Results 1 to 10 of about 6,133 (181)
Case study data for joint modeling of insurance claims and lapsation [PDF]
Data in Brief, 2021 The dataset tracks 40,284 insurance clients over five years, between 2010 and 2015, who subscribed to both automobile and homeowners insurance. We have combined information on these customers.
Montserrat Guillen +3 more
doaj +2 more sources
Ratemaking as Climate Adaptation Governance [PDF]
Frontiers in Climate, 2021 Electric utilities are directly affected by, and in some cases are a source of, many pressing climate adaptation challenges: wildfires, vulnerable infrastructure, extreme storms, and drought. The state Public Utilities Commission (PUC) is one of the most
Jonas J. Monast
doaj +2 more sources
Cyber Insurance Ratemaking: A Graph Mining Approach [PDF]
Risks, 2021 Cyber insurance ratemaking (CIRM) is a procedure used to set rates (or prices) for cyber insurance products provided by insurance companies. Rate estimation is a critical issue for cyber insurance products.
Yeftanus Antonio +2 more
doaj +3 more sources
Machine Learning in Ratemaking, an Application in Commercial Auto Insurance
Risks, 2022 This paper explores the tuning and results of two-part models on rich datasets provided through the Casualty Actuarial Society (CAS). These datasets include bodily injury (BI), property damage (PD) and collision (COLL) coverage, each documenting policy ...
Spencer Matthews, Brian Hartman
exaly +3 more sources
Pricing weekly motor insurance drivers’ with behavioral and contextual telematics data [PDF]
HeliyonTelematics boxes integrated into vehicles are instrumental in capturing driving data encompassing behavioral and contextual information, including speed, distance travelled by road type, and time of day.
Montserrat Guillen +2 more
doaj +2 more sources
Risks, 2020 This article presents the Poisson-Inverse Gamma regression model with varying dispersion for approximating heavy-tailed and overdispersed claim counts. Our main contribution is that we develop an Expectation-Maximization (EM) type algorithm for maximum ...
George Tzougas
exaly +3 more sources
A priori ratemaking using bivariate poisson regression models [PDF]
Insurance: Mathematics and Economics, 2008 In automobile insurance, it is useful to achieve a priori ratemaking by resorting to gene- ralized linear models, and here the Poisson regression model constitutes the most widely accepted basis.
Bermúdez, Lluís +1 more
core +7 more sources
Crop Insurance Premium Ratemaking Based on Survey Data: A Case Study from Dingxing County, China [PDF]
International Journal of Disaster Risk Science, 2015 Tao Ye
exaly +2 more sources
GEOGRAPHIC RATEMAKING WITH SPATIAL EMBEDDINGS [PDF]
ASTIN Bulletin, 2021 AbstractSpatial data are a rich source of information for actuarial applications: knowledge of a risk’s location could improve an insurance company’s ratemaking, reserving or risk management processes. Relying on historical geolocated loss data is problematic for areas where it is limited or unavailable.
Christopher Blier-Wong +3 more
openaire +3 more sources
RISK FACTORS SELECTION WITH DATA MINING METHODS FOR INSURANCE PREMIUM RATEMAKING [PDF]
Zbornik radova Ekonomskog fakulteta u Rijeci : časopis za ekonomsku teoriju i praksu, 2020 Insurance companies that have adopted the application of data mining methods in their business have become more competitive in the insurance market. Data mining methods provides the insurance industry with numerous advantages: shorter data processing ...
Amela Omerašević, Jasmina Selimović
doaj +1 more source