LexisNexis Risk Classifier – Stratifying Mortality Risk Using Alternative Data Sources
Munich Re assessed LexisNexis Risk Classifier, a predictive modeling tool developed and owned by LexisNexis Risk Solutions, Inc. that accurately stratifies mortality risk using public records, consumer credit history and motor vehicle history. Insurers considering alternative data-based mortality scores should begin with a retrospective validation study on their own experience data.
Classification Model Performance (Gen Re Risk Insights)
Insurers are increasingly developing prediction models to use in their insurance processes. Often these models are using traditional techniques, but more and more we see machine learning techniques being applied.
Big Data Sharing and Predictive Modeling: 5 Things for Regulators to Consider
The U.S. market is ready to realize this potential from these expansive technologies and networks but a regulatory pathway needs to be established to safeguard adherence to our core insurance principles and an individual’s right of privacy.
Predictive Modeling Case Study – Life Insurance Underwriting
Vince Granieri, FSA, MAAA, EA from Predictive Resources presents a case study of applying predictive analytics to a classical actuarial problem: life insurance underwriting.
LexisNexis Risk Classifier – An Effective Indicator of Mortality Risk (Munich RE)
Munich Re, US (Life) (Munich Re) assessed LexisNexis® Risk Classifier, which is a predictive modeling tool that was developed by and is proprietary to LexisNexis. LexisNexis allowed Munich Re access to the Risk Classifier in order to perform an objective review of its ability to accurately assess mortality risk using publicly available and easily obtainable non-biometric criteria.
Revolutionary: Eye on Big Data, Medicine and Underwriting
A multidisciplinary revolution is underway that bridges advances in IT, medical science and underwriting.
Is Automation Going to Put an End to the Underwriting Profession?
Recently, the jobs website CareerCast.com completed a study and published a list of the “10 Most Endangered Jobs of 2015." Right there at position #9 is the good ol’ insurance underwriter, with streamlined processes cited as the main culprit.
The Accuracy of Prediction Models in Life Underwriting
According to IBM, 90% of all the data in the world has been created in the past two years. Each of us is utilizing and providing data every time we log in to our computers, browse the Internet or simply drive down the highway with our iPhone in our pocket. The challenge for every industry is how to harness and effectively utilize that data to drive more profitable business.
Predictive Modeling in Underwriting (Slides)
Presentation given at the 2015 SOA Annual Meeting by Barry Senensky.
Underwriting Presentations from the 45 Annual M.U.D. Group Conference
Conference presentations have been posted at the M.U.D. Group website. They include:
- General Neurology: “Mind Bending” Underwriting Conundrums
- Medical Adherence: Practical Insight for underwriters
- Tumor Case Clinic: Breast, Prostate, Melanoma
- MVR's: Why Should I Care?
- Different Smokes for Different Folks
- Predictive Modeling in Underwriting: Proving The Science Behind The Theory - Mortality Implications and Correlations
- Multicultural Market and Foreign Risk Challenges - Ask the Experts