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Abstract

Details

Quantitative and Empirical Analysis of Nonlinear Dynamic Macromodels
Type: Book
ISBN: 978-0-44452-122-4

Article
Publication date: 22 August 2008

Angel E. Muñoz Zavala, Arturo Hernández Aguirre, Enrique R. Villa Diharce and Salvador Botello Rionda

The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.

Abstract

Purpose

The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.

Design/methodology/approach

This paper introduces a hybrid approach based on a modified ring neighborhood with two new perturbation operators designed to keep diversity. A constraint handling technique based on feasibility and sum of constraints violation is adopted. Also, a special technique to handle equality constraints is proposed.

Findings

The paper shows that it is possible to improve PSO and keeping the advantages of its social interaction through a simple idea: perturbing the PSO memory.

Research limitations/implications

The proposed algorithm shows a competitive performance against the state‐of‐the‐art constrained optimization algorithms.

Practical implications

The proposed algorithm can be used to solve single objective problems with linear or non‐linear functions, and subject to both equality and inequality constraints which can be linear and non‐linear. In this paper, it is applied to various engineering design problems, and for the solution of state‐of‐the‐art benchmark problems.

Originality/value

A new neighborhood structure for PSO algorithm is presented. Two perturbation operators to improve PSO algorithm are proposed. A special technique to handle equality constraints is proposed.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 1 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 1 January 2001

William Blair QC and Cheong Ann Png

The governance of financial markets is approached at various levels. National regulators are charged with the responsibility for maintaining a system of regulation for the…

Abstract

The governance of financial markets is approached at various levels. National regulators are charged with the responsibility for maintaining a system of regulation for the purpose of ensuring stability and confidence in the financial markets. This has to be done according to ascertainable standards. Within the European Union, directives and regulations provide a framework for approximating practices within its member states. At the international level, organisations such as the Bank of International Settlements (BIS), the International Monetary Fund (IMF) and the Organisation for Economic Cooperation and Development (OECD) have developed standards and guidelines with the view to harmonising practices among relevant states.

Details

Journal of Financial Crime, vol. 8 no. 3
Type: Research Article
ISSN: 1359-0790

Book part
Publication date: 16 November 2009

Giandomenica Becchio

Menger disagreed with this view for various reasons. Also, the subjective expectation is infinite. There are many cases where man's behaviour fails to conform to…

Abstract

Menger disagreed with this view for various reasons. Also, the subjective expectation is infinite. There are many cases where man's behaviour fails to conform to mathematical expectations: games in which a player can win only one very large amount with a very small probability or games offering a single moderate amount with a very high probability. Furthermore, we can always find a sequence of payoffs x1, x2, x3,…, which yield infinite expected value, and then propose, say, that u(xn)=2n, so that expected utility is also infinite. Menger therefore proposed that utility must also be bounded above for paradoxes of this type to be resolved.

Details

Unexplored Dimensions: Karl Mengeron Economics and Philosophy (1923–1938)
Type: Book
ISBN: 978-1-84855-998-1

Article
Publication date: 1 February 1993

J.H.M. TEN THIJE BOONKKAMP and W.H.A. SCHILDERS

An extension of the Scharfetter‐Gummel discretization scheme is presented which is designed for electrothermal semiconductor device equations including avalanche…

Abstract

An extension of the Scharfetter‐Gummel discretization scheme is presented which is designed for electrothermal semiconductor device equations including avalanche generation terms. The scheme makes explicit use of the exponential character of solutions, and reduces to the standard Scharfetter‐Gummel scheme in the isothermal non‐avalanche case.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 12 no. 2
Type: Research Article
ISSN: 0332-1649

Article
Publication date: 5 September 2022

Joseph Oscar Akotey, Godfred Aawaar and Nicholas Addai Boamah

This research explores to answer the question: What accounts for the substantial underwriting losses in the Ghanaian insurance industry?

Abstract

Purpose

This research explores to answer the question: What accounts for the substantial underwriting losses in the Ghanaian insurance industry?

Design/methodology/approach

Thirty-four (34) insurers' audited financial reports covering the period of 2007 to 2017 were analysed through dynamic panel regression to uncover the underlying causes of high underwriting losses in the Ghanaian insurance industry.

Findings

The findings indicate that efforts at increasing market share by overtrading add no value to insurers underwriting profitability. The underwriting risk suggests that the industry charges disproportionately too small premiums for the risks it underwrites. This may indicate under-pricing by some insurers to grow their customer base.

Practical implications

The findings have implications for managerial efficiency and risk management structures that align compensation with underwriting efficiency.

Originality/value

The association between managerial preference and the underwriting performance of insurers in emerging markets has rarely been researched. This study responds to this knowledge challenge.

Details

African Journal of Economic and Management Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-0705

Keywords

Book part
Publication date: 19 July 2022

Pallavi Seth and Kamal Gulati

Introduction: There is a variety of wearables and health applications available in the market which allow the tracking of various health and lifestyle measures like blood…

Abstract

Introduction: There is a variety of wearables and health applications available in the market which allow the tracking of various health and lifestyle measures like blood sugar, calorie counter, number of steps, sleep patterns, etc. After the Covid-19 pandemic, people have become more aware of their health and use these wearables to maintain a healthy lifestyle. Insurance companies in India are also eyeing the potential usage of these wearables in life and health insurance.

Purpose: This research aims to look at the emergence of wearables and health apps and their usage in India’s life and health insurance industry. This study also focuses on how these devices might benefit insurers’ business models and some of the pitfalls to consider.

Methodology: The study used both primary and secondary data. A survey was conducted to understand the customer perception towards usage of wearables. The secondary research included the analysis of the integration of wearables by insurance companies.

Findings: The research would be helpful to the insurance companies as it would help them to understand the customer’s viewpoint for the usage of wearables in the insurance industry. This study would also allow insurers to understand new dimensions, such as where the wearables improve customer satisfaction and engagement. The study results would be helpful for the customers for the appropriate usage of wearables and the internet of things (IoT). Insurance companies can provide better pricing and make personalised insurance plans that ultimately help customers.

Details

Big Data: A Game Changer for Insurance Industry
Type: Book
ISBN: 978-1-80262-606-3

Keywords

Book part
Publication date: 19 July 2022

Vimal Sharma and Deepak Sood

Introduction: The internet of things (IoT) is the emerging technology of interconnected objects that can be termed as ‘things’ used to exchange data, connecting with…

Abstract

Introduction: The internet of things (IoT) is the emerging technology of interconnected objects that can be termed as ‘things’ used to exchange data, connecting with different devices on the internet. It is the future where connected devices are controlled remotely. The insurance sector is one of the leading industries providing financial protection services to their customers to recover losses. Like others, the insurance industry uses the services very efficiently to solve their customer-centric problems and provide the best services to them. IoT in insurance is enhancing customer services.

Purpose: To determine how the insurance industry utilises the different IoT technologies to provide the best services and solutions to their users. The insurance sector is working on other areas of expertise to offer outstanding facilities to their clientele.

Methodology: We reviewed published material covering five years on IoT and insurance and customer services in the media, newspapers, journal publications, and the web. We determined how the insurance sector adapted the new terminology to contribute its best services to the users.

Findings: We observed that IoT services and technologies benefit the insurance industry and the clientele. This shows excellent results in the growth of the sector and heightened facilities for the consumers.

Details

Big Data: A Game Changer for Insurance Industry
Type: Book
ISBN: 978-1-80262-606-3

Keywords

Book part
Publication date: 18 July 2022

Payal Bassi and Jasleen Kaur

Introduction: The insurance industry has unprecedented growth, and the demand for insurance has outgrown in the recent past due to the prevailing pandemic. The companies…

Abstract

Introduction: The insurance industry has unprecedented growth, and the demand for insurance has outgrown in the recent past due to the prevailing pandemic. The companies have a large base of the data set at their disposal, and companies must appropriately handle these data to come out with valuable solutions. Data mining enables insurance companies to gain an insightful approach to map strategies and gain competitive advantage, thus strengthening the profits that will allow them to identify the effectiveness of back-propagation neural network (BPNN) and support vector machines (SVMs) for the companies considered under study. Data mining techniques are the data-driven extraction techniques of information from large data repositories, thus discovering useful patterns from the voluminous data (Weiss & Indurkya, 1998).

Purpose: The present study is performed to investigate the comparative performance of BPNNs and SVMs for the selected Indian insurance companies.

Methodology: The study is conducted by extracting daily data of Indian insurance companies listed on the CNX 500. The data were then transformed into technical indicators for predictive model building using BPNN and SVMs. The daily data of the selected insurance companies for four years, that is, 1 April 2017 to 21 March 2021, were used for this. The data were further transformed into 90 data sets for different periods by categorising them into biannual, annual, and two-year collective data sets. Additionally, the comparison was made for the models generated with the help of BPNNs and SVMs for the six Indian insurance companies selected under this study.

Findings: The findings of the study exhibited that the predictive performance of the BPNN and SVM models are significantly different from each other for SBI data, General Insurance Corporation of India (GICRE) data, HDFC data, New India Assurance Company Ltd. (NIACL) data, and ICICIPRULI data at a 5% level of significance.

Book part
Publication date: 19 July 2022

Jasleen Kaur and Payal Bassi

Introduction: The insurance industry is one of the lucrative sectors of the economy. However, it is volatile because of the large chunk of data generated by the…

Abstract

Introduction: The insurance industry is one of the lucrative sectors of the economy. However, it is volatile because of the large chunk of data generated by the transactions taking place daily. However, every bit of it is responsible for creating market trends for stock investors to predict the returns. The specialised data mining techniques act as a solution for decision-making, reducing uncertainty in decision-making.

Purpose: There are limited studies that have examined the efficiency and effectiveness of data mining techniques across the companies in the insurance industry to date. To enable the companies to take exact benefit of data mining techniques in insurance, the present study will focus on investigating the efficiency of artificial neural network (ANN) and support vector machine SVM across insurance companies of CNX 500.

Method: For predictive models, various technical indicators were considered independent variables, and change in return, i.e. increase and decrease, was deemed a dependent variable. The indicators were transformed from daily raw data of insurance company’s stock values spanning four years. We formed 90 data sets of varied periods for building the model – specifically six months, one year, two years, and four years for selected six insurance companies.

Findings: The study’s findings revealed that ANN performed best for the ICICIPRULI data model in terms of hit ratio. Whereas the performance of SVM was observed to be the best for the ICICIGI data model. In the case of pairwise comparison among the six selected Indian insurance companies from CNX 500, the extracted data evaluated and concluded that there were eight significantly different pairs based on hit ratio in the case of ANN models and nine significantly different pairs based on hit ratio for SVM models.

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