The Role of Big Data in Detecting Fraud

As the gathering of data becomes more integral to organizational operations, managing anti-fraud efforts is more essential than ever. In order to protect themselves and their customers, companies must take a proactive stance against fraudulent activity. The Canadian government recognized this need several years ago when it created the Proceeds of Crime (Money Laundering) and Terrorist Financing Act (PCMLTFA). In fact, a variety of organizations contribute to the objectives set forth by the Financial Transactions and Reports Analysis Centre of Canada (FINTRAC). Since criminals will continue to develop and refine deceptive practices, companies and the government must continue to reinforce actions against such tactics.

Understanding the Scope of Financial Fraud

It is vital not to underestimate the potential impact that nefarious financial activity can have, on institutions as well as on individuals. As this type of criminal pursuit evolves, more people and entities will be affected. As early as 2014, the rate at which fraud was being detected had grown from 24 to 35 instances for every 10,000 applications. Identity theft is among the top offenses in the realm of deceptive activities. Fraudulent mortgage applications are another major concern for financial institutions.

The most widespread issues seem to stem from third-party transactions. When examining the role of third-party involvement with regard to such acts, it appears that many who use commonplace financial products/services are at great risk. Such products/services might include loans, credit and debit cards, and savings options.

Using Analytics to Enhance Security

When exploring the topic of strengthening security, it is useful to acknowledge how Big Data can play a part in the movement to combat money laundering and other kinds of fraud. After all, such details are leveraged by criminals when perpetrating such offenses. Thus, various institutions need to consider the data they gather, as well as the systems they have in place to protect such information.

Consider these strategies for catching and preventing financial wrongdoing and identity theft:   

• Observing Patterns: Start by taking a look at ongoing patterns. Examining individual activity, along with industry trends, can provide useful insights related to emerging security threats.

• Performing Collective Analysis: Instead of simply monitoring information in isolation, your organization may be able to detect certain schemes more effectively when viewing data collected across several platforms. By doing so, such entities might discover relationships that could otherwise remain hidden.

• Flagging Potential Issues: Some of the behaviours that may be tracked include log-in speed and frequency, in addition to the geographical locations from which such log-ins take place. Red-flagging abnormalities may help to minimize the number of fraudulent acts overall. Financial groups and other entities can also implement algorithms to develop awareness of the habits of their customers. They can subsequently make note of odd inconsistencies as needed.

Utilizing Technology to Identify and Prevent Criminal Behaviour

Fortunately for companies and individuals, major advances are being made to modernize technology stacks. It is now possible for your organization to more accurately track, trace, and stop money laundering, and other kinds of fraud. Big Data technologies and methods are emerging to manage this process. Cornerstone® offers streaming ingestion capability and live monitoring, which can help you track deceptive activity in real time. Making use of such advancements will be imperative in the effort to secure the personal information necessary to conduct business.

Next Pathway is at the forefront of the digital transformation industry. Contact us today for more information about Big Data management and security.