Why Your Fraud Prevention Strategy Needs to Shift to Address Compromised Data
Compromised data relates to computerized information gained by theft or unauthorized access, attainment or release. Human error, transmission errors, software bugs, viruses, hardware malfunctions and natural disasters can also compromise data integrity. Your fraud prevention strategy needs to focus on compromised data because of this problem’s scale and effects.
Account for information compromised in a data breach or identity theft case.
Stealing information to commit financially motivated fraud is the goal of most data security breaches. With the data gained from a breach, a fraudster can make fraudulent purchases, siphon bank accounts, open new accounts and more — all as the result of identity theft.
Many companies are using Artificial Intelligence (AI) and machine learning to detect and prevent this type of fraud. Doing so allows them to validate transactions in near-real time through the recognition of data patterns.
But, this technology is only as good as the data that drives it. For that reason, it’s important to consider compromised data often results from identity theft, and your fraud strategy and AI models need to account for this fact.
With data driving artificial intelligence and machine learning models, if it’s corrupted, so are your means to detect potential fraud patterns. But, there’s a way to combat the compromised information that fuels your models and overall fraud prevention strategy.
Explore a fraud prevention strategy that combats compromised data.
While companies are focused on developing efficient, simplified ways to validate a customer’s identity, the abundance of breached data presents a real challenge. According to Statista, 1,473 data breaches in 2019 resulted in the exposure of more than 164 million sensitive records.
Compromised information can easily mask a user’s true identity and impede determining the transaction’s accuracy . The data can appear to be a match but, when using certain information to verify a user’s identity, it can be difficult to truly assess if the person using it is the true owner of that identity. These are cases of synthetic ID fraud.
Static data such as names, addresses, Social Security numbers or phone numbers can easily be stolen without the user knowing — at least until an identity theft protection solution alerts him or her to the issue. Because of this, it’s important to ensure your fraud prevention strategy includes detection for both static and dynamic data.
The one identifier fraudsters like to get their hands on is a user’s email address. The potential victim is generally notified of this as it’s happening. Fraud rings look for scalable tactics and, therefore, tend to shy away from email account takeovers because phishing scams and malware attacks are time-consuming.
Instead, one ploy fraudsters have resorted to involves creating an email address that looks like it could belong to the victim and then attempting to pass the new email off with the stolen information.
At Emailage, we use email addresses as the core data point that drives our predictive fraud risk analysis and scoring models. We connect that element to other information such as a customer’s name, phone number, IP address, device, and billing and shipping addresses.
Combined, this analysis renders a clear indication of whether or not the person engaged in the transaction is who he or she is purporting to be. The result is a frictionless customer experience that leads to increased conversion rates for real consumers and a reduction in fraud cases.
Emailage can outsmart fraud even when information is compromised.
Email addresses are at the core of how we help companies like yours enhance your fraud prevention strategy because of their ubiquity and relative security.
While the foundation is simple, enhanced machine learning and behavior analytics are built into our robust digital identity validation solutions to further improve hit rates in instances such as card-not-present fraud, chargebacks and synthetic ID fraud in a scalable fashion.
When compromised data is used, our state-of-the-art solutions impede fraudsters at account registration — or even earlier in the process. These tools can also enhance your strategy for fraud detection and prevention in the following ways:
- Complete identity validation based on data points such as email, phone, name, address and more
- Across-the-board risk assessment powered by holistic data points
- Network intelligence to monitor new threats in real time and provide an added layer of protection and velocity tracking
Explore our range of fraud management tools to see what best fits the needs of your business.
Email Risk Score delivers rapid reports on potential fraud risks to ensure you can approve or deny transactions with ease and certainty.
Portal 3 produces intuitive and instantaneous data visualizations within a comprehensive dashboard to help analysts detect fraud.