Blockchain Technology in Automobile Insurance Claim Systems Research

2021 ◽  
pp. 163-172
Author(s):  
Han Deng ◽  
Chong Wang ◽  
Qiaohong Wu ◽  
Qin Nie ◽  
Weihong Huang ◽  
...  
Keyword(s):  
Automobile Insurance ◽  
Insurance Claim ◽  
Blockchain Technology ◽  
Systems Research

A Comparison of State-of-the-Art Classification Techniques for Expert Automobile Insurance Claim Fraud Detection

2002 ◽  
Vol 69 (3) ◽  
pp. 373-421 ◽  
Author(s):  
Stijn Viaene ◽  
Richard A. Derrig ◽  
Bart Baesens ◽  
Guido Dedene
Keyword(s):  
State Of The Art ◽  
Fraud Detection ◽  
Automobile Insurance ◽  
Insurance Claim ◽  
Classification Techniques

scholarly journals Problems in Motor Insurance — Claim Reserves

1962 ◽  
Vol 2 (1) ◽  
pp. 152-160 ◽  
Author(s):  
Norton E. Masterson
Keyword(s):  
Statistical Estimation ◽  
Third Party ◽  
Estimation Methods ◽  
Automobile Insurance ◽  
Insurance Claim ◽  
Motor Insurance ◽  
Safe Side ◽  
Aggregate Loss ◽  
Settlement Property ◽  
Image Position

In his comprehensive paper entitled “A General Survey of Problems Involved in Motor Insurance”, Dr. Carl Philipson includes remarks with respect to mathematical reserves. The purpose of this paper is to discuss a method of statistical estimation of Third Party Motor Insurance claim reserves. These methods can also be used for Car Damage Insurance, since reserve determination for these rapid settlement property coverages is simpler than for Third Party lines.Dr. Philipson mentions the two main purposes of claim reservesbalance sheet loss reserves which shall be estimated on the safe side for financial reasons, and those reserves needed for risk statistics. In this paper I shall confine my subject to aggregate loss reserves for financial statements and internal management operating reports.In this paper, it will be convenient to refer to both European and U.S. terminology for Motor Car and Automobile Insurance.The comparable terms are:The accident year is the important fiscal period underlying not only the statistical estimation methods discussed in this paper but it is also the basic grouping of accidents in the official reserve tests required in the Annual Statements of U.S. companies for casualty and property lines. An accident year embraces the entire population of claims incurred with accident dates in a particular calendar year, whether reported to the company in that year or subsequently (i.e., incurred /not reported).

New Financial Technologies, Cryptocurrencies, Blockchain, and Challenges

2020 ◽  
pp. 85-102
Author(s):  
Burcu Sakiz
Keyword(s):  
Information Systems ◽  
Technological Innovation ◽  
Research Agenda ◽  
The Internet ◽  
Blockchain Technology ◽  
Systems Research ◽  
Information Systems Research ◽  
The World ◽  
Start Ups

As technological innovation transforms our economies, companies and start-ups all over the world are performing developments on financial technologies called “FinTech/fintech” for a chance to thrive. It even sparked the invention of blockchain and the inception of cryptocurrencies (digital/virtual money) such as Bitcoin. The blockchain technology provides Bitcoin's public ledger, an ordered and timestamped record of transactions. Blockchain is one of a kind decentralized technology mainly used by fintechs and it is a distributed as well as decentralized ledger that presents a radical, new, modern, and disruptive way of conducting all manner of transactions over the internet. Blockchain-based applications provide many opportunities to create a more sustainable world. With this research agenda, this chapter contributes to the discussion on future avenues for sustainability and information systems research on fintechs, especially cryptocurrencies and blockchain-based platforms and services.

Blockchain Technology for Fraudulent Practices in Insurance Claim Process

2020 ◽  
Author(s):  
Jaideep Gera ◽  
Anitha Rani Palakayala ◽  
Venkata Kishore Kumar Rejeti ◽  
Tenali Anusha
Keyword(s):  
Insurance Claim ◽  
Blockchain Technology

scholarly journals Blockchain Technology in Business and Information Systems Research

2017 ◽  
Vol 59 (6) ◽  
pp. 381-384 ◽  
Author(s):  
Roman Beck ◽  
Michel Avital ◽  
Matti Rossi ◽  
Jason Bennett Thatcher
Keyword(s):  
Information Systems ◽  
Blockchain Technology ◽  
Systems Research ◽  
Information Systems Research

scholarly journals Towards an understanding of technology fit and appropriation in business networks: evidence from blockchain implementations

2020 ◽  
Author(s):  
Stefan Seebacher ◽  
Ronny Schüritz ◽  
Gerhard Satzger
Keyword(s):  
Business Processes ◽  
New Technologies ◽  
Business Networks ◽  
Group Level ◽  
Blockchain Technology ◽  
Systems Research ◽  
Information Systems Research ◽  
Potential Factors ◽  
And Performance ◽  
The Impact

Abstract Existing information systems research thoroughly explains how task-technology fit and appropriation affect performance on an individual or group level. This was appropriate for many years, as technology is typically used to fulfill a certain task on these levels. Today, however, companies are tightly interconnected and rely on business networks to develop, produce, and deliver products and services. They collaboratively engage in joint implementation and utilization of new technologies that are applied and integrated into their business processes. These technologies, such as the newly introduced blockchain technology, operate across business networks and, thus, unfold their benefits not only on an individual or group level, but ideally on a network level. On this level, though, knowledge of the application and performance of information technology is still scarce. To drive the performance of technology in such networks, we investigate the impact of fit and technology appropriation on a network level. Due to the technology’s expected impact and characteristics, we select blockchain technology to explore potential factors, impacting fit, appropriation and, in turn, performance. We draw upon a set of interviews with experts that have implemented blockchain solutions in large business network settings. Based on our analysis, we propose a comprehensive model elevating the Fit-Appropriation Model to a network level. We contribute to the general understanding of technology utilization and performance by extending existing theory to a network-level perspective. Using insights on blockchain implementations as our empirical base, we also provide guidance to business leaders, intending to connect their partners through blockchain technology.

scholarly journals Zero-inflated and over-dispersed data models: Empirical evidence from insurance claim frequencies

2018 ◽  
Vol 84 (3-4) ◽  
pp. 103-128
Author(s):  
Imen Karaa ◽  
Habib Chabchoub
Keyword(s):  
Regression Models ◽  
Claims Data ◽  
Poisson Model ◽  
Insurance Premium ◽  
Automobile Insurance ◽  
Insurance Company ◽  
Insurance Claim ◽  
Sample Data ◽  
Claim Frequency ◽  
Over Dispersion

The main objective of this paper is to model automobile claim frequency by using standard count regression and zero-inflated regression models. The use of the latter model is mainly motivated by its ability to handle the over dispersion and zero-inflation phenomenon. The sample data consist of claims data obtained from one randomly selected automobile insurance company in Tunisia for a single year, 2009, containing beginning drivers and drivers who have had a license for less than three years. Our estimation results show that many exogenous variables can explain the frequency of claims; they are not taken into account in calculating the basic insurance premium. Moreover, the ZI binomial negative regression outperforms the standard count models and the ZI Poisson model in handling zero-inflated and additional over dispersed claim count data.

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