Verisk, a leading data analytics provider, announced the release of Life Risk Navigator, an innovative, cloud-based stochastic risk modeling platform that offers in-depth portfolio analytics which can enhance risk selection, quantify changes in mortality rate, improve hedging strategies, and drive better financial decision-making. The cutting-edge analytics provided by Life Risk Navigator are driven by Verisk’s Life Risk Models, a comprehensive set of probabilistic risk models that simulate mortality trends, causes of death, and excess mortality events at a granular level.
“As the life insurance industry undergoes a digital transformation, the demand for modern analytics platforms has grown significantly,” said Maroun Mourad, president, global underwriting at Verisk. “Life Risk Navigator brings together a robust modeling suite and allows organizations to streamline their pricing, ERM, and portfolio optimization workflows into a single platform.”
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The web-based Life Risk Navigator was built to consider the workflows of life insurers, annuity providers, and reinsurers. It enables insights across a full probability distribution of risk, capturing uncertainty and offering insight into correlations between policies and portfolios. This full range of tail risk metrics enables portfolio benchmarking, optimization, and Solvency II modeling. By capturing trend risk at an individual level, regardless of the granularity of data inputs, the platform diminishes adverse selection and can enhance profitability through greater pricing precision.
Verisk’s Life Risk Models are now available in the Life Risk Navigator platform. The comprehensive set of models allow users to access targeted analytics in a single tool to make efficient risk selections. The Mortality Projection Model, part of the risk model set, provides mortality assessments categorized by age, s**, and cause of death.
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The model simulates causes of death for each age and s** specifically, considering socioeconomic and related risk factors and accounting for medical advancements and changing lifestyles informed by peer-reviewed epidemiological studies and statistics from relevant ministries and departments of health. Changes in mortality risk based on associated biomedical factors are explicitly modeled—such as smoking status, diabetes, body mass index—incorporating not just the overall trends in mortality, but the weighted contribution of each risk factor to potential mortality improvement for each cause of death over time.
“Backed by AIR Worldwide, a trusted leader in risk modeling and analytics, our Life Risk Models go beyond traditional actuarial methods to explicitly capture dynamic mortality and morbidity risk associated with changing habits and lifestyles, as well as excess mortality events,” continued Mourad. “By incorporating this detailed understanding of the drivers of mortality risk and possible trends over a policy’s lifecycle, life insurers and annuity providers can make better risk management decisions that align with strategic goals.”
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