Actuarial Models for Understanding Driver Behavior with Telematics Data

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)

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Book Synopsis Actuarial Models for Understanding Driver Behavior with Telematics Data by : Banghee So

Download or read book Actuarial Models for Understanding Driver Behavior with Telematics Data written by Banghee So and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powered with telematics technology, insurers can now capture a wide range of data to better decode driver's behavior, such as distance traveled and how drivers brake, accelerate or make turns. Such additional information helps insurers improve risk assessments for usage-based insurance (UBI), an increasingly popular industry innovation. In this thesis, we first explore how to integrate telematics information to improve understanding of driver heterogeneity, as well as to better predict accident counts. For motor insurance during a policy year, we typically observe a large proportion of drivers with zero accidents, a less proportion with exactly one accident, and far fewer with two or more accidents. We introduce the use of a cost-sensitive multi-class adaptive boosting algorithm, which we call SAMME.C2, to handle such imbalances in a classification model. Using the SAMME.C2 algorithm, we find improved assessment of driving behavior with telematics relative to traditional risk variables. We next demonstrate the theoretical justification of the SAMME.C2 algorithm in two respects: (1) it is equivalent to Forward Stagewise Additive Modeling with exponential loss, and (2) it is a Bayes classifier. When cost-sensitive learning is added, we find the superiority of SAMME.C2 in controlling for issues related to class imbalances, especially when compared to just the SAMME algorithm. We performed numerical experiments to better understand the distinguishing characteristics of the algorithm. Finally, this thesis describes the techniques employed in the production of a synthetic dataset of driver telematics that is emulated from a real insurance dataset. The method uses a three-stage process that involves deploying machine learning algorithms. It is aimed to produce a resource that can be used to advance models to assess risks for usage-based insurance. It is the hope of this work to provide and encourage the research community to explore innovative methods relevant to such data. The synthetic dataset produced includes 100,000 observations about driver's claims experience (both claim counts and amounts were generated) together with associated classical risk variables and telematics-related variables. We further show, using visualization, model fitting, and data summarization, how remarkable the similarities are between the synthetic and the real datasets.

Telematics and Contextual Data Analysis and Driving Risk Prediction

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ISBN 13 :
Total Pages : 162 pages
Book Rating : 4.:/5 (125 download)

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Book Synopsis Telematics and Contextual Data Analysis and Driving Risk Prediction by : Sobhan Moosavi

Download or read book Telematics and Contextual Data Analysis and Driving Risk Prediction written by Sobhan Moosavi and published by . This book was released on 2020 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Characterizing driving style is about illustrating drivers' personalities and skills, by capturing variations in driving behavior that discriminate different drivers from each other. We propose a deep-neural-neural-network model to derive useful driving style information from telematics data.

Predictive Modeling Applications in Actuarial Science

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Publisher : Cambridge University Press
ISBN 13 : 1107029880
Total Pages : 337 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Predictive Modeling Applications in Actuarial Science by : Edward W. Frees

Download or read book Predictive Modeling Applications in Actuarial Science written by Edward W. Frees and published by Cambridge University Press. This book was released on 2016-07-27 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second volume examines practical real-life applications of predictive modeling to forecast future events with an emphasis on insurance.

Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance

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Publisher : Cambridge University Press
ISBN 13 : 1316720527
Total Pages : 337 pages
Book Rating : 4.3/5 (167 download)

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Book Synopsis Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance by : Edward W. Frees

Download or read book Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance written by Edward W. Frees and published by Cambridge University Press. This book was released on 2016-07-27 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.

Building Regression Models with SAS

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Publisher : SAS Institute
ISBN 13 : 1951684001
Total Pages : 464 pages
Book Rating : 4.9/5 (516 download)

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Book Synopsis Building Regression Models with SAS by : Robert N. Rodriguez

Download or read book Building Regression Models with SAS written by Robert N. Rodriguez and published by SAS Institute. This book was released on 2023-04-18 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advance your skills in building predictive models with SAS! Building Regression Models with SAS: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models: general linear models quantile regression models logistic regression models generalized linear models generalized additive models proportional hazards regression models tree models models based on multivariate adaptive regression splines Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.

Advancing Driver Behavior Modeling and Improved Driving Safety in the Age of Mixed Vehicle Automation Levels

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis Advancing Driver Behavior Modeling and Improved Driving Safety in the Age of Mixed Vehicle Automation Levels by : Yongkang Liu

Download or read book Advancing Driver Behavior Modeling and Improved Driving Safety in the Age of Mixed Vehicle Automation Levels written by Yongkang Liu and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the expectation of continuing to reduce the fatality rate and improve road safety, enormous efforts have been made by researchers and industries in the development of fully autonomous vehicles. However, not only because of the complex nature of driving, factors such as technical performance, cost barriers, public safety, insurance issues, legal implications, and government regulations also bring a large number of challenges in this process. Such factors clearly suggest it is more likely that early steps in this progression will be multi-functional vehicles with level 2 0́3 partial automation or level 3 0́3 conditional automation. It is expected that during this transition period, vehicles with different levels of automation and driver engagement will be mixed together to form large-scale traffic environments. Therefore, greater research and understanding are needed regarding the vehicle and driver monitoring in these mixed assistive driving scenarios to improve driving safety. Either by using the vehicle0́9s own sensors (e.g., Controller Area Network (CAN)-Bus, camera, accelerations, etc.) or combine information from other sources (e.g., Vehicle-to-Vehicle (V2V) communication, Vehicle-to-Everything (V2X) communication, etc.). Next-generation intelligent vehicles should have the ability to evaluate and understand the driver0́9s status, performance, and driving behavior. As a result, they could warn protentional risks, provide guidance when necessary (e.g., lane level guidance), and make essential adjustments or actions when critical. Three general research questions could be raised to achieve advancing driver behavior modeling and improved driving safety in the age of mixed vehicle automation levels, which are (i) how can we acquire sufficient data, (ii) how to evaluate and understand driving behavior, and (iii) how to deliver information to drivers. This dissertation presents the efforts focusing on the last two problems. A number of aspects regarding driving behavior modeling and understanding are discussed, which includes driving performance analysis using vehicle dynamic signals, exploring the effectiveness of transfer learning for risky lane change maneuver detection, a cause study of long-term lane change intention prediction, as well as estimate driver0́9s cognitive workload from the environment. After receiving prediction results, a driver visual guidance framework is designed to deliver warning or guidance information to drivers for better decision making. Taken collectively, these advancements contribute to improved driver analysis and modeling, environment understanding, improved safety, and therefore ensure a safe, comfortable, efficient driving environment during this transition period.

Effective Statistical Learning Methods for Actuaries I

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Publisher : Springer Nature
ISBN 13 : 3030258203
Total Pages : 441 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Effective Statistical Learning Methods for Actuaries I by : Michel Denuit

Download or read book Effective Statistical Learning Methods for Actuaries I written by Michel Denuit and published by Springer Nature. This book was released on 2019-09-03 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.

Loss Models

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Publisher : John Wiley & Sons
ISBN 13 : 0470391332
Total Pages : 758 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Loss Models by : Stuart A. Klugman

Download or read book Loss Models written by Stuart A. Klugman and published by John Wiley & Sons. This book was released on 2012-01-25 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.

Insurance Distribution Directive

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Publisher : Springer Nature
ISBN 13 : 3030527387
Total Pages : 439 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Insurance Distribution Directive by : Pierpaolo Marano

Download or read book Insurance Distribution Directive written by Pierpaolo Marano and published by Springer Nature. This book was released on 2021 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access volume of the AIDA Europe Research Series on Insurance Law and Regulation offers the first comprehensive legal and regulatory analysis of the Insurance Distribution Directive (IDD). The IDD came into force on 1 October 2018 and regulates the distribution of insurance products in the EU. The book examines the main changes accompanying the IDD and analyses its impact on insurance distributors, i.e., insurance intermediaries and insurance undertakings, as well as the market. Drawing on interrelations between the rules of the Directive and other fields that are relevant to the distribution of insurance products, it explores various topics related to the interpretation of the IDD - e.g. the harmonization achieved under it; its role as a benchmark for national legislators; and its interplay with other regulations and sciences - while also providing an empirical analysis of the standardised pre-contractual information document. Accordingly, the book offers a wealth of valuable insights for academics, regulators, practitioners and students who are interested in issues concerning insurance distribution.--

Modeling Driver Behavior and Their Interactions with Driver Assistance Systems

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Publisher :
ISBN 13 :
Total Pages : 125 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Modeling Driver Behavior and Their Interactions with Driver Assistance Systems by : Ning Li

Download or read book Modeling Driver Behavior and Their Interactions with Driver Assistance Systems written by Ning Li and published by . This book was released on 2019 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: As vehicle automation becomes increasingly prevalent and capable, drivers have the opportunity to delegate primary driving task control to automated systems. In recent years, significant efforts have been placed on developing and deploying Advanced Driver Assistance Systems (ADAS). These systems are designed to work with human drivers to increase vehicle safety, control, and performance in both ordinary and emergent situations. Current ADAS are mainly presented in rule-based or manually programmed design based on the summary and modeling of pre-collected human performance data. However, the pre-fixed system with limited personalization may not match human drivers' needs, which may arise the driver's dissatisfaction and cause ineffective system improvement. Human-centered machine learning (HCML) includes explicitly recognizing this human operator's role, as well as re-constructing machine learning workflows based on human working practices. The goal of this dissertation is to build a novel driver behavior modeling framework to understand and predict interactions with the driver assistance system from a human-centered perspective. It can lead not only to more usable machine learning tools but to new ways of improving the driver assistance systems. A driving simulator study was conducted to evaluate drivers' interactions with Forward Collision Warning (FCW) system. Gaussian Mixture Model (GMM) clusterization was used to identify different driving styles based drivers' driving performance, secondary task engagement, eye glance behavior and survey information. The impact of the FCW system on the different driving styles was also evaluated and discussed from three perspectives: initial reaction, distraction types, and safety benefits. A driver behavior model was also built using inverse reinforcement learning. Lastly, the timing prediction of FCW using driving preference was compared to the algorithm from a traditional FCW system. The findings of this study showed that ADAS without human feedback may not always bring positive safety benefits. Learning driver's preference through inverse reinforcement learning could better account for future scenarios and better predict driver behavior (e.g., braking action). This algorithm can be incorporated into real world in-vehicle warning systems such that the feedback and driving styles of the human operator are appropriately considered.

Determination of Driver's Behavior for Car-following Model Using GPS Data

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Publisher :
ISBN 13 : 9789745310681
Total Pages : pages
Book Rating : 4.3/5 (16 download)

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Book Synopsis Determination of Driver's Behavior for Car-following Model Using GPS Data by :

Download or read book Determination of Driver's Behavior for Car-following Model Using GPS Data written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Car following is the major driving task reflecting individual vehicle movements and interactions among vehicles in a single lane, resulting in overall characteristics of traffic flow. Thus, determination of the driver's behavior is fundamental to accurate explanation of traffic flow. In this research, the driver's behavior was determined under different traffic conditions in Thailand, especially expressway and surface street using GPS technology. The vehicle trajectories were collected by RTK-GPS device at 0.1 second interval with accuracy of less than +- 1 cm. The speed and acceleration profile were then constructed. Drivers behaviors described in the GM car following model parameters, namely reaction time and sensitivity parameters, were determined using Graphical method and Linear regression method, respectively. The results indicate that the reaction time of a driver varies by traffic and road conditions. In congested traffic condition, the reaction time for acceleration is longer than that for deceleration. However, the reaction time for acceleration is shorter than that for deceleration in uncongested traffic condition. The result of the 5th GM model calibration shows that the sensitivity parameter of drivers is inconsistent. Compared among subject drivers, some drivers are more aggressive in a more critical (close spacing, high speed) situation but less aggressive in a non-critical situation. The research brings about the better understanding of driver's behaviors.

Analysis of Driver Behavior Modeling in Connected Vehicle Safety Systems Through High Fidelity Simulation

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Publisher :
ISBN 13 :
Total Pages : 92 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Analysis of Driver Behavior Modeling in Connected Vehicle Safety Systems Through High Fidelity Simulation by : Ahura Jami

Download or read book Analysis of Driver Behavior Modeling in Connected Vehicle Safety Systems Through High Fidelity Simulation written by Ahura Jami and published by . This book was released on 2018 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: A critical aspect of connected vehicle safety analysis is understanding the impact of human behavior on the overall performance of the safety system. Given the variation in human driving behavior and the expectancy for high levels of performance, it is crucial for these systems to be flexible to various driving characteristics. However, design, testing, and evaluation of these active safety systems remain a challenging task, exacerbated by the lack of behavioral data and practical test platforms. Additionally, the need for the operation of these systems in critical and dangerous situations makes the burden of their evaluation very costly and time-consuming. As an alternative option, researchers attempt to use simulation platforms to study and evaluate their algorithms. In this work, we introduce a high fidelity simulation platform, designed for a hybrid transportation system involving both human-driven and automated vehicles. We decompose the human driving task and offer a modular approach in simulating a large-scale traffic scenario, making it feasible for extensive studying of automated and active safety systems. Furthermore, we propose a human-interpretable driver model represented as a closed-loop feedback controller. For this model, we analyze a large driving dataset to extract expressive parameters that would best describe different driving characteristics. Finally, we recreate a similarly dense traffic scenario within our simulator and conduct a thorough analysis of different human-specific and system-specific factors and study their effect on the performance and safety of the traffic network.

Traffic Safety and Human Behavior

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Publisher : Emerald Group Publishing
ISBN 13 : 1786352214
Total Pages : 1262 pages
Book Rating : 4.7/5 (863 download)

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Book Synopsis Traffic Safety and Human Behavior by : David Shinar

Download or read book Traffic Safety and Human Behavior written by David Shinar and published by Emerald Group Publishing. This book was released on 2017-06-22 with total page 1262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive 2nd edition covers the key issues that relate human behavior to traffic safety. In particular it covers the increasing roles that pedestrians and cyclists have in the traffic system; the role of infotainment in driver distraction; and the increasing role of driver assistance systems in changing the driver-vehicle interaction.

Heavy Vehicle Event Data Recorder Interpretation

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Publisher : SAE International
ISBN 13 : 0768092477
Total Pages : 316 pages
Book Rating : 4.7/5 (68 download)

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Book Synopsis Heavy Vehicle Event Data Recorder Interpretation by : Christopher D Armstrong

Download or read book Heavy Vehicle Event Data Recorder Interpretation written by Christopher D Armstrong and published by SAE International. This book was released on 2018-11-02 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last ten years have seen explosive growth in the technology available to the collision analyst, changing the way reconstruction is practiced in fundamental ways. The greatest technological advances for the crash reconstruction community have come in the realms of photogrammetry and digital media analysis. The widespread use of scanning technology has facilitated the implementation of powerful new tools to digitize forensic data, create 3D models and visualize and analyze crash vehicles and environments. The introduction of unmanned aerial systems and standardization of crash data recorders to the crash reconstruction community have enhanced the ability of a crash analyst to visualize and model the components of a crash reconstruction. Because of the technological changes occurring in the industry, many SAE papers have been written to address the validation and use of new tools for collision reconstruction. Collision Reconstruction Methodologies Volumes 1-12 bring together seminal SAE technical papers surrounding advancements in the crash reconstruction field. Topics featured in the series include: • Night Vision Study and Photogrammetry • Vehicle Event Data Recorders • Motorcycle, Heavy Vehicle, Bicycle and Pedestrian Accident Reconstruction The goal is to provide the latest technologies and methodologies being introduced into collision reconstruction - appealing to crash analysts, consultants and safety engineers alike.

Machine Learning in Insurance

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Publisher : MDPI
ISBN 13 : 3039364472
Total Pages : 260 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Machine Learning in Insurance by : Jens Perch Nielsen

Download or read book Machine Learning in Insurance written by Jens Perch Nielsen and published by MDPI. This book was released on 2020-12-02 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.

Actuarial Modelling of Claim Counts

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Publisher : John Wiley & Sons
ISBN 13 : 9780470517413
Total Pages : 384 pages
Book Rating : 4.5/5 (174 download)

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Book Synopsis Actuarial Modelling of Claim Counts by : Michel Denuit

Download or read book Actuarial Modelling of Claim Counts written by Michel Denuit and published by John Wiley & Sons. This book was released on 2007-07-27 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are a wide range of variables for actuaries to consider when calculating a motorist’s insurance premium, such as age, gender and type of vehicle. Further to these factors, motorists’ rates are subject to experience rating systems, including credibility mechanisms and Bonus Malus systems (BMSs). Actuarial Modelling of Claim Counts presents a comprehensive treatment of the various experience rating systems and their relationships with risk classification. The authors summarize the most recent developments in the field, presenting ratemaking systems, whilst taking into account exogenous information. The text: Offers the first self-contained, practical approach to a priori and a posteriori ratemaking in motor insurance. Discusses the issues of claim frequency and claim severity, multi-event systems, and the combinations of deductibles and BMSs. Introduces recent developments in actuarial science and exploits the generalised linear model and generalised linear mixed model to achieve risk classification. Presents credibility mechanisms as refinements of commercial BMSs. Provides practical applications with real data sets processed with SAS software. Actuarial Modelling of Claim Counts is essential reading for students in actuarial science, as well as practicing and academic actuaries. It is also ideally suited for professionals involved in the insurance industry, applied mathematicians, quantitative economists, financial engineers and statisticians.

Telematics Data in Motor Insurance

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Publisher :
ISBN 13 :
Total Pages : 169 pages
Book Rating : 4.:/5 (731 download)

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Book Synopsis Telematics Data in Motor Insurance by : Tobias Ippisch

Download or read book Telematics Data in Motor Insurance written by Tobias Ippisch and published by . This book was released on 2010 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: