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SAS® Detection and Investigation for Government

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The nature of government programs requires collecting and processing enormous amounts of information. One of the biggest challenges for these systems is the integrity of the data itself. Data authentication, verification, standardization, integration and matching are required first steps to implementing an effective analytical fraud, waste and abuse solution. Without a trustworthy, single version of the truth, auditors and analysts cannot adequately protect government funds from improper payments.

SAS Detection and Investigation for Government helps governments detect and prevent both opportunistic and professional fraud through improved data effectiveness and analytics. You can standardize, integrate and authenticate data and consolidate program integrity activities. By harnessing your quantitative and qualitative data, you can better identify fraudulent activity and stop payments before they’re made.

Analytics helps government investigators identify abnormalities and patterns that may indicate fraudulent activity, for instance, by finding patterns and aberrations using visualization and analysis techniques. SAS calculates the propensity for fraud at each stage of a process with a fraud analytical engine that uses multiple techniques, including:
• Automated business rules  • Predictive modeling  • Machine learning  • Text mining

• Search and discovery within databases  • Exception reporting  • Network link analysis

• Artificial intelligence

Download the Whitepaper to know more.

My organisation’s data access is through:
ERPExcel files / AccessEmailsLog Books/ Hard CopiesCustom application (Please specify)

My organisation is looking for a Data Quality & Integration solution that will help us:
Address Data Quality issue and turn information in to mission critical intelligence for strategic business decisionsFetch departmental data from various 'source' systems to create a single version of truth

Which of the challenges are you facing in your organization? (Tick ALL applicable points)
Unable to tap into big data to surface unexpected insights for effective decision making`Lacking the ability to interact with data in a graphically driven, intuitive manner to identify new relationshipsUnable to interact with information on mobile devices for offline decision making


If you have an interesting article / experience / case study to share, please get in touch with us at [email protected]

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