This study proposes an efficacious approach to analyze the over-dispersed insurance frequency data as it is imperative for the insurers to have decisive informative insights for precisely underwriting and pricing insurance products, retaining existing customer base and gaining an edge in the...

This study proposes an efficacious approach to analyze the over-dispersed insurance frequency data as it is imperative for the insurers to have decisive informative insights for precisely underwriting and pricing insurance products, retaining existing customer base and gaining an edge in the...

We study a large intervention intended to reduce hospital readmission rates in Israel. Since 2012, readmission risk was calculated for patients aged 65 and older, and high-risk patients were flagged to providers upon admission and after discharge. Analyzing 171,541 admissions during 2009-2016,...

We study a large intervention intended to reduce hospital readmission rates in Israel. Since 2012, readmission risk was calculated for patients aged 65 and older, and high-risk patients were flagged to providers upon admission and after discharge. Analyzing 171,541 admissions during 2009-2016,...

In this paper, we propose models for non-life loss reserving combining traditional approaches such as Mack's or generalized linear models and gradient boosting algorithm in an individual framework. These claim-level models use information about each of the payments made for each of the claims in...

In this paper, we propose models for non-life loss reserving combining traditional approaches such as Mack's or generalized linear models and gradient boosting algorithm in an individual framework. These claim-level models use information about each of the payments made for each of the claims in...