(Image source: Verisk.)
Verisk (Jersey City, N.J.), a provider of data analytics to the insurance industry, has released Life Risk Navigator, which the vendor describes as a 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 analytics provided by Life Risk Navigator are driven by Verisk’s Life Risk Models, which the vendor calls 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,” comments Maroun Mourad, president, global underwriting, 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.”
Verisk says the web-based Life Risk Navigator was built to consider the workflows of life insurers, annuity providers, and reinsurers. The vendor says the solution 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,” the vendor statement says. “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 Life Risk Models
Verisk’s Life Risk Models are currently available in the Life Risk Navigator platform. The models are designed to 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, sex, and cause of death. The model simulates causes of death for each age and sex 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,” adds 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.”