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Has data science changed the financial sector? And if so, how? Of course, data science in finance has changed the industry immensely!
From informing banks on how to provide low-risk credit to the stock market through machine learning algorithms, data science is reinventing the financial world! Watch this video to learn about all the other ways data science has changed the world of finance!
Since its inception, Data Science has helped transform many industries.
For decades, financial analysts have relied on data to gain valuable insights, but the rise of Data Science and Machine Learning has ushered in a new era in the field. Now more than ever, automated algorithms and complex analytical tools are being used hand in hand to stay ahead of the curve.
So let's take a look at the five ways financial institutions use these methods to their advantage!
Number 5: Fraud prevention
Fraud prevention is an area of financial security that deals with fraudulent activities such as identity theft and credit card fraud. Abnormally high transactions from conservative spenders or out-of-area purchases often indicate credit card fraud. When this is detected, the cards are usually automatically blocked and a notification is sent to the owner.
In this way, banks can protect their customers, but also themselves and even insurance companies, against enormous financial losses in a short time. The opportunity cost far outweighs the minor inconvenience of having to call or issue another card.
The role that data science plays in this comes in the form of random forests and other methods that determine whether there are enough factors to indicate suspicion.
Number 4: Anomaly detection
Unlike fraud prevention, the goal here is to detect the problem, rather than prevent it. The reason is that we cannot classify an event as 'abnormal' at the time it occurs, but can only do so in its aftermath. The main application of this anomaly detection in the financial world comes in the form of detecting illegal insider trading…
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