5 Steps to Prevent & Detect Fraud in Public Sector Using Data Analytics

Financial fraud can take many forms, and as fraudulent activities become more stealth and difficult to detect, public sector organizations are challenged to keep up. The key to fraud detection and prevention is building a robust data analytics strategy to understand your data, derive actionable insights, and mitigate the risks.

Implementing a data analytics strategy makes a profound impact: according to the Association of Certified Fraud Examiners (ACFE) 2018 Report to the Nations, organizations that implement preventive data monitoring detect fraudulent activity 58% faster and experience 52% lower losses than organizations that don’t.

Read this whitepaper to learn five actions that will help you face down fraud with data analytics. These actions, adopted by many private sector enterprises, are relevant for all government organizations that are committed to building a data-driven approach to reducing fraud.

  1. Identify fraud risk factors.
  2. Identify areas susceptible to fraud schemes.
  3. Understand relevant data sources.
  4. Mix, match, and analyze the data.
  5. Share insights and schedule alerts.

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