By using data-based tools to quantify and model risk, retailers can assign a value to the unknown, forecast the extent of potential financial damage, and determine what steps can be taken to prevent, manage, or transfer risk. In short, data and analytics can help drive intelligent business decisions and change.

In this issue of Taking Stock, we explore several ways retailers are using big data to minimize their total and economic cost of risk. For example, retailers are using data and analytics to:

  1. Organize and consolidate data.
  2. Capture and analyze potential volatility across risks.
  3. Forecast the probability of potential losses against comparable industry data.
  4. Identify potential risks, including those that haven’t historically led to losses.

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