It’s only the second week of 2024, and we’ve already seen a major cyber fraud incident. The SEC’s Twitter account was hacked, and a fake announcement about a new Bitcoin ETF caused the cryptocurrency price to spike. This not only embarrassed the SEC but also made money for the hackers. To avoid such situations, businesses need to understand and use fraud scores to identify and prevent risks. Know more about Fraud Detection API Tools
What is an IP Fraud Score?
An IP fraud score is a number between 1 and 100 that shows how likely it is that a certain IP address is involved in fraud. A low number means low risk and a high number means high risk. This score is determined by considering various factors, including:
– Location of the IP address
– If the IP address matches the location of the user
– Whether the IP address is residential
Fraud scores help businesses spot and stop fraud before it causes financial and reputational damage.
Why is the IP Fraud Score Important?
- Protect Against Cyber Risks: Cyber risks include malware, phishing, and ransomware attacks. By understanding these risks, companies can take steps to prevent them.
- Real-time Action: Fraud scores let businesses react quickly to threats. Automated systems can instantly calculate the score and block high-risk transactions.
- Verify Customers and Partners: Fraud scores help verify the legitimacy of customers and partners, making transactions safer.
How to Calculate a Fraud Score
Every company has its method for calculating a fraud score, but most consider the following factors:
– Billing and Shipping Match: Does the billing address match the shipping address?
– Bank and Billing Match: Does the bank location match the billing address?
– IP Address and Billing Match: Is the computer’s IP address near the billing address?
– Proxy Detection: Is a VPN being used? This can signal a potential fraud attempt.
– Email Age: Older email accounts are usually more trustworthy.
Fraud Scoring Models
Companies use fraud scoring models to automate the process. Each factor is assigned a weight according to its significance. For example, detecting a proxy might be more significant than a billing and shipping match. Here’s what different scores could mean:
– 0-10: Very low risk of fraud
– 11-49: Low risk of fraud
– 50-69: Neutral risk
– 70-89: High risk of fraud
– 90-100: Very high risk of fraud
Automated fraud scoring helps businesses avoid chargebacks and other fraud-related issues. However, it’s important to use a reliable model to minimize false positives and avoid turning away genuine customers or partners.
Prevent Cyber Fraud with Trustpair
Cyber fraud can harm any business by exposing sensitive information and causing financial losses. Trustpair’s platform uses fraud scoring and other tools to protect companies from payment fraud. With reliable data, automated validations, and efficient workflows, Trustpair helps businesses stay safe.
Request a demo from Trustpair today to protect your business from cyber fraud.
