With fraud being a major risk factor in e-commerce in the United States and Europe, new ideas on fraud prevention are needed, to counter the rising amount of online fraud. One of the newest ideas in doing this is using new technology to prevent fraud and identify fraudsters and potential areas for fraud before they can be used.
New solutions can help prevent fraud
For many companies, fraud is a major risk factor in their online and e-commerce options. Risk Ident, an Otto Group Company, was formed for the sole purpose of utilizing modern technology in the prevention of fraud. One of Europe’s largest e-commerce merchants, the Otto group have developed many internal solutions to combat fraud on their platforms, and have realized that their own technology can help other online fraud prevention applications as well, augmenting the services to prevent online fraud in a big way. Now, with a major move to helping others in their fight, Risk Ident have benefited from their collaboration with other companies, helping them to develop ways to solve the more complex problems of fraud.
Global online fraud is a reality
Online fraud is not a regional thing. With the advent of more cross-border commerce, a new type of cross-border fraud has developed, which is being felt around the world. Modern technology can now help businesses around the world in the secure processing of international data and transactions. There are many challenges within the European e-commerce market, with new emergent trends in fraud. An increase in the sophistication of fraudster’s techniques has been evident over the last two years, with many organized e-commerce models showing vulnerabilities in the online defenses of many companies. Fraudsters are continuously exploiting these weaknesses, and modern technology such as machine learning can help with fraud detection and prevention. Companies using these methods are being targeted by fraudsters using very sophisticated algorithms designed to counter the machine learning technology, putting many merchants at risk.
Better countermeasures are necessary
Merchants now need to have the even more sophisticated technology to counter these attacks. Public records and records from previous data breaches are freely available on the dark web, and data breaches are continuing to rise at a significant rate. Several trends are emerging that show more and more data breaches are being used to find new ways to commit fraud. For example, low-value fraud is often used to test the mechanisms of fraud detection in card payment technology, and if valid are then being used in high-value fraud. There are also examples of high-value merchants who see very few chargebacks. However, when a vulnerability is exploited, often it is done late on a Friday so that by Monday morning the companies have already registered a significant financial loss.
EMV and machine learning can detect fraud risk areas
The introduction of the EMV chip has meant that fraud has been pushed out of the high street and onto the web. With the European card-present market being much more secure than that of the United States, there is an opportunity to utilize that experience and technology in the U.S. market to help prevent fraud.
Machine learning is also a new option that can be used for the detection and prevention of online fraud. When used correctly, with the right sets of data, machine learning can act like a brain, giving out good results from the input of relevant data. However, if there is too much irrelevant data, the results can be catastrophic. In newer machine learning technology, like the ones introduced by Risk Ident, there is a specific core to the machine learning technology that includes the correct data relevance programs. It can reduce those grey areas that exist between accept and reject options by breaking down the risks identified. And while machine learning cannot remove the human element totally, there is concrete evidence that it can see patterns that are not noticeable to the human eye.
Data is the key to fraud prevention
Data is the key to everything, and software to prevent fraud and risk detection needs to be smarter, especially with tighter data control laws in Europe. Finding new ways to connect the limited data available requires the use of machines as well as human intervention. The workable data needed to detect and prevent fraud online is increasing with every sale or purchase, giving the machine learning programs more to work with, and improving the protection available.
Payment methods are growing and changing
The way society and people are ordering and paying for goods is changing, with more transactions being done using mobile payment options. This brings in new challenges in the long-term, including predictions in how this online spending will change in the future and investing in better fraud prevention technology. Shifts in customer spending patterns also create bigger competition between e-commerce companies vying for their custom, and with service providers and vendors. Biometrics and behavioral analytics are expected to become more common than fingerprint data, although many people may not keep up with the changing security features as the market changes. Looking forward, there is an expectation for frictionless transactions to move towards voice-activated technology, such as Amazon Echo and Alexa. Current fraud prevention methods will also need to change then, to take into account a change in the mechanisms of new payment options. And, as the number of customers increases, fraud prevention specialists will truly be challenged.
Related articles published in Cardholders Data security :
- Updates on the latest high-profile data breaches
- Payment card security compliance is directly related to the ability to defend against cyber attacks
- Merchant complacency in identifying international transactions
- Common sense measures to protect yourself against identity theft