The Guide to Automating Fraud Prevention

As fraud rates continue to rise, companies are taking measures to protect their revenue and are increasingly looking for processes to automate. With the growth of generative AI, fraudsters are finding new ways to amplify their tactics. In 2022, fraud rates reached their highest levels yet, with the FTC reporting a 30% increase in losses compared to the previous year. Although the numbers for 2023 are still being calculated, it seems that fraud rates have reached an all-time high.

Risk, fraud, and payment teams must work more efficiently than ever. Business threats are becoming more common, while budgets are tighter than in the past. However, with new tools available, companies will likely lean on more automation in 2024 to increase accuracy and efficiency, reduce manual work, and allow teams to focus on higher-risk and complex cases.

The question is, how can teams evaluate what activities they can automate? Here, we’ll answer that with seven steps to determine how to incorporate automation into fraud-preventative measures.

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Role of automation in fraud prevention activities

Many teams are increasingly implementing automated processes to fill gaps in risk strategies and remove bottlenecks or lengthy manual processes. 

Here are a few examples of how teams are using automation:

  • Processing and analyzing data. AI and machine learning can be leveraged to process patterns, identify anomalies, and flag suspicious transactions or activities.


  • Enhanced accuracy. Automated machine learning algorithms can learn from past data and adapt to changes in fraud patterns. This ability to learn contributes to reducing false positives since it can adjust detection criteria based on past decisions, removing the need for fraud analysts to identify patterns on their own, which is often slower and less accurate.


  • Streamlining case management. Routine tasks and workflows can be automated, such as data collection, documentation, and reporting. This leaves room for fraud analysts to focus more on investigating and resolving complex cases.

By leveraging automated systems, companies can enhance their fraud prevention capabilities and mitigate the risks associated with fraudulent activities.

Seven steps to evaluate and implement automation

We recommend these seven steps to get started:

1. Identify existing processes

Start by identifying the different processes and tasks of your fraud prevention activities. Create a comprehensive list of jobs done manually or with minimal automation. This can include fraud detection, authentication, verification, or transaction monitoring. Collect this data so you can compare it with automated alternatives in the future.

‍2. Evaluate repetitive and rule-oriented tasks

Such tasks primarily involve data processing, analysis, or documentation, often ideal for automation. Examples include data entry and validation, fraud detection, and report generation. Prioritize processes based on potential impact and complexity.

3. Determine complexity and feasibility

When identifying processes to automate, it is important to consider their complexity and feasibility. Questions to ask are how available and accessible your data is, if it’s compatible with automation tools, how it will impact other interconnected processes, and if it will cause too much friction.

4. Clearly define your objectives

Objectives can include increased accuracy, faster response time, cost reduction, and improved scalability. By setting clear objectives, you can ensure that your automation efforts are aligned with overall business goals.

5. Research tools and carefully choose what’s best for your business

When selecting tools, there are a few important questions to ask:

  • How does the automated process compare to manual processes in terms of cost?
  • How quickly does the system process and deal with potential fraud cases?
  • How accurately does the automated system identify and flag fraudulent activities?
  • Can the automated system handle a growing volume of transactions without compromising performance?

6. Pilot automation with a small subset

When introducing automation, you might want to pilot a small subset of data or processes before full implementation. Doing so allows you to test automation’s feasibility, effectiveness, and efficiency while minimizing potential risks or disruptions. After the pilot, evaluate the results and make any necessary adjustments before scaling up the automation to more extensive operations.

‍7. Continuous evaluation and improvement

Monitor and evaluate automated processes regularly using metrics and user feedback. Adapt and optimize as needed to ensure efficiency and effectiveness, and be open to making iterations for improvement.

Remember, automation is an ongoing process, and identifying automation opportunities requires a combination of analysis, collaboration, and experimentation. By continuously assessing, improving, and adopting automation, you can optimize your fraud prevention activities and achieve better results.


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‍Want to learn more about increasing efficiency?

Fraud and risk departments work hard to protect businesses, and automation can significantly enhance effectiveness. Identifying opportunities for automation requires a careful analysis of your fraud prevention activities, collaboration with your team, and experimentation. By continuously assessing, optimizing, and adopting automation, you can improve your fraud prevention strategies and achieve better results. Remember, It is an ongoing process that requires constant attention and effort, but the benefits are worth it in the long run.

Learn 12 more ways you can optimize your fraud investment in 2024.

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