Insurance claims

Epidemiological aspects of Parkinson's disease (PD), co-occurring diseases and medical healthcare utilization of PD patients are still largely elusive. Based on claims data of 3.7 million statutory insurance members in Germany in 2015 the prevalence and incidence of PD was determined. PD cases had at least one main hospital discharge diagnosis of PD, or one physician diagnosis confirmed by a subsequent or independent diagnosis or by PD medication in 2015. Prevalence of (co-)occurring diseases, mortality, and healthcare measures in PD cases and matched controls were compared. In 2015, 21,714 prevalent PD cases (standardized prevalence: 511.4/100,000 persons) and 3,541 incident PD cases (standardized incidence: 84.1/100,000 persons) were identified. Prevalence of several (co-)occurring diseases/complications, e.g., dementia (PD/controls: 39/13%), depression (45/22%), bladder dysfunction (46/22%), and diabetes (35/31%), as well as mortality (10.7/5.8%) differed between PD cases and controls. The annual healthcare utilization was increased in PD cases compared to controls, e.g., regarding mean ± SD physician contacts (15.2 ± 7.6/12.2 ± 7.3), hospitalizations (1.3 ± 1.8/0.7 ± 1.4), drug prescriptions (overall: 37.7 ± 24.2/21.7 ± 19.6; anti-PD medication: 7.4 ± 7.4/0.1 ± 0.7), assistive/therapeutic devices (47/30%), and therapeutic remedies (57/16%). The standardized prevalence and incidence of PD in Germany as well as mortality in PD may be substantially higher than reported previously. While frequently diagnosed with co-occurring diseases/complications, such as dementia, depression, bladder dysfunction and diabetes, the degree of healthcare utilization shows Parkinson's Disease Epidemiology and Healthcare in Germany large variability between PD patients. These findings encourage a rethinking of the epidemiology and healthcare utilization in PD, at least in Germany. Longitudinal studies of insurance claims data should further investigate the individual and epidemiological progression and healthcare demands in PD.

Epidemiological aspects of Parkinson's disease (PD), co-occurring diseases and medical healthcare utilization of PD patients are still largely elusive. Based on claims data of 3.7 million statutory insurance members in Germany in 2015 the prevalence and incidence of PD was determined. PD cases had at least one main hospital discharge diagnosis of PD, or one physician diagnosis confirmed by a subsequent or independent diagnosis or by PD medication in 2015. Prevalence of (co-)occurring diseases, mortality, and healthcare measures in PD cases and matched controls were compared. In 2015, 21,714 prevalent PD cases (standardized prevalence: 511.4/100,000 persons) and 3,541 incident PD cases (standardized incidence: 84.1/100,000 persons) were identified. Prevalence of several (co-)occurring diseases/complications, e.g., dementia (PD/controls: 39/13%), depression (45/22%), bladder dysfunction (46/22%), and diabetes (35/31%), as well as mortality (10.7/5.8%) differed between PD cases and controls. The annual healthcare utilization was increased in PD cases compared to controls, e.g., regarding mean ± SD physician contacts (15.2 ± 7.6/12.2 ± 7.3), hospitalizations (1.3 ± 1.8/0.7 ± 1.4), drug prescriptions (overall: 37.7 ± 24.2/21.7 ± 19.6; anti-PD medication: 7.4 ± 7.4/0.1 ± 0.7), assistive/therapeutic devices (47/30%), and therapeutic remedies (57/16%). The standardized prevalence and incidence of PD in Germany as well as mortality in PD may be substantially higher than reported previously. While frequently diagnosed with co-occurring diseases/complications, such as dementia, depression, bladder dysfunction and diabetes, the degree of healthcare utilization shows Parkinson's Disease Epidemiology and Healthcare in Germany large variability between PD patients. These findings encourage a rethinking of the epidemiology and healthcare utilization in PD, at least in Germany. Longitudinal studies of insurance claims data should further investigate the individual and epidemiological progression and healthcare demands in PD.

Epidemiological aspects of Parkinson's disease (PD), co-occurring diseases and medical healthcare utilization of PD patients are still largely elusive. Based on claims data of 3.7 million statutory insurance members in Germany in 2015 the prevalence and incidence of PD was determined. PD cases had at least one main hospital discharge diagnosis of PD, or one physician diagnosis confirmed by a subsequent or independent diagnosis or by PD medication in 2015. Prevalence of (co-)occurring diseases, mortality, and healthcare measures in PD cases and matched controls were compared. In 2015, 21,714 prevalent PD cases (standardized prevalence: 511.4/100,000 persons) and 3,541 incident PD cases (standardized incidence: 84.1/100,000 persons) were identified. Prevalence of several (co-)occurring diseases/complications, e.g., dementia (PD/controls: 39/13%), depression (45/22%), bladder dysfunction (46/22%), and diabetes (35/31%), as well as mortality (10.7/5.8%) differed between PD cases and controls. The annual healthcare utilization was increased in PD cases compared to controls, e.g., regarding mean ± SD physician contacts (15.2 ± 7.6/12.2 ± 7.3), hospitalizations (1.3 ± 1.8/0.7 ± 1.4), drug prescriptions (overall: 37.7 ± 24.2/21.7 ± 19.6; anti-PD medication: 7.4 ± 7.4/0.1 ± 0.7), assistive/therapeutic devices (47/30%), and therapeutic remedies (57/16%). The standardized prevalence and incidence of PD in Germany as well as mortality in PD may be substantially higher than reported previously. While frequently diagnosed with co-occurring diseases/complications, such as dementia, depression, bladder dysfunction and diabetes, the degree of healthcare utilization shows Parkinson's Disease Epidemiology and Healthcare in Germany large variability between PD patients. These findings encourage a rethinking of the epidemiology and healthcare utilization in PD, at least in Germany. Longitudinal studies of insurance claims data should further investigate the individual and epidemiological progression and healthcare demands in PD.

This edition of our insurance law series discusses the analysis of insurance contracts. Insurance is a special kind of contract. The document which embodies the insurance contract is known as the policy. This chapter reviews the component parts of a typical insurance policy.

This study assessed the contribution of fire insurance to the Nigerian economy from 1990 to 2020. It was aimed at examining the effect of fire insurance premium income and claim expenditure on the Nigerian gross domestic product. The study was motivated by the incessant fires in Nigeria which has resulted in an increase in fire insurance premium income in recent times. The research design for the study was ex post facto, while the study population was made up of all insurance companies providing fire insurance cover as of 2020. Data were obtained from Nigeria Insurance Digest, Central Bank of Nigeria statistical bulletin and the National Bureau of Statistics for the study period. Analysis of data was carried out using cointegration and ordinary least square regression. A long-run relationship between fire insurance premium income, claim expenditure and GDP was established while a positive significant relationship was observed between fire insurance premiums and GDP. Claim expenditure had an insignificant relationship with GDP. This study implies that fire insurance serves as a risk diversification tool that has had a positive impact on the Nigerian economy. It is concluded that fire insurance is of importance and its pull of premiums and financial intermediation role boosts economic activities in the country. It is recommended that fire insurance should be encouraged among individuals and businesses in Nigeria.

Background: The performance of a sample of manufacturing enterprises was measured in terms of return on assets, and this study looked at the impact of exposure to credit risk, liquidity risk, and interest rate exposure. Objective: The aim of this study is to examine how risk exposure affects the productivity of manufacturing companies in Nigeria. The specific objectives of this study are to examine the effect of credit risk exposure on return on asset of manufacturing firms, investigate the effect of liquidity risk exposure on return on asset of manufacturing firms and assess the effect of interest risk exposure on return on asset of manufacturing firms in Nigeria Method: This study employs inferential and descriptive analysis, using metrics like mean, minimum and maximum value, kurtosis, skewness, and Jacque bera for descriptive analysis. Inferential analytic approaches include correlation analysis and panel regression estimation. Panel regression estimation was chosen to determine if heterogeneity affects the influence of risk exposure on performance, a feature not found in previous studies. Results: Results showed that exposure to credit risk and liquidity risk positively affected return on assets, while interest rate risk exposure had a negative effect. However, credit risk exposure was the only factor significantly affecting the return on assets of the chosen enterprises. The study concluded that manufacturing firms' exposure to risk, particularly credit risk exposure, significantly affects performance. Conclusion: To improve performance, the study suggested that manufacturing enterprises should be exposed to a certain level of risk related to debtors and creditors.

As datasets increase radically in size, highly scalable algorithms leveraging modern distributed infrastructures need to be developed for detecting outliers in massive datasets. In this work, we present the first distributed distance-based outlier detection approach using the MapReduce-based infrastructure, called DOD. DOD features a single-pass execution framework that minimizes communication overhead. Furthermore, DOD overturns two fundamental assumptions widely adopted in the distributed analytics literature, namely cardinality-based load balancing and one algorithm for all data. The multi-tactic strategy of DOD achieves a truly balanced workload by taking into account the data characteristics in data partitioning and assigns most appropriate algorithm for each partition based on our theoretical cost models established for distinct classes of detection algorithms. Thus, DOD effectively minimizes the end-to-end execution time. Our experimental study confirms the efficiency of DOD and its scalability to terabytes of data, beating the baseline solutions by a factor of 20x.

Detecting fraudulent and abusive cases in healthcare is one of the most challenging problems for data mining studies. However, most of the existing studies have a shortage of real data for analysis and focus on a very limited version of the problem by covering only a specific actor, healthcare service, or disease. The purpose of this study is to implement and evaluate a novel framework to detect fraudulent and abusive cases independently from the actors and commodities involved in the claims and an extensible structure to introduce new fraud and abuse types. Interactive machine learning that allows incorporating expert knowledge in an unsupervised setting is utilized to detect fraud and abusive cases in healthcare. In order to increase the accuracy of the framework, several well-known methods are utilized, such as the pairwise comparison method of analytic hierarchical processing (AHP) for weighting the actors and attributes, expectation maximization (EM) for clustering similar actors, two-stage data warehousing for proactive risk calculations, visualization tools for effective analyzing, and z-score and standardization in order to calculate the risks. The experts are involved in all phases of the study and produce six different abnormal behavior types using storyboards. The proposed framework is evaluated with real-life data for six different abnormal behavior types for prescriptions by covering all relevant actors and commodities. The Area Under the Curve (AUC) values are presented for each experiment. Moreover, a cost-saving model is also presented. The developed framework, i.e., the eFAD suite, is actor-and commodity-independent, configurable (i.e., easily adaptable in the dynamic environment of fraud and abusive behaviors), and effectively handles the fragmented nature of abnormal behaviors. The proposed framework combines both proactive and retrospective analysis with an enhanced visualization tool that significantly reduces the time requirements for the fact-finding process after the eFAD detects risky claims. This system is utilized by a company to produce monthly reports that include abnormal behaviors to be evaluated by the insurance company.

Insurance plays an essential role in stimulating economic growth. Insurance is an intangible product, and prompt claim settlement proves that insurers fulfill their promises to the insureds. This paper analyses the impacts of insurance claims settlement on economic growth. It examines the effect of insurance claims' settlements on a nation's economic growth, using Nigeria as a case study. The research utilised an ex-post facto design, using 28-year time series data (1992 – 2019). Gross Domestic Product (GDP) and Nigeria's insurance companies' claims settlement are the dependent and independent variables used for the study, respectively. The Long-run co-integration result revealed that INCLM (Insurance claims) has an insignificant negative effect on GDP. The coefficient shows that a percentage increment in INCLM (Insurance claims) would result in a 1.22 decrease in GDP. The results indicate that insurance claims settlement has an insignificant negative effect on econo...

The statement above suggests that in Nigeria, Insurers are using claims payment as a competitive tool, particularly when premium rates are comparable. This implies that Insurers may seek to differentiate themselves by emphasizing efficient and reliable claims processing to attract and retain customers. It underscores the significance of a prompt and fair claims settlement process as  key factor influencing consumer choice in a competitive insurance market.

Resilience to withstand the destructive impact of the external environment and modern challenges contributes to ensure the economic security of the company. The consequences of the pandemic, military actions in Ukraine, rising inflation, and the transformation of geopolitical processes in the European Union have negatively affected the economic security of insurance companies in Slovakia. The purpose 10 of the study is to assess the economic security of Slovak insurance companies. The study is based on the analysis of profitability, assets and liabilities, premiums, claims and expenses of insurance companies in Slovakia. The forecasting methodology is applied and various scenarios of further functioning of insurance companies in Slovakia, proposed by the National Bank of Slovakia, are analyzed. Insurance companies in Slovakia have sufficient capital, losses in the forecast period can be covered by current profits, and the growth of insurance claims can be transferred to reinsurers. The study found that insurance companies in Slovakia to ensure stability and economic security, and have prospects for further operation and development.

Purpose: With this study, the authors aim to design a measure to determine the effectiveness of having Forensic Auditors in the Insurance Business. Moreover, in doing this to determine whether this measure is affected by different demographic variables. Design/Methodology: To prove the effectiveness of forensic auditors in the insurance industry, the authors designed a questionnaire using criteria of effectiveness established by Bond et al. (2011) which was completed by 402 valid participants. The criteria revolved around having procedural, substantive, transactive and normative effectiveness. Findings: Results show that engaging forensic auditors in the insurance industry are effective. Forensic auditors are needed in the claims process of insurance firms, and possibly, they should further be engaged in the risk management team of an insurance company. However, with regards to determining the compensation amount, respondents showed a lack of trust, and prefer if forensic auditors w...

Govoreći o uredskom poslovanju i njegovu razvoju na području Hrvatske od 1945. do 1958. godine treba odmah napomenuti da sagledavanje toga razvoja nije moguće izvan konteksta FNRJ, jer su u vrijeme centralizirane uprave i unitarnoga sagledavanja društvenih pitanja srodna obilježja i podjednaka razvojna dinamika uredskoga poslovanja prisutni na čitavom jugoslavenskom prostoru. S druge strane upravo zbog manjka objavljenih tekstova koji bi se odnosili isključivo na Hrvatsku primjeri iz drugih republika mogu poslužiti kao dobra ilustracija stanja i razvoja te djelatnosti i na našem području, jer korespondiraju s našim neposrednim iskustvima nastalima u obradi i tijekom uporabe gradiva toga doba. brought to you by CORE View metadata, citation and similar papers at core.ac.uk 2 Postupci su: primanje i pregled pošte, signiranje i uvođenje spisa u evidencije, dostava u rad, tehničkoadministrativna obrada, otpremanje pošte, razvođenje spisa, njihova pohrana u pismohrani (tzv. arhivu), a alati koji se pritom rabe jesu: popisi radnih jedinica i njihovih oznaka, oznake pismohrane, tj. registraturne oznake (registraturni nacrti) ili pak klasifikacijski sustavi.

Insurance plays an essential role in stimulating economic growth. Insurance is an intangible product, and prompt claim settlement proves that insurers fulfill their promises to the insureds. This paper analyses the impacts of insurance claims settlement on economic growth. It examines the effect of insurance claims' settlements on a nation's economic growth, using Nigeria as a case study. The research utilised an ex-post facto design, using 28-year time series data (1992-2019). Gross Domestic Product (GDP) and Nigeria's insurance companies' claims settlement are the dependent and independent variables used for the study, respectively. The Long-run co-integration result revealed that INCLM (Insurance claims) has an insignificant negative effect on GDP. The coefficient shows that a percentage increment in INCLM (Insurance claims) would result in a 1.22 decrease in GDP. The results indicate that insurance claims settlement has an insignificant negative effect on economic growth. This implies a negative relationship between insurance claims settled by insurance companies and economic growth in Nigeria. The finding is surprising as one expects that settlement of claims by insurers should positively impact economic growth. The implication is that the relationship between insurance claims settlement and economic growth varies depending on several factors, including country-specific factors and the performance of the country's insurance industry.

Extreme value theory is applied to model extreme occurrences, and it is applied in business and finance to measure tail risk. Marine and aviation class of insurance business is an important component of non-life business because it insures all risks relating to aviation and marine vessels which play a significant role in the economic development of Nigeria. Recent claims experience has necessitated the investigation of tail risks with small probability of occurrence but with high potential impact on company's survival. The study employs the Extreme Value Theory (EVT) to estimate the minimum expected claims for the marine and aviation insurance business using historical claims data. Diagnostics plot like the mean excess plot suggest the threshold to chosen, to fit Generalized Pareto model based on EVT and the excess distributions were obtained over a chosen threshold. Linear Q-Q plots and tail plots reveal that parametric model fits the data well. VaR estimate was finally obtained using the extreme value method at 5% confidence interval and the empirical results show that Extreme VaR is most suitable to calculate VaR as against the Historical and Gaussian methods. This will guide proper underwriting process and loss reserving in this class of business.

Purpose: With this study, the authors aim to design a measure to determine the effectiveness of having Forensic Auditors in the Insurance Business. Moreover, in doing this to determine whether this measure is affected by different demographic variables. Design/Methodology: To prove the effectiveness of forensic auditors in the insurance industry, the authors designed a questionnaire using criteria of effectiveness established by Bond et al. (2011) which was completed by 402 valid participants. The criteria revolved around having procedural, substantive, transactive and normative effectiveness. Findings: Results show that engaging forensic auditors in the insurance industry are effective. Forensic auditors are needed in the claims process of insurance firms, and possibly, they should further be engaged in the risk management team of an insurance company. However, with regards to determining the compensation amount, respondents showed a lack of trust, and prefer if forensic auditors w...

Over the last 11 years, the Law Commission and the Scottish Law Commission have worked on a joint project to modernise the law of insurance contracts. Due to the size of the project, the Law Commissions proceeded in phases and separated out specific issues for legislative reform. Their proposals have already resulted in the Consumer Insurance (Disclosure and Representations) Act 2012 and the Insurance Act 2015 which brought about significant changes for consumer and non-consumer insureds and insurers alike. This paper examines two further areas of reform: the introduction of an implied term about payment of insurance claims by insurers within a reasonable time and a statutory restatement of the doctrine of insurable interest. It considers the old and new substantive law and provides an insight into the reform process.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Urban flooding caused by heavy rainfall is expected to increase in the future. The main purpose of this study was to investigate the variables characterizing the placement of a house, which seem to have an impact when it comes to the exposure to floods. From the same region in Norway, data from 347 addresses were derived. All addresses were either associated with insurance claims caused by flooding or were randomly selected. A multivariate statistical model, Partial Least Square Regression (PLS), was used. Among others, the analysis has shown that the upstream, sealed area is the most significant variable for characterizing properties' exposure to urban flooding. The model confirms that flooding tends to occur near old combined sewer mains and in concave curvature, and houses located in steep slopes seem to be less exposed. Using this method, it is possible to rank and quantify significant exposure variables contributing to urban floods within a region. Results from the PLS-analysis might provide important input to professionals, when planning and prioritizing measures. It can also predict flood-prone areas and make residents aware of the risks, which may induce them to implement preventive measures.

In fraud detection paradigms, the role of predictor variables cannot be overemphasized particularly when analytical toolssuch as statistical, machine learning and artificial intelligent tools are employed. These variables or attributes are used to organize records of data in database tables. The combination of the values of these attributes usually affects which class of a target variable a record or an observation would belong. In this paper, we propose an algorithm and employ spreadsheet 'count' 'count if' and 'filtering' functionalities (techniques) to take toll on how the individual attribute may affect the prediction of the class of an observation in an insurance dataset of 5000 observations. The analysis showed that indeed, the individual predictor attribute affects the outcome of the target variable (legal or fraudulent) differently.

A cross-sectional exploratory survey on occurrence of triple-whammy prescription pattern in Japan ABSTRACT Background: The concurrent use of nonsteroidal anti-inflammatory drugs, renin-angiotensin-aldosterone system blockers, and diuretics, known as a "triple-whammy," is related to the occurrence of acute kidney injury. However, there are few reports regarding the prescription pattern of the triple-whammy. Objective: To elucidate the patterns of the triple-whammy prescription in Japan. Methods: A cross-sectional study was performed using a health-insurance-claims database that included Japanese people under 75 years of age, and enrolled outpatients that were prescribed any nonsteroidal anti-inflammatory drugs, renin-angiotensin-aldosterone system blockers, and diuretics between April 2017 and June 2017. As an outcome, the proportion of triple-whammy prescriptions was evaluated. Among the patients who received triple-whammy prescriptions, we evaluated the prevalence of chronic kidney disease and the proportion of prescriptions provided for these three drugs from different clinical departments and institutions. Results: Overall, 730 of 246,721 (0.3%) patients received triple-whammy prescriptions. Among these patients, 13.3% had underlying chronic kidney disease. The proportions of any of the three drug types prescribed by different clinical departments and institutions was 48.2% and 61.8%, respectively. Conclusions: We examined the patterns of triple-whammy prescriptions and concluded that pharmacists need to pay attention to triple-whammy prescriptions if the prescriptions are provided by multiple clinical departments or institutions.

In fraud detection paradigms, the role of predictor variables cannot be overemphasized particularly when analytical toolssuch as statistical, machine learning and artificial intelligent tools are employed. These variables or attributes are used to organize records of data in database tables. The combination of the values of these attributes usually affects which class of a target variable a record or an observation would belong. In this paper, we propose an algorithm and employ spreadsheet 'count' 'count if' and 'filtering' functionalities (techniques) to take toll on how the individual attribute may affect the prediction of the class of an observation in an insurance dataset of 5000 observations. The analysis showed that indeed, the individual predictor attribute affects the outcome of the target variable (legal or fraudulent) differently.

Fraud in healthcare insurance claims is one of the significant research challenges that affect the growth of the healthcare services. The healthcare frauds are happening through subscribers, companies and the providers. The development of a decision support is to automate the claim data from service provider and to offset the patient's challenges. In this paper, a novel hybridized big data and statistical machine learning technique, named MapReduce based iterative support vector machine (MR-ISVM) that provide a set of sophisticated steps for the automatic detection of fraudulent claims in the health insurance databases. The experimental results have proven that the MR-ISVM classifier outperforms better in classification and detection than other support vector machine (SVM) kernel classifiers. From the results, a positive impact seen in declining the computational time on processing the healthcare insurance claims without compromising the classification accuracy is achieved. The proposed MR-ISVM classifier achieves 87.73% accuracy than the linear (75.3%) and radial basis function (79.98%).

Purpose: With this study, the authors aim to design a measure to determine the effectiveness of having Forensic Auditors in the Insurance Business. Moreover, in doing this to determine whether this measure is affected by different demographic variables. Design/Methodology: To prove the effectiveness of forensic auditors in the insurance industry, the authors designed a questionnaire using criteria of effectiveness established by Bond et al. (2011) which was completed by 402 valid participants. The criteria revolved around having procedural, substantive, transactive and normative effectiveness. Findings: Results show that engaging forensic auditors in the insurance industry are effective. Forensic auditors are needed in the claims process of insurance firms, and possibly, they should further be engaged in the risk management team of an insurance company. However, with regards to determining the compensation amount, respondents showed a lack of trust, and prefer if forensic auditors w...

Purpose: With this study, the authors aim to design a measure to determine the effectiveness of having Forensic Auditors in the Insurance Business. Moreover, in doing this to determine whether this measure is affected by different demographic variables. Design/Methodology: To prove the effectiveness of forensic auditors in the insurance industry, the authors designed a questionnaire using criteria of effectiveness established by Bond et al. (2011) which was completed by 402 valid participants. The criteria revolved around having procedural, substantive, transactive and normative effectiveness. Findings: Results show that engaging forensic auditors in the insurance industry are effective. Forensic auditors are needed in the claims process of insurance firms, and possibly, they should further be engaged in the risk management team of an insurance company. However, with regards to determining the compensation amount, respondents showed a lack of trust, and prefer if forensic auditors w...

Extreme value theory is applied to model extreme occurrences, and it is applied in business and finance to measure tail risk. Marine and aviation class of insurance business is an important component of non-life business because it insures all risks relating to aviation and marine vessels which play a significant role in the economic development of Nigeria. Recent claims experience has necessitated the investigation of tail risks with small probability of occurrence but with high potential impact on company's survival. The study employs the Extreme Value Theory (EVT) to estimate the minimum expected claims for the marine and aviation insurance business using historical claims data. Diagnostics plot like the mean excess plot suggest the threshold to chosen, to fit Generalized Pareto model based on EVT and the excess distributions were obtained over a chosen threshold. Linear Q-Q plots and tail plots reveal that parametric model fits the data well. VaR estimate was finally obtained using the extreme value method at 5% confidence interval and the empirical results show that Extreme VaR is most suitable to calculate VaR as against the Historical and Gaussian methods. This will guide proper underwriting process and loss reserving in this class of business.

Extreme value theory is applied to model extreme occurrences, and it is applied in business and finance to measure tail risk. Marine and aviation class of insurance business is an important component of non-life business because it insures all risks relating to aviation and marine vessels which play a significant role in the economic development of Nigeria. Recent claims experience has necessitated the investigation of tail risks with small probability of occurrence but with high potential impact on company's survival. The study employs the Extreme Value Theory (EVT) to estimate the minimum expected claims for the marine and aviation insurance business using historical claims data. Diagnostics plot like the mean excess plot suggest the threshold to chosen, to fit Generalized Pareto model based on EVT and the excess distributions were obtained over a chosen threshold. Linear Q-Q plots and tail plots reveal that parametric model fits the data well. VaR estimate was finally obtained using the extreme value method at 5% confidence interval and the empirical results show that Extreme VaR is most suitable to calculate VaR as against the Historical and Gaussian methods. This will guide proper underwriting process and loss reserving in this class of business.

The ability to mine relational data has become important in several domains (e.g., counter-terrorism), and a graph-based representation of this data has proven useful in detecting various relational, structural patterns [1]. Here, we analyze the use of graph properties as a method for uncovering anomalies in data represented as a graph.

This study examined the Effect of general insurance cost of claims on gross claims of insurances industry in Nigeria. The motive of the work is anchored on the gap in the empirical where average cost per claims has not been used to evaluate the effect of cost of claims of general insurance policies on the gross claims of insurance industry in Nigeria. The main objective is to appraise the effect of general insurance cost of claims on gross claims of general insurance business in Nigeria. The specific objectives are to determine the average cost of: motor, general accident, and oil/gas insurances claims (independent variables) on the gross claims paid (dependent variable) by insurance firms in Nigeria. Ex-post facto research design was adopted while secondary data were sourced from CBN and NAICOM respectively. Auto regressive distributed lag (ARDL) model was employed in analysis. The investigation revealed that the impact of motor insurance claims and oil/gas insurance claims were positive and significant at (P-value of 0.00003 < 5% and a coefficient value of 4.16) and (P-value of 0.0085 > 5% and a coefficient value of 0.13) respectively. Similarly, general accident insurance claims were negative and significant at (P-value of 0.0010 < 5% and a coefficient value of -3.87). The implication of the finding is that the cost of settling motor and oil/gas claims is positive and significant while general accident insurance claims is negative and significant.  The study concluded that motor and oil/gas insurance policy claims have positive and significant impact while general accident had a negative and significant impact on the dependent variable. The study recommends among others that insurers should develop a mechanism to mitigate fraud within the claims department.  Consequently, insurers should be stringent and closely monitor losses and recovery with respect to general accident insurance given the time and its nature and equally insurers should form pools to underwrite oil/gas insurance in collaboration with loss adjusters to tap from expanded expertise skill.

Due to the complexity of the processes within healthcare insurance systems and the large number of participants involved, it is very difficult to supervise the systems for fraud. The healthcare service providers' fraud and abuse has become a serious problem. The practices such as billing for services that were never rendered, performing unnecessary medical services and misrepresenting non-covered treatment as covered treatments etc. not only contribute to the problem of rising health care expenditure but also affect the health of the patients. Traditional methods of detecting health care fraud and abuse are time-consuming and inefficient. In this paper, the health care insurance fraud and abuse detection system (HECIFADES) was proposed. The HECIFADES consist of six modules namely: claim, augment claim, claim database, profile database, profile updater and updated profiles. The system was implemented using Visual Studio 2010 and SQL. After testing, it was observed that HECIFADES was indeed an effective system for detecting fraudulent activities and yet very secured way for generating medical claims. It also improves the quality and mitigates potential payment risks and program vulnerabilities.

Insurance claims forecasting for extreme weather events that result in large scale destruction such as hurricanes, wildfires, floods, etc. is an important planning activity for insurance firms and any process improvements that can enhance the accuracy and quality of the forecasts should be welcome. This article provides an introduction to the forecasting methodology for insurance claims payouts and then discuss potential use of machine learning techniques to enhance the forecasting process.

Every year, billions of dollars are lost due to fraud in the U.S. health care system. Health care claims are complex as they involve multiple parties including service providers, insurance subscribers, and insurance carriers. Medicare is susceptible to fraud because of this complexity. To build a comprehensive fraud detection system, one must take into consideration all of the financial practices involved among the associated parties. This paper is focused on graph-based analysis of CMS provided Medicare claims data to look for anomalies in the relationships and transactions among patients, service providers, claims, physicians, diagnosis, and procedures. In our experiments, we create graphs from in-patient, outpatient, and carrier claims data of the beneficiary. We then demonstrate the potential effectiveness of applying graph-based anomaly detection to the problem of discovering anomalies and potential fraud scenarios.

India’s general insurance business is under a double squeeze of meager premium incomes and mega fire claims outgoes. How it got trapped in such an unenviable position is symbolic of poetic justice.
In the rudimentary stages, indemnity was but the whim of the haughty loss assessor, as his fancy would suggest, that the overawed insurers and the insured alike had to accept like a claim prasad. Though later on, the system had acquired some semblance of balance, yet the irony of inequity, more or less, remained the guiding factor for settling the claims of the small frays that were treated like serfs in the general insurance corridors. More often than not, owing to the insurers’ apathy, the claim processing was tortuous, accompanied by arbitrariness, occasioned by their ignorance or suspicion, and / or both. The hapless insured was hoodwinked to sign on the dotted line of the discharge voucher, or else. Some claim processing officials even went to the extent of maintaining dairies of their misdeeds, of coercive claim reductions, to boast about the savings thus accrued to the company. Just the same, at the same time, it was a red carpet, all the way, for the valued clients, more so when it came to their large losses.
This is the updated edition of my article "The Genesis of Over indemnity" published in  The Insurance Times, May 2001.

There occurred a fire mishap in the farmhouse belonging to a gentleman of leisure, which in due course engulfed the neighborhood nursery. Among the properties destroyed in the fire or damaged during the fire-fighting operations were a large number of garden plants, in both premises, which have been insured, coincidentally, with the same underwriting office. For uniformity in loss analysis and equanimity in assessment, the underwriters chose to entrust the survey assignments of both the claims to a single surveyor. Whereas the loss assessment with regard to the other damaged properties should pose no problem, as there are precepts and precedents to follow, the question of providing indemnity in respect of plants, to the respective insured's, calls for a deeper contemplation on part of the surveyor concerned. The fire policy unequivocally states that…….. "the company will pay to the insured, the value of the property at the time of the happening of its destruction or the amount of such damage, or at its option reinstate or replace such property or part thereof." What, in effect, is value? It is as per the Concise Oxford Dictionary, the ability of a thing to serve a purpose or cause an effect. What, then, is the value of the damaged plant to the respective insured's? To the landlord of the farmhouse, their value lies in the aesthetics they provide to the environs and the emotional feeling he derives from gardening them. However, to the nursery owner, the plants have an altogether different value, primarily mundane, in that they are the means by which he and his family get their livelihood from, through their sale, though he too may exult in their joyous presence. Thus, the value of the plants, property of similar nature, going by their ability to serve a purpose or cause an effect, is uniquely different to their respective owners. If one were to arrive at the amount of compensation, a cost of production mode, it would involve the cost of planting nascent seedlings or saplings, of the same or similar varieties, of the damaged plants, capping it up with an allowance for such of the expenses on gardening, like the cost of manure and watering charges, that have to be incurred, till they would have grown into plants of the destroyed description as at the time of the outbreak of fire. For the landlord, after he, in due course, psychologically overcomes his gloom, these seedlings and saplings, progressively create agreeable scenery, though different from the previous one, that too enlivens his environs, and thus would under the circumstances, apparently restore to him the value the damaged property hold for him. Thus the amount of compensation based on cost of production mode could fairly indemnify him for his material loss.

MSD and Work: A Critical Mapping (Disturbi muscolo-scheletrici e lavoro: una mappatura critica).

Trends in Italian and European health statistics show an exponential increase in work-related illnesses. Within the range of work-related illnesses there is a different incidence of “old and new illnesses”. Musculoskeletal diseases (from here on, MSD), along with work-related stress, are the main illnesses in the new mode of production. On the European level, 60% of work-related illnesses are due to MSD, with stress related illnesses being the second most common. And the growing trend in these illnesses seems to be unstoppable. In Italy, in recent years, there has been an exponential increase in MSD, almost certainly linked to the fact that INAIL has created a new list of insurable diseases. This has finally brought Italy in line with Europe. The research project “Musculoskeletal diseases and Work: A Critical Mapping” was the first attempt that we know of to bring together the study of the phenomenon of work-related MSD with that of insurance claims, with the aim of mapping MSD risk based on INAIL data.

The Italian scientific community is an international leader in studies regarding the medical causes of MSD, the instruments of risk valuation, and solutions of an ergonomic nature. But there has been little work done studying insurance claims to deepen the understanding of the macro dynamics of MSD. The most recent Eurogip report on work-related illnesses also points out that Italy lacks an in depth study of insurance claims. Apart from the annual reports of INAIL that simply describe the current state of things, there are few attempts to understand the phenomenon of MSD in an inter-disciplinary manner. For example, in France the study of this phenomenon has brought together heterogeneous disciplines: from medicine to sociology, from ethnography to jurisprudence, from ergonomy to economy. To analyse MSD workplace illnesses in Italy on a macro level, one has to begin from the INAIL insurance data, as it is the only source of such information in Italy, after the stalling of a project by the National Register of Work Place Illnesses (Registro Nazionale delle malattie professionali) to epidemiologically map MSD. It is important to affirm from the start that insurance claims relating to workplace-illnesses are a ‘social fact’ and not simply a medical fact. This affirmation is the thread that links – in the different studies of the two authors – the chapters that follow this introduction.

As Hatzfeld notes in his historiographical work on the subject in France, work-related MSD has been recognised since Ramazzini (18th Century father of work-related medicine), but it only became a social question once it was political accepted, legally recognised and quantified in insurance claims. The fact that this process is based on political and social choices is clear from the fact that Italy lags 36 years behind France in its professional recognition of MSD (happening in 2008 and 1972 respectively), and also from the fact that in Italy there exist important territorial and sectorial distortions both in trends in insurance claims and in the recognition of those claims. Obviously choosing to begin from all insurance claims made and not only from those illness positively recognized by the insuring institution, is a choice that allows us to investigate the diverse dynamics inherent in the processes of recognition, and to see that they are also subject to distortions.

INAIL’s statistics naturally constitute the base of the official reporting on work-place accidents and illnesses, as well as being used for the calculation of insurance premiums that – as a function of estimated risk – businesses have to pay to the Institute. They also constitute the principle source of information systems on the surveillance of work-related illnesses (such as the MalProf project and Flussi Informativi INAIL-Regioni). The objective of the project was therefore primarily to develop a method of analysis that attempted to partially reveal the dynamics that underlie insurance claims and their recognition allowing us to say something more about the trends of MSD in Italy. The key for the development of such methodologies has been identified in our analysis of different territories, in particular at the provincial level and in the productive sector. The objective of the investigation has been to discriminate as much as possible between these components: the behaviour of businesses and the related sectors; the behaviour of the claims of insured labourers; the decision making behaviour of INAIL in its role as insurance body; and the role of other institutional actors/factors. This approach has brought to light new issues, as well as deepening investigations already present in the literature. It reveals the phenomenon of MSD in all its complexity, a subject until now underestimated in Italy, in which territorial differences distort the figures beyond those logically expected in the different productive sectors.

This report is the fruit of the independent work of the two authors, who have partial differences in the interpretation of the subject matter and have concentrated on different chapters. Chapter 1 is dedicated to a general outline of the phenomenon of MSD, while Chapter 2 presents the theoretical framework of the phenomenon of insurance claims. Chapter 3 gives a complete illustration of the dataset used in the analysis, presents the descriptive evidence, and describes the problems we met in the application of the administrative data supplied by the 2013 edition of Flussi informativi Inail-Regioni. Chapter 4 is dedicated to the statistical analysis of the phenomenon of insurance claims and their recognition from an economic-organisational and sociological perspective. Chapter 5 reconstructs the framework of Italian institutions in which the analysis of MSD insurance claims are situated. Chapter 6 engages in statistical analysis of the phenomenon of insurance claims and their recognition from a economic-juridical perspective as well as a politological persepective, as outlined in Chapters 2 and 5.

The research was carried out as part of a study on health and safety at work by the Marco Biagi Foundation, and thanks to funding by the foundation of the Banca nazionale delle comunicazioni. The data with which the research was carried out – Flussi informativi Inail regioni, 2013 Edition – was provided by the Epidemiology Unit ASL TO3, in the region of Piedmont. The authors would like to thank: the institutions that allowed this work to happen; the coordinators of the research project, Ylenia Curzi and Iacopo Senatori, the researchers within the Marco Biagi Foundation; Angelo D’Errico and Osvaldo Pasqualini from Epidemiology Unit ASL TO3; and Giuseppe Fiorani from University of Modena and Reggio Emilia, for their advice and their help in filling the gaps in our knowledge.

(FULL TEXT IN ITALIAN: http://www.fmb.unimore.it/on-line/home/ricerca/pubblicazioni/quaderni-fondazione-marco-biagi/documento9387.html )

Uno dei primi articoli inerente la patologia muscolo-scheletrica del musicista risale al 1885, quando Forbes ha descritto il successo raggiunto tramite la tenotomia di un tendine accessorio del mignolo dell'estensore comune delle dita per migliorare l'agilità di un pianista che lamentava impaccio funzionale durante la performance musicale (1). Sempre alla fine del diciannovesimo secolo risalgono studi su crampi dolorosi di pianisti e violinisti (2, 3).

Le attività di prevenzione dei rischi e dei danni legati al lavoro non possono prescindere da un adeguato sistema informativo Per orientare gli interventi e le azioni di prevenzione e per valutare i risultati delle azioni intraprese, occorrono informazioni sistematiche almeno su dove sono situati e quali sono i luoghi di lavoro, quali sono i cicli lavorativi, le modalità di lavoro ed i rischi a queste collegati, quali sono i conseguenti danni alla salute conosciuti. L'iniziativa dei flussi informativi INAIL-ISPESL-Regioni si pone come una progressiva soluzione verso un Sistema nazionale integrato nazionale per la prevenzione nei luoghi di lavoro, con l'obiettivo di risolvere gradualmente una situazione di carenza informativa che ha contrassegnato gli anni novanta. Si tratta di una soluzione come detto progressiva, per alcuni aspetti incompleta ma che già comporta una considerevole ricchezza di informazioni almeno relativamente alla distribuzione e localizzazione delle imprese, alla distribuzione degli infortuni e delle patologie professionali, alle tipologie, caratteristiche e modalità di insorgenza degli stessi. I "Nuovi Flussi" si basano su un accordo tra i 3 soggetti ("codificato" con la firma del Protocollo d'intesa del 25 luglio 2002), riferito soprattutto agli scambi informativi dal centro ai territori e viceversa attraverso i quali: