Applications of Data Mining Techniques in Life Insurance

, , , . , , , .

In this paper, the application of data mining techniques on polynomial based approach for better electrocardiogram (ECG) authentication mechanism is presented. Polynomials being used for ECG data processing have a history of nearly two decades. Recently it has been bringing about promising solutions for heart beat recognition problem. General polynomial based approach are used in this research and by using the polynomial coefficients extracted as unique features from the ECG signals, data mining techniques was applied for person identification. A total of 18 ECG recordings from MIT/BIH Normal Sinus Rhythm database (NSRDB) were used for development and evaluation. QRS complexes from each dataset was divided into two parts, the training and the testing dataset which was used to prove the validity of the data mining technique applied. Experimental results was classified using Multilayer Perceptron (MLP) in order to confirm the identity of an individual and was compared with the previous research using polynomials without the use of data mining technique. Our experimentation on a public ECG database suggest that the proposed data mining technique on polynomial based approach significantly improves the identification accuracy by 96% as compared to 87% from the existing study.

INSURANCE ISSUES IN LIVING KIDNEY DONATION We have undertaken a study to ascertain the perspective of U.K. insurance companies to provision of insurance to living kidney donors. WHICH (consumer guide) and customer directories were used to identify the major life and health insurance providers in the United Kingdom, who were then invited to complete specific questionnaires. The results were as follows: 14 life insurance companies, insuring approximately 6.5 million customers (79% of U.K. life insurance market), replied. When questioned regarding their policy if an existing customer should die during kidney donation, 13 of 14 stated that they would pay the agreed life insurance sum. One company did not provide an answer, as they had no experience of the situation and are currently deciding their position for future reference. No companies required to be informed by a customer of their intention to donate. Furthermore, all would accept new customers after previous kidney donation and would not charge an increased premium but indicated that time considerations since donation were a factor in assessing such customers (Table 1). Table 1: Time since living kidney donation for new customers considered relevant by life and health insurers in the United KingdomRegarding health insurance provision, seven major health insurance companies replied; however, one did not complete the questionnaire because they do not market new business. Of the remaining six companies, half cover existing customers for kidney donation. Should an existing customer require a transplant, one company would pay recipient medical expenses and would also pay donor costs if the recipient and donor were both policy holders. All companies accept new customers after previous kidney donation, although two of six stipulate that they exclude any problems arising from donation. Two of six charge an increased rate and four of six do not. Time since donation is considered to be relevant for new customers, as shown in Table 1. Insurance companies providing life insurance to almost 80% of the life insurance policy holders in the United Kingdom would honor the terms of their agreement should a customer die as a consequence of live kidney donation. Premiums are not raised; therefore, kidney donation has no long-term financial implications regarding life insurance. When considering new customers applying for insurance, there were significant inconsistencies among both life and health insurers in the amount of time postdonation that respondents considered relevant. Deaths associated with live kidney donation are rare but occur predominantly in the perioperative period, as do the great majority of complications (1,2), and so these time considerations could be considered to be without scientific foundation. It has been postulated that the increased life expectancy in donor populations may be attributed to exclusion of concomitant illness by the rigorous assessment (3–5). Considering this, the reluctance of certain health insurers to provide medical expenses for donors or sickness benefit is disappointing. Equally, it could be argued that life insurance premiums should actually be reduced postdonation. Kidney donation may have financial implications for health insurance; however, the long-term effects of this are minimized because of the current structure of the National Health Service in the United Kingdom. The inconsistencies in many aspects of insurance provision to live kidney donors highlight the necessity to share information and strive for evidence-based practice from insurance providers. Sarah Clarke Jennifer A. Lumsdaine Stephen J. Wigmore Murat Akyol John L. R. Forsythe

In last decade, the uses of data mining techniques in medical studies are growing gradually. The aim of this paper is to present a recent research on the application of data mining technique for medical diagnosis problems. The proposed data mining technique is Multiple Knot Spline Smooth Support Vector Machine (MKS-SSVM). MKS-SSVM is a new SSVM which used multiple knot spline function to approximate the plus function instead the integral sigmoid function in SSVM. To evaluate the effectiveness of our method, we carried out on two medical dataset (diabetes disease and heart disease). The accuracy of previous results of these data still under 90% so far. The results of this study showed that MKS-SSVM was effective to diagnose medical dataset, especially diabetes disease and heart disease and this is very promising result compared to the previously reported results.

Waste container weighing data processing to create reliable information of household waste generation

Due to the rapid advancements in information and communication technologies, the digital data is exponentially growing on the internet. The insurance industry with tough competition has emerged as information rich domain based on health, assets, and life insurance for public. Customers expect to receive personalized services that match their needs, preferences, and lifestyles. But a large portion of population is still unfriendly to the insurance selection. Major reasons could be the time and complexities involved in selection of suitable policies. This paper presents the state of the art of the research done in insurance recommendation systems at national and international levels. Multi-criteria decision-making methods are compared with collaborative filtering and data mining techniques. Their suitability to the field of life insurance recommendation is analyzed. The paper identifies the lack of public dataset of customers and life insurance policies and highlights the need for a personalized, neutral, and unified model for effective information computing for life insurance recommendations.

The data mining has been performed for the aerodynamic design optimization result of two-stage-to-orbit reusable launch vehicle flyback booster wing. Three data mining techniques were used such as self-organizing map, functional analysis of variance, and rough set theory. The optimization problem had four aerodynamic objective functions and 71 design variables regarding wing shape. The optimization obtained the result as the hypothetical design database with 302 all solutions including the 102 non-dominated solutions. Consequently, the knowledge in the design space was acquired regarding the correlation between objective functions, and the influence of the design variables to the objective function, for non-dominated and all evaluated solutions, respectively. The features of three data mining techniques were revealed. Although the combination among three techniques discovered detailed design knowledge, self-organizing map was especially a key technique for knowledge discovery. Moreover, design knowledge from all solutions conserved the information from non-dominated solutions. Data mining was essential to solve multi-objective optimization problem.

Physical ecosystems, such as an IT ecosystem, consist of multiple disparate entities that generate large volumes of data related to their environmental and operational state. Knowledge discovery and data mining techniques can be applied to identify the current state, and use knowledge derived from historical data to transform the system to a more sustainable operational state.

The study has focused on the customer relationship management (CRM) system in the life insurance sector of India. The study revealed the technical progress of India's insurance industry, especially in Tamil Nadu. The deployment of CRM systems in LIC and other private insurance sectors in India was analysed using primary data. India is a populous, diverse country. Life insurers can grow in unused markets. LIC previously dominated the Indian life insurance market, thus buyers had few options. So, private life insurance businesses emerged, and consumers can now readily separate LIC and other private insurance sectors. However, the number of respondents is limited to 51 respondents in this paper, which undermines the external and internal validity of the paper. In some circumstances, it's hard to understand the specific conclusion with real findings. Indian life insurance varies. The insurance market relies on medical and life histories. Life insurance sectors have so much information about their customers and sometimes they cannot properly handle all the data accordingly.

The enthusiasm of the Indonesian people for social media makes digital marketing strategies an important factor to increase brand strength through improving the company's postitf image. Social media is a place for companies to form positive online perceptions and reputations. This condition is the basis for research to find out how the consistency of positive reputation is on the financial performance of insurance companies in Indonesia. The relationship between the Digital Reputation Index (IRD) on the financial performance of insurance companies (gross premiums, productivity ratio and company profit) was analyzed based on data from 12 life insurance companies and 12 conventional general insurance companies respectively. The Spearman correlation test resulted in a significant positive directional relationship for the Digital Reputation Index to gross premiums (for life and general insurance companies). A non-significant positive directional relationship between the Digital Reputation Index and the Productivity Ratio (life and general insurance). A non-significant positive directional relationship between the Digital Reputation Index and the profits of life insurance companies while a significant positive relationship occurs with the profits of general insurance companies.

Introduction. Life insurance arises from the need for individuals to provide financial protection and security for themselves and their families. It can be used as a tool for accumulating financial resources and as a means of pension planning. Life insurance in Ukraine remains less developed compared to other European countries due to low confidence in insurance companies, a difficult economic situation in the country, and the lack of proper legislative regulation in this area of insurance. Problem Statement. The increasing proportion of elderly people, according to demographic projections, determines the corresponding requirements for reforming primarily the social security sphere, and life insurance could become one of the effective ways of supplemental social security. Purpose. To highlight the potentialities of using life insurance as supplemental social security. Methods. We used general scientific and special methods, i.e. analysis, synthesis, grouping, description, comparison, theoretical generalization, and abstract-logical methods. Results. It is emphasized that life insurance inherently aims at additional protection and support of the financial and social welfare of the population. It is noted that in most developed countries, life insurance is integrated into the social security system. It is proved that life insurance in Ukraine is not a mandatory part of the social security system, but is available on a voluntary basis through insurance companies. The number of insured citizens and life insurance contracts concluded by life insurers in Ukraine during the last 5 years has been analyzed. Research of the voluntary life insurance market in Ukraine has been conducted and an overview of the programs offered by insurance companies according to the classes of insurance has been made. Conclusions. Life insurance as an opportunity for supplemental social security has a significant potential in our country. However, the impact of some negative factors, in particular, military aggression, and an underdeveloped stock market hinders the development of the voluntary life insurance market and the possibility to expand the share of the insured population of our country. Taking into account statistics, which are aggravated by the military situation in the country, there is a need for clearly defined legislative conditions for the use of life insurance as a supplemental method of social security.

This research paper presents a comparative study of selected private life insurance companies in India using the CARAMEL model. Tawheed B. (2016) The macro-level analysis of the performance of the Life Insurance Corporation (LIC) in India provides valuable insights into its operational efficiency and societal impact. The study focuses on HDFC Life Insurance, ICICI Prudential Life Insurance, SBI Life Insurance, and Max Life Insurance, representing a significant portion of the private life insurance market. The CARAMEL model, which encompasses Capital Adequacy, Asset Quality, Risk Management, Earnings, Market Perception, and Liquidity, serves as a comprehensive framework for evaluating the financial health and performance of these insurance companies. Trivedi S. (2016) The study on risk management tools and techniques in life insurance in India aims to provide valuable insights into developing effective tools for life insurers to analyze customer risks. This research endeavors to conduct a comparative study of three leading private life insurance companies in India: HDFC Life Insurance, ICICI Prudential Life Insurance, and SBI Life Insurance. The findings indicate that HDFC Life Insurance exhibits superior Capital Adequacy, positioning it favorably in terms of protecting policyholders and promoting financial system stability. Max Life Insurance demonstrates better Asset Quality, reflecting its strong financial health and risk management capabilities. All the selected companies show effective risk management practices, which contribute to their financial stability and resilience. SBI Life Insurance is a top performer in Management Soundness, Earnings and Profitability, and Liquidity ratios, highlighting its operational efficiency, profitability, and financial resilience. Madhuri T. and Rao N. (2020) has evaluated the financial performance of selected Indian life insurance companies using the CARAMEL model. Recommendations of the paper suggested LIC's capital position and underwriting expenses while urging private insurers to enhance liquidity for timely liability fulfillment. The study provides valuable insights for regulators, investors, and other stakeholders, supporting informed decision-making and promoting overall stability and sustainability in the insurance industry.

Efforts to formulate legislation designed to tax the income of various types of life insurance companies have encountered difficult and complex problems. This article enumerates several of these problems and describes four alternative forms of life insurance company income tax legislation: U.S. Treasury's 1958 proposal for a total income tax base, Lent's proposal for a total income plus reserve interest tax base, the 1959 Act and a revised version of the 1959 Act. potential impact of each alternative tax law is systematically analyzed by means of a computer simulation technique. results suggest that certain laws would create inter-company inequities as well as industry financial chaos. history of life insurance company income tax legislation reveals the complex problems involved in designing a tax law which will simultaneously generate adequate amounts of revenue while treating all life insurance companies equitably. Early attempts2 to apply a total income Andrew F. Whitman, Ph.D., is Assistant Professor of Insurance in the University of Minnesota. He has served as part-time instructor in Pennsylvania State University, as Technical Assistant in the Wisconsin State Insurance Department, as a State Farm Fellow and Teaching Assistant in the University of Wisconsin, and as a Traveler's Research Fellow. earlier article by Dr. Whitman on taxation of insurance companies appeared in this Journal. Howard E. Thompson, Ph.D., is Associate Professor of Business in the Graduate School of Business of the University of Wisconsin. From 1957 to 1961, Dr. Thompson served as Mathematician and Operations Research Analyst at the A. 0. Smith Corporation. His earlier articles have been published in Management Science, the Journal of the Academy of Management, and this Journal. This paper was presented at the 1967 Annual Meeting of A.R.I.A. 1 research for this study was sponsored in part by Ford Foundation, National Science Foundation through the Graduate School of the University of Wisconsin, and the Research Department of Travelers Insurance Company. or corporate income tax approach to life insurance companies were abandoned3 in 2 From 1909 to 1921 the method of determining the income tax base for life insurance companies was substantially the same as that imposed on companies not in the insurance business. Between 1913 and 1921, premium income, investment income, and capital gains were included in gross taxable income. deductions from gross income included the following items: tax-exempt interest, dividends on policies for which premiums were currently paid, operating expenses, current payments on policies, and net additions to policy reserves. Corporation Enactment of 1909 was reenacted in the Revenue Acts of 1913, 1916, 1917, and 1918. For life insurance companies, Tax rates started at 1 per cent in 1909 and gradually increased to 12 per cent in 1918; Allen L. Mayerson, The Life Insurance Company Income Act of 1959, CLU Journal, XIV, No. 2 (Spring, 1960) p. 172. 3 For statements of the reasons for abandoning the corporate or total income tax base which taxes both life insurance company investment income and underwriting gain, see House Report No. 350, 67th Congress, 1st Sess., p. 20; T. S. Adams, Advisor to the Treasury, Senate Committee on Finance, Hearings on H. R. 8245, 67th Congress, 1st Sess. (Washington U.S. Gover ment Printing Office, 1921); Robert T. Collins, The Federal Taxation of Insurance Companies (unpublished Ph.D. dissertation, University of Southern California, 1954) pp. 142-66; Barnie E. Abelle, An Evaluation of the Life Insurance Company Income Act of 1959, (unpub-

Could Not Duplicates (CNDs) are the bane of modern aircraft. Inflight Built-in-Test (BIT) or pilot squawks often indicate faults that can not be duplicated with ground testing. For many subsystems CND rates run over 50 percent. The Vehicle Systems Technology (VST) group at the Boeing Company is developing an onboard diagnostic system architecture and supporting technologies to reduce CNDs and exploit the promise of prognostics. The approach involves the use of neural network and fuzzy logic models of subsystem health, correlation of health incidents with operational context and fusion of health reports within and across subsystems. Knowledge Discovery and data mining techniques are used to identify health/fault signatures and develop diagnostic/prognostic models from these signatures. This work was sponsored by Boeing internal research, the Navy through the On-line Flight Control Diagnostic System program (with Lockheed-Martin Control Systems as a subcontractor) and the Joint Strike Fighter technology maturation program.

Comprehensive and Technical Efficiency of Insurance and Takaful Companies in Pakistan Insurance and Takaful companies, both, are business organizations existing for the motive of profit. Large capital is required by the shareholders to establish a company; therefore, the company is expected to earn sufficient profit to meet the expectations of the shareholders. Moreover, a company also has its responsibilities towards its customers in terms of quality service. Shareholders are more concerned with their profit and customers regarding the services. Companies pay claims when the covered persons suffer a loss which can be the death of the family’s only bread earner, factory on fire, theft of business goods etc. Therefore, efficient financial performance of insurance and Takaful companies is important to fulfil the requirements of both: shareholders and clients. This study investigates financial efficiency of insurance and Takaful companies via Data Envelopment Analysis during the period 2011 to 2015. We have taken six general (non - life ) insurance & Takaful companies operating in Pakistan with input factors labor cost, assets and output factors premium / contribution received and percentage of claims paid. Results show that insurance and takaful companies are more than 80% efficient in their operations. For further increasing their efficiencies, they need to reduce their input by less than 20% to have same level of output. Comparing efficiencies of insurance and takaful companies, insurance companies are more efficient in terms of pure technical & super efficiency while takaful companies have higher scale efficiency than insurance companies, though the difference in most of the cases is less than 2%. Both types of companies need to improve their efficiencies by decreasing their assets input and labor cost while retaining the same output level of premiums and claims. Keywords: General insurance, Data Envelopment Analysis (DEA); Malmquist index, Takaful, Scale and technical efficiency