Fraud is on the rise and has become a boardroom issue these days. Fraud happens in different parts of the world and fraudsters use very sophisticated and technology-enabled techniques. The scariest part is all of the possible ways that are vulnerable to fraud, such as fraudulent transactions (both online and offline), inaccurate credit applications, identity thefts, and false insurance claims.
Some of the major victims of fraud are credit card companies, insurance companies, retail merchants, telecom service providers, and business-to-business suppliers.
The Global Fraud Detection and Prevention Market is expected to grow rapidly during the 2013-2018 period, posting a CAGR of 16.4 percent. This is mostly thanks to the prevalence of fraud cases throughout the world, but also in part to emerging technologies that are making it easier and easier to detect and, more importantly, prevent fraud.
Introduction of IP-based Services
There is high adoption of IP-based communication services like VoIP by enterprises. These services expose the network to fraudsters and increase the chances of fraud attacks. This leads to many organizations to employ fraud detection software and hence is one of the major factors driving the growth of the market.
Emergence of Big Data Platforms
Fraud detection has been a major challenge in most industries because of the presence of huge volumes of data that could not be easily analyzed by analytic engines. However, with the introduction of big data, it is now possible to integrate and analyze huge amounts of data, both structured and unstructured.
This increases the capabilities of analytic engines to analyze data from disparate sources such as databases, social media sites, and blogs, and hence is driving the growth of the Global Fraud Detection and Prevention market using analytics.
Emergence of Analytics-as-a-Service (AaaS)
AaaS is a cloud-based approach to delivering analytic solutions. This approach allows organizations to deploy FDP solutions tailored to their business needs. This provides cost advantage and flexibility to organizations and offers low cost of ownership. However, data security is a major concern in this approach.
Increasing Use of Open-source Tools such as R and Hadoop
To gain a cost advantage, organizations are increasingly demanding open-source solutions for fraud detection. For instance, Hadoop from Apache helps to efficiently store and manage huge volumes of data, and R is a tool used for data manipulation, calculation, and graphical display.
These two open-source tools combined can help organizations overcome the complexity of processing huge volumes of unstructured data and analyzing social networks in a short span of time.
