3 Ways Real-Time Analytics Is Revolutionizing the Finance Industry

DZone 's Guide to

3 Ways Real-Time Analytics Is Revolutionizing the Finance Industry

Ever-increasing amounts of data are leading to widespread changes in how financial institutions operate. Here are three areas where transformation is crucial for the financial services industry.

· Big Data Zone ·
Free Resource

Financial services firms spent $6.4 billion on data-related programs in 2015, according to Accenture, and they predict this amount to grow at approximately 26% each year for the next two years. So, what are these firms spending their budget on? In a word: Transformation.

Today, financial services companies not only need access to vast amounts of data from a wider variety of sources in order to operate effectively but they also need to an extreme performance to leverage real-time analytics. Ever-increasing amounts of data are moving in real-time through networks, and in order to capitalize on that, stay relevant, and grow, financial services businesses need to develop their technical ability to operationalize data analytics.

This is leading to widespread changes in how financial institutions operate. Here are three areas where moving at the speed of business is crucial for the financial services industry.

1. Consumer Analytics and Engagement

Like many other industries, financial services companies are undergoing a revolution when it comes to using consumer data in order to hone their marketing efforts. Consumers are generating an estimated 2.5 exabytes of data every day, and finance companies are tapping into this ocean of information to get a sharper understanding of their customers. This is revolutionizing almost every function of the banking system, from how consumers use banking services to what services they are even offered in the first place. Offers and services are becoming more and more personalized, and as a result, are feeding into the data pool making them even more effective and efficient at extending the lifetime value of each customer.

2. Real-Time Fraud Detection

Fraud detection has always been a key function of financial institutions, ensuring that they operate with as few losses as possible. Today, financial institutions have to deal with fraud resulting from issues like identity theft and hacking of consumer information. And these threats are serious. For example, from accounting firm KPMG found that in the U.K. alone, the value of fraud cases reaching courts totaled $1.36 billion; an estimated 55 percent increase over the previous year.

Fortunately, real-time analytics is not only helping to reduce these threats but transforming how banks detect and manage them. There is actually an additional use for all that consumer data: Banks can now easily analyze and model customer behavior to identify when transactions are out of the ordinary. While this capability has existed in some form for some time now, real-time analytics have the potential to significantly reduce fraud using the larger amounts of data available as well as the technical capabilities needed to analyze the data.

3. Trading

Perhaps the area where real-time analytics has had the biggest impact so far is trading. Financial institutions can now take advantage of having access to both traditional and non-traditional data, and as a result, can make real-time market decisions based on information that is only seconds old. And because this data is often only valuable for a short time, being competitive on Wall Street means having the fastest means of analyzing it. Think about the stereotypical blue-jacket trader at the NYSE; those guys are now just 1s and 0s (sure, they still exist, but today the majority of trades occur electronically).

These are just a few examples of how real-time analytics is dramatically transforming the financial services industry. Banks, trading firms, and many other industry players are gaining competitive advantages by leveraging data to gain real-time insights, operational efficiencies, and business growth.

big data ,financial ,big data analytics ,real-time data

Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}