Description: The April 2016 Issue of The Modeling Platform

Description: We discuss the challenges of Excel usage in companies, and what needs to be considered in order to develop robust modeling governance.

Description: Software vendors participating in the A Comparative Analysis of Claims–Based Tools for Health Risk Assessment study were invited to submit comments on the study. In this document, MEDai comments on their contribution to the study's source data, and their results.

Description: The next evolution of actuarial systems in the U.S. will likely be a move toward a single system solution. This article defines a single system solution and illustrates how models can be shared across actuarial functions, the potential benefits of a single system solution, and describes potential mitigation strategies to address typical actuarial concerns.

Description: State regulators' review of predominant LTC Risks after review of year-end AG51 reports.

Description: Many top-performing businesses aren’t just risk aware, but rather risk intelligent. Such a posture helps prepare companies for a major event and can demonstrate to a regulator or auditor that an appropriately strong control framework is in place. Better still, companies gain real strategic value from a “risk adjusted” understanding not only of their threats and vulnerabilities, but also the upside opportunities associated with various risks. It starts with having both qualitative and quantitative information to identify, assess and manage risks. Strategic risk management, at its core, is about creating value by increasing transparency and accountability, and quality of information. More than a mere compliance exercise, effective risk management enables more informed strategic decision making, increased accountability and transparency, a greater likelihood of organizational success, and – ultimately – competitive advantage, as borne out by many studies that correlate risk management and financial results.

Description: This article explains how to create more maintainable models using abstractions by relating it to option, machine learning and machine intelligence models.