Behavioral Analytics and the Banking Industry

The advances in artificial intelligence and machine learning has brought about sweeping changes to how we do things with data. One way this has manifested is through how we use big data. Open Source defines big data as data that is too large and complex for human minds to interpret, thus needing the aid of various machines to process and utilize this information. Through big data, many fields have taken significant leaps into improving how they do things. One such field is risk management.

Despite it being around way before big data, there’s no doubt how much this innovation has changed the entire landscape of risk management. Companies such as IBM have already incorporated big data into the discipline of risk management. They use the advances in data analysis and cognitive computing to further their understanding of potential risk factors, and more companies are taking notice. The banking industry has also had its eyes on behavioral analytics in hopes of bolstering their risk management efforts. Read on to know more about the impact of behavioral analytics on the banking industry!

Fraud Detection

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Fraud detection is vital to any financial institution. Big data helps with this as it allows these institutions to detect anomalous changes in user activity, that could hint at something more malicious happening behind the scenes. ZDNet details how through the use of big data and data analytics, financial institutions can preserve the “instant transaction” user experience, as they’ll be able to prevent and detect potential fraud in real-time. Variables that could raise red flags include geolocation, the type of device being used, and the amount involved in the transaction.

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Predictive Analytics

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Another aspect that big data has changed when it comes to risk management is the use of predictive analytics. With Maryville University outlining how the U.S. business data analytics market is worth more than $95 billion this year, this new type of analysis is having a huge impact on how the corporate world operates. The importance of data analytics for any business is that it allows them to delve deep into the data for forecasting and predictive analytics purposes. This lets them assess and detect risks. They can use this data to design models to help determine relationships between behavioral factors which will help identify the risk presented in any given situation. Live Mint explains that banks utilize data on whether or not customers pay their bills on time or is a frequent loan defaulter to gauge the creditworthiness of a potential borrower.

Aid in Decision Making

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Lastly, big data can aid banks and financial institutions during the decision-making process as it can be integral for assessing risk. Finance experts from MIT Sloan highlight how much a difference data makes when it comes to risk management, as it helps lay down all variables that need to be considered so that big companies can make the right decision to expand further. This applies more to institutions with a wider reach such as Exxon, because they have access to more data — which in turn makes their projections more accurate. Banks have also harnessed behavioral analytics for this purpose, placing them on the cusp of major industrial transformation. They’ve begun to use data to mitigate risk when making both minute and major decisions.

So there you have it, three major ways that behavioral analytics is changing the banking industry. If you found this beneficial, check out our article on What is Digital Behavioral Intelligence? to further understand how technology is changing the way we utilize data.

By: Skylar Stella

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