big data transformed the industry, and where is it going?
The number one thing financial services have taken to using big data for is risk management. Large financial firms are constantly balancing the need to make profits off of investments, loans, and other tools with the need to avoid risks that could threaten the future of the company. A good example of this is the housing crisis of 2008. Many investment banks and firms did not have an accurate picture of the risk they were taking on, and this hole in the data led to some of the largest bankruptcies in US history.
Another breakthrough is in machine learning. Most financial experts use what is called technical analysis to detect patterns and trends in the financial sector. If you haven’t heard of technical analysis, the concepts, at least, are worth learning. Here is a good list of time-tested books I have read.
There are many patterns that a person could never notice without the help of big data. Patterns that point to specific things happening in world markets whenever another action happens elsewhere are a good example. Big data can conglomerate billions of data points and see what trends emerge that push markets higher, or drop them lower. Wall Street currently uses many such algorithms to make incredible profits, with limited risk.
The future of big data in the financial markets is vast. Many investment banks have been slow to start investing in big data techniques, preferring things such as intuition when making big decisions. Unfortunately these firms will slowly crumble as research and data eventually win out.
