Tools Used in Online Fraud Prevention

Published on: 2024-08-10 18:29:56

Antifraud covers a wide range of tasks. In e-commerce transactions, you need controls that prevent, or at least reduce, fraudulent activity. Here are some of the most common methods and platforms used for that purpose.

Payment gateway fraud tools

All payment gateways include basic fraud controls such as 3D Secure, AVS, and CVV checks. Some gateways also include more advanced controls, such as address verification or velocity checks.

Decisimo decision engine

Try our decision engine.

Data enrichment services

Data enrichment services help fill gaps in the data you have about your customers. They can provide information about a customer’s name, address, phone number, email address, social media profiles, and more.

Machine learning

Machine learning is a type of artificial intelligence used to detect patterns in data automatically. It can help identify anomalies in customer behavior, such as unusually high order values or unusually high shipping costs.

Chargeback prevention

Chargebacks happen when a customer disputes a charge with their credit card issuer. Chargeback prevention platforms can help you identify and flag potential chargebacks automatically, so you can act before they happen.

Fraud detection

There are many different fraud detection platforms available, like FraudLabs, Maxmind, and SEON. These platforms can help you flag orders that are likely to be fraudulent, so they can be reviewed manually.

Fraud prevention

Fraud prevention platforms can help stop fraud before it happens. They do this by sharing data about known fraudsters with other businesses.

Transaction Monitoring

Transaction monitoring is the process of continuously checking all transactions for fraud. It can be done manually or with automated platforms. Automated transaction monitoring platforms can flag potential fraud cases for manual review.

Case Management Tools

Each transaction flagged as potential fraud needs to be tracked in a system. Investigators reviewing those transactions need access to all relevant data, and they need to be able to collaborate or escalate to domain experts. If law enforcement becomes involved, the platform should be able to provide the full case file to support the investigation.

Conclusion

The most effective way to prevent fraud is to use a combination of these platforms. Using multiple methods gives you a clearer view of customer behavior and reduces the chance of fraud.

Decisimo decision engine

Try our decision engine.

Related Articles

  • How to integrate macaddress.io into a decision engine

    This guide shows how to connect macaddress.io to a decision engine and use MAC address data in automated checks. It walks through API key setup, data source configuration in Decisimo Portal, and adding the lookup to your decision flow.

  • Email address profiling

    Email address profiling is a low-cost, high-signal way to assess customer quality. In fintech and insurance, it can support credit risk and actuarial ML models. By extracting username features such as first or last name presence, numbers, nickname or gibberish indicators, and Levenshtein distances, along with domain signals such as MX or WHOIS deliverability, disposable email detection, and provider type, teams can improve scoring, fraud detection, and deliverability decisions.

  • What is a decision engine?

    See what a decision engine does and how it automates repeatable, data-driven decisions. It supports use cases like loan approvals, fraud checks, and customer service routing, producing consistent outcomes in real time or batches to improve accuracy and scale.

  • Antifraud articles

    This collection maps the core techniques, signals, and control points behind antifraud work. It covers device and browser fingerprinting, IP and email checks, rule engines, case management, and detection patterns for account takeover, synthetic identity fraud, merchant fraud, and bot activity.

  • Antifraud operations models

    Choosing an antifraud model starts with 2 questions: how much control you want, and how much fraud expertise you have in-house. This article compares outsourced, hybrid, and internal approaches, and shows where each model fits in eCommerce operations.