Question

Identify the sources of external data. How is external data used? What is its advantage in the consideration of losses?

Answer 1

1. External data is any data generated from outside an organization. It can come from a variety of sources, and open data initiatives are now plentiful, making available a wealth of external data for analysis.

Some external sources include:

• Government sources, such as the U.S. Census Bureau
• Corporate filings, such as annual reports to the U.S. Securities and Exchange Commission (SEC)
• Trade, business and professional associations
• Media, including broadcast, print and Internet
• Universities
• Foundations
• Think tanks, such as the Rand Corporation or Brookings Institute
• Commercial data services, which are businesses that find the data for you

2. When people think of big data and analytics, it tends to be exclusively in terms of utilizing data they have collected themselves, such as customer journey, demographics, and so forth. The problem with this though, is that it doesn’t give you the full picture. In order to use data to its full potential, companies need to be collecting external data too, and incorporating it into their models for analysis.

One example of external data is weather, which is particularly useful in supply chain management. UK based supermarket chain Tesco, for example, is renowned for their use of weather data to drive richer insights that help them to predict sales and stock requirements. They reported in 2013 that they had managed to save £6m ($7.5m) per year and reduced out-of-stock by 30% on special offers. In fact, in a recent survey of supply chain professionals by the UK Met Office, 47% cited weather as one of the top three factors external to their business that drives consumer demand. Of these, 57% said they had better sales forecast accuracy, 51% that they had better on-shelf availability, and 43% that they had reduced waste.

3. Many financial services companies are now utilizing loss data for the purposes of calculating operational risk capital requirements, potentially arising from either regulatory requirements or indeed from a desire to integrate capital sensitive management within their organizations. Instinctively, the use of internal loss experience directly or as a means of deriving distribution parameters from which simulations can be made is most appealing. However, several factors mitigate against its effectiveness when considered alone: firstly, the data is backward looking based on historical events – the company profile may have changed, and should any large losses have occurred it is likely that controls will have been improved to prevent a reoccurrence. A greater problem nonetheless is that the regularly encountered losses may provide limited information on the size and frequency of large, rarely occurring losses that are the major factor in determining capital requirements. With this in mind organizations have recognized the value of obtaining loss data from outside their company, either through data sharing consortia or through publicly reported losses.