Credit Card Fraud Detection Solutions To Secure Your Business

Complete guide on how to implement Credit Card Fraud Detection and Prevention solutions using advanced Machine Learning techniques. This is an updated version with new and improved content!

From the moment the payment systems came into existence, there have always been people who will find new ways to access someone’s finances illegally. This has become a major problem in the modern era, as all transactions can easily be completed online by only entering your credit card information. Even in the 2010s, many American retail website users were the victims of online transaction fraud right before two-step verification was used for shopping online. Organizations, consumers, banks, and merchants are put at risk when a data breach leads to monetary theft and ultimately the loss of customers’ loyalty along with the company’s reputation.

Unauthorized card operations hit an astonishing amount of 16.7 million victims in 2017. Additionally, as reported by the Federal Trade Commission (FTC), the number of credit card fraud claims in 2017 was 40% higher than the previous year’s number. There were around 13,000 reported credit card fraud cases in California and 8,000 in Florida, which are the largest states per capita for such type of crime. The amount of money at stake will exceed approximately $30 billion by 2020. Here are some most common credit card frauds statistics:

Can Fraud Analytics Be a Solution to the Problem?

Luckily, not only the criminals have access to evolving technology, but also the financial institutions have access; that’s why there is hope to reduce such terrifying statistics of crimes and provide a level of security higher than ever before. Fraud Analytics is a term that covers a number of quantitative sciences and disciplines to achieve a better understanding of financial fraud and how to deal with it.

Read the full article here: https://spd.group/machine-learning/credit-card-fraud-detection/