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Risk Analytics Whitepaper

Improving your Insights into Risk with Historical Models

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The next step for Risk Management is using Data Science to find actionable insights in historical data.

See real-world applications of historical models in risk reporting

Historical Models refers to the new functionality available in Protecht.ERM that unwraps historical data to enable analytics involving point in time snapshots, trends and predictions with historical data.

With this graphical document, full of analytics screenshots, you will be able to see the value you can gain from Historical Models and ways of discovering valuable business insights.

What You Will Learn

  • What are Historical Models and why investigate the past?
  • Real World applications and use cases of Historical Models.
  • Applying Data Science and Predictive Analytics to provide business optimisation, prescriptive decision making and proactive real-time feedback.

About the Author

matthew-lee

Dr. Matthew Lee
 

Matthew joined Protecht in 2017 having extensive experience in senior roles within government and private organisations delivering large transformation projects, providing hands-on expertise and thought leadership in data and software.

He graduated with a PhD in Applied Mathematics in 2001 from the University of Wollongong and more recently with an Executive MBA in 2008 from RMIT.

Matthew managed the Business Intelligence and Analytics team that follow the Agile methodology to deliver high-quality Data Visualisations to clients via Protecht’s suite of software products including Protecht.ERM and Protecht.ALM.

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