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ACCA Strategic Professional · Strategic Business Leader · Big data and data analytics

Brindle Insurance mines claims records, telematics from policyholders' cars and social media activity to detect patterns linked to fraudulent claims. Which use of big data analytics is this, and what does it mainly imply for the business?

This is predictive analytics. Brindle uses patterns in claims, telematics and social data to flag likely fraud earlier, reducing claims losses. The implication is a need to manage accuracy, false positives and privacy concerns, rather than simply reporting past totals or removing human investigators.

  1. ADescriptive analytics only, implying historic reporting of claim totals
  2. BPredictive analytics, implying earlier identification of likely fraud and lower claims losses, but requiring attention to accuracy and privacyCorrect
  3. CPrescriptive robotics, implying that human claims staff are no longer required
  4. DData warehousing, implying that no further analysis is needed

Explanation

Identifying patterns that indicate likely fraud is predictive analytics, giving earlier detection and reduced losses. It brings risks such as false positives and privacy concerns over social media and telematics data. Descriptive reporting only summarises the past, and staff are still needed to investigate.

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