Big Data in Finance


Big Data is a disruptive technology. It is changing major industries from the inside. In the next posts, we will learn how Big Data changes different industries.

Today’s focus: Big Data in Finance.

The finance sector heavily benefits from Big Data analytics. First, there is banking. Banks have large amounts of data on transactions that have to be processed every day. This data needs to be checked for fraud. Real-time analytics such as Apache Storm play a vital role in that process. To improve the security and detect fraud before it can happen largely decreases financial loss for them. But not only banks adapt Big Data for that: credit card companies such as Visa or MasterCard also apply these techniques in order to prevent fraud. A sample is when you travel: imagine you travel from New York to London. You didn’t pay anything during the trip with your credit card nor did you pay the travel itself with your credit card. Once in London, you get a coffee at the airport, but your credit card is rejected (or at least, authorization is required). In case you paid the trip with your credit card, the credit card company knows that you will be in London and can accept the payment.

Insurance companies face a similar problem with financial fraud. By analyzing data, the validity of a claim can be checked. Insurance companies can also lower their risk by analyzing data (and thus increase our bill)

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Published by

Mario Meir-Huber

I work as Big Data Architect for Microsoft. With this role, I support my customers in applying Big Data technologies - mainly Hadoop/Spark - for their use-cases. I also teach this topic at various universities and frequently speak at various Conferences. In 2010 I wrote a book about Cloud Computing, which is often used at German & Austrian Universities. In my home country (Austria) I am part of several organisations on Big Data.

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