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3 Big Data Analytics Use Cases Against Fraud

William Trotman
Marketing Director, Big Data & Analytics EMEA

Fraud is on the rise. And it’s costing us. Take a look at the numbers: 

In this article, Wiljo van Beek, Director, Big Data Banking & Insurancediscusses three fraud-related big data use cases in the realms of insurance, telecom, and healthcare. You'll discover how big data with analytics is a great weapon in the war to detect and prevent fraud. 

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Criminals are getting ever-more inventive. In response, companies have declared war against fraud and are using big data analytics as their weapon. By looking for hidden correlations across the immense volume of customer, market and third-party data at their disposal, businesses are beginning to detect suspicious behavior and prevent criminal activity. This can lead to immense cost savings, not to mention avoiding negative PR and a bad perception of your company. 

1. Insurance Fraud Big Data Use Case

The insurance industry is taking the lead in this regard. Many insurers now analyze their internal data, such as call center notes and voice recordings, alongside social media data and third party details on people’s bills, wages, bankruptcies, criminal records, and address changes to gain insight into potentially fraudulent claims.

For example, while a claimant may declare their car was damaged by flooding, their social media feed may indicate weather conditions were sunny on the day of the supposed incident. Insurers can supplement this data with text analytics technology that can detect minor discrepancies hidden in a claimant’s case report. Fraudsters tend to alter their story over time, making this a powerful tool in detecting criminal activity.

The insurance sector has traditionally analyzed fraud data in silos and largely ignored unstructured data points, but this is changing. According to Morgan Stanley, a more advanced analytics approach helps insurers improve fraud detection rates by 30%.

In addition to cost-savings, advanced analytics is  helping businesses to improve the customer experience and protect their brand reputation too. For insurers, fraud-related losses are not only detrimental to their finances but can lead to price increases for customers and lengthen review times for legitimate claims. Honest customers have little patience for this, so the ability to keep fraud to a minimum is crucial to keep turnover down. 

2. Telecom Fraud Big Data Use Case

The telecoms industry is also arming itself with data analytics to fight the estimated $38 billion it loses to fraud each year. Companies like Turkcell analyze billions of daily call data records alongside other customer data to build more complete user profiles. By comparing a customer’s recent activities with this highly detailed profile, Turkcell can detect irregularities more effectively and quickly. For example, many people who conduct subscription fraud tend to not pay their bills and exhibit suspicious long-distance calling patterns in the six months following an installation. Anomalous behaviors like these can inform predictive models and make the entire business better equipped to block criminal accounts.

Mobile operators are taking their data one step further, sharing smartphone GPS data with banks to help them monitor and prevent credit card fraud by verifying a person’s card use against their location. This is also reduces the need for credit card freezes, so customers who are on holiday or working abroad don’t have to deal with the frustration and time loss of contacting their bank.

3. Healthcare Fraud Big Data Use Case

Analytics is also being used to detect fraudulent claims in healthcare. The British National Health Service (NHS) recently deployed a new analytics infrastructure that has allowed it to identify roughly £100 million in potential savings following a reduction in benefit fraud and the risk of human error. In the digital space, online ticket exchange StubHub has reduced online fraud by 90% after implementing an analytics-based detection system.

Billions of dollars are being lost to fraudulent activity each year. Today, companies have the tools to combat this trend without compromising their service for customers. By using advanced analytics and detections systems to detect criminal activity more quickly, businesses are gaining ground in the fight against fraud.

From data scientists and analysts, who work closely with company data each day, to business leaders exploring new ways to improve the way they work, Oracle has a set of rich integrated big data and analytics solutions for everybody in your organization. 

Read our ebook, "Driving Growth and Innovation Through Big Data" to understand how Oracle’s Cloud Platform for Big Data helps companies uncover new benefits across their business.

By Wiljo van Beek, Director, Big Data Banking & Insurance, Oracle EMEA. You can follow him at linkedin.com/in/wiljovanbeek or @Lange_65.

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