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How Machine Learning Helps Fraud Prevention

Thu, May 18 2017 | Author: PT. Central Data Technology

Any business is vulnerable to frauds and/or unauthorized intrusion. According to Ponemon Institute research conducted in US based companies, the average consolidated cost caused by security breaches grew from US$3.8 million to US$4 million. It is also reported that the average cost incurred for each lost or stolen record containing sensitive and confidential information increased from US$154 to US$158.

Frauds happened internally or externally. With the advancement in computer technology and e-commerce, the vulnerability to fraud also increases. Hackers are continuously finding new ways to target their victims, from stolen credit card details, to false accounts. Data breaches is now becoming a permanent risk organization need to be prepared to deal with.

In the industry, machine learning and big data are becoming and increasingly important tool to help businesses combat fraud. When deployed as a part of automated fraud screening systems, machine learning can help businesses to prevent breaches and give recommendations on mitigation steps needed.

CyberSource stated that machine learning relies on complex statistical methods and high computing power. By identifying the most influential cause-and-reflect relationships from the past, machine learning can create accurate predictions about the future.

Machine learning can become a powerful approach to fight frauds. Here are some benefits of using machine learning in fraud detection and prevention:

- Machine learning can facilitate real-time decision-making. By using rule-based systems to automatically accept or reject requests, machine learning helps evaluating huge amount for transactions or requests in real time.

- As technology advances, criminals also will find new ways to commit frauds. Machine learning can become a effective tools to use to detect new methods or unusual patterns that might be used to perform security breach.

- Security breaches changes methods in a very fast pace that humans might not be able to keep track. Machine learning is continously analyzing and processing new data, and automatically updating its models to reflect the latest trends.

- Significant advances in technology also have reduced the cost associated with machine learning solutions. As machine learning improves accuracy, it also reduce false positives that might by costly, and minimize the time and expenses of manual reviews.

Data is an organization's most valuable asset as it represents the entire history of the business and its interactions with the customers. Going through the digital transformation, companies should put more efforts in protecting their data. Not just defending their data from breaches, but also learn and predict future potential fraudulent activity and take steps to prevent it.