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What’s the Difference Between Fraud Prevention and Fraud Detection?

Fraud prevention and fraud detection are two distinct but interconnected concepts representing mutually reinforcing strategies and approaches to combat fraud. Here's a breakdown of the differences. Fraud prevention is a set of policies and processes to reduce the risk of fraud before it happens, while fraud detection is the process of recognizing fraud as it’s happening so it can be stopped.

What is fraud prevention?

Fraud prevention focuses on implementing measures and controls that proactively reduce the likelihood of fraudulent activities occurring in the first place. This approach aims to create barriers and deterrents that make it difficult for fraudsters to initiate or carry out their schemes. Fraud prevention strategies include:

  • Authentication and authorization: Methods used to better ensure users are who they claim to be, such as two-factor authentication (2FA) or biometric identification.
  • Transaction limits and rules: Setting up rules and limits for transactions based on user behavior, location and transaction history to help identify and block potentially suspicious activities.
  • Encryption and security: Securing sensitive data and communications through encryption and robust cybersecurity measures to help prevent unauthorized access and data breaches.
  • Employee training: Educating employees about the types of fraud, warning signs and best practices to better recognize and prevent fraud.
  • Customer education: Educating customers about safe online practices, how to identify identity scams, and ways to better protect their personal information.
  • Fraud detection software: A set of data, technologies, algorithms and strategies combined to help identify and prevent fraud by differentiating risky transactions from legitimate ones.

Remember fraud prevention is an ongoing process that requires a combination of technology, policy enforcement and user education to be effective. Different organizations may need to tailor their strategies to their specific industries, user bases and risk profiles.

Learn more about fraud prevention for your business

What is fraud detection?

Fraud detection is a set of processes to help identify potential fraud risk by monitoring the customer lifecycle, including transaction activities, new account openings and account access requests.

Fraud can happen at any point in the customer journey, so it’s important to businesses and consumers that fraud detection is active at each point as well. The more business is served digitally and remotely, organizations and their employees and customers face increased risks. Fraudulent activities carried out by people, networks or automated bots focus attention at key points along the customer journey that demand protection. Broadly speaking, there are three main areas of risk to address with fraud detection:

  1. Account opening — Use of fraudulently obtained identity data (real or synthetic) to register or apply for services and open accounts.
  2. Account login — Accessing an account belonging to someone else for illicit gain.
  3. Account or transaction activity — Any business transaction in which fraud could occur, including account changes, applications, purchases, returns, claims or transfers.

Remember the effectiveness of fraud detection during these customer touchpoints may vary based on the specific context, data quality and the nature of fraud being targeted. A combination of multiple fraud detection techniques and continuous adaptation is often necessary to more effectively combat the ever-evolving fraud landscape.

Fraud prevention and fraud detection work together to combat fraud

Fraud prevention aims to create a secure environment that discourages cybercriminals from attempting fraud, while fraud detection focuses on identifying and responding to ongoing fraudulent activities in real time. Both prevention and detection are essential components of a robust fraud strategy —working together to reduce the risk and impact of fraud on individuals and organizations.


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