Empirical Evidence on the Use of Credit Scoring for Predicting Insurance Losses with Psycho-social and Biochemical Explanations

An important development in personal lines of insurance in the United States is the use of credit history data for insurance risk classification to predict losses. This research presents the results of collaboration with industry conducted by a university at the request of its state legislature. The purpose was to see the viability and validity of the use of credit scoring to predict insurance losses given its controversial nature and criticism as redundant of other predictive variables currently used. Working with industry and government, this study analyzed more than 175,000 policyholders’ information for the relationship between credit score and claims. Credit scores were significantly related to incurred losses, evidencing both statistical and practical significance. We investigate whether the revealed relationship between credit score and incurred losses was explainable by overlap with existing underwriting variables or whether the credit score adds new information about losses not contained in existing underwriting variables. The results show that credit scores contain significant information not already incorporated into other traditional rating variables (e.g., age, sex, driving history). We discuss how sensation seeking and self-control theory provide a partial explanation of why credit scoring works (the psycho-social perspective). This article also presents an overview of biological and chemical correlates of risk taking that helps explain why knowing risk-taking behavior in one realm (e.g., risky financial behavior and poor credit history) transits to predicting risk-taking behavior in other realms (e.g., automobile insurance incurred losses). Additional research is needed to advance new nontraditional loss prediction variables from social media consumer information to using information provided by technological advances. The evolving and dynamic nature of the insurance marketplace makes it imperative that professionals continue to evolve predictive variables and for academics to assist with understanding the whys of the relationships through theory development.     

预约定价与税收公平原则关系之探究

预约定价作为调整跨国公司转移定价的新制度体现了税收效率原则,但这一制度是否同样体现了税收公平原则值得认真研究。本文通过对预约定价与税收公平原则相互关系的剖析,重点考察了预约定价影响税收公平原则的若干因素,并结合我国预约定价的实践,得出了相应的结论。     

A Robust Unsupervised Method for Fraud Rate Estimation

If one is interested in managing fraud, one must measure the fraud rate to be able to assess the degree of the problem and the effectiveness of the fraud management technique. This article offers a robust new method for estimating fraud rate, PRIDIT‐FRE (PRIDIT‐based Fraud Rate Estimation), developed based on PRIDIT, an unsupervised fraud detection method to assess individual claim fraud suspiciousness. PRIDIT‐FRE presents the first nonparametric unsupervised estimator of the actual rate of fraud in a population of claims, robust to the bias contained in an audited sample (arising from the quality or individual hubris of an auditor or investigator, or the natural data‐gathering process through claims adjusting). PRIDIT‐FRE exploits the internal consistency of fraud predictors and makes use of a small audited sample or an unaudited sample only. Using two insurance fraud data sets with different characteristics, we illustrate the effectiveness of PRIDIT‐FRE and examine its robustness in varying scenarios.     

‘Created’ enclaves for enterprise: an empirical study of Singapore's industrial parks in Indonesia,Vietnam and China

The dynamics of globalization have prompted governments to re-examine accustomed policies, and search for alternative strategies, in order to re-position their economies for the future. This paper explores the spatial context of state involvement in the new economics of competition, with the focus on Singapore's much publicized, and controversial, orchestration of its state enterprise network to encapsulate economic space for Singapore-based firms to expand into the Asian region. This strategic initiative is promulgated on the exportability of Singapore's ‘state credibility’, systemic and operational efficiencies, and technological competencies, to locations where these attributes are less certain. A logit model is applied to questionnaire surveys culled from Singapore's industrial-township projects in Indonesia, Vietnam and China and the findings are presented. The authors conclude that the strategic advantage created for the firms within these privileged investment enclaves, although remarkable, is often at risk from the administrative complexities, and socio-political milieux, of the host environments.     

高校财务风险的防范与控制

高校的财务风险又称筹资风险,是指由于举债而给高校财务成果带来的不确定性。有效开展银校合作,实行适度举债办学,是一种客观经济现象,它对于缓解高校事业发展与经费短缺矛盾,实现学校快速发展有着重要的作用。但是,举债经营需还本付息,而高校毕竟不同于企业,不以盈利为目的,收益和偿债能力有限,一旦无力偿付到期债务,高校便会陷入财务困境甚至破产。这就要求高等学校在举债时,必须采取各种措施,防范和控制财务风险的出现。一、树立风险观念学校资金结构中债务所占的比例越大,财务风险就越大。相反,债务比例越小,财务风险就越小。举债的风险…     

贵州省养老服务产业需求与发展障碍调查研究

以问卷调查方式,在对贵州省5个市区养老服务机构进行走访调查的基础上,分析了贵州省养老服务产业的供给与需求概况,提出促进养老服务产业发展的建议,主要包括完善城乡基本养老保险制度,促进区域经济协调展;加大政策宣传力度,改变养老传统观念;整合资源供给,实现医养结合优势互补;精确服务定位,提升养老机构服务水平。     

浅析后金融危机时代中国经济发展前景与走势

由美国次贷危机引发的全球金融危机深刻影响世界与中国。在后金融危机时代中,中国经济发展前景和走势如何,如何找准中国定位并制定相应策略以促进中国经济可持续发展成为当今学界研究的重中之重,也为进一步拓宽并延展中国自身经济转型研究提供思路和分析。     

产能过剩影响商业银行不良贷款率的机制--基于各省市面板数据的实证研究

选取2005年到2014年中国31个省级单位面板数据,采用静态面板和动态面板计量模型,分别从企业存货规模和产能利用率两个角度实证考察了产能过剩与不良贷款率的关系。研究结果表明:企业存货规模变动对商业银行不良贷款影响显著为正,产能利用率对商业银行不良贷款影响显著为负;由此表明,产能过剩是引起商业银行不良贷款规模上升的重要原因。据此,建议政府坚定不移的推动去产能步伐,以有效控制产能过剩带来的金融风险。     

二元市场视角下的B2B交易效率影响因素分析及建议

在二元市场演变的过程中,结合基本交易成本理论,综合B2B电子商务当前的形势以及存在的问题,找出B2B电子商务交易效率的影响因素。通过对B2B电子商务虚拟市场与传统实体市场的交易总成本进行分析与对比,结果表明,B2B电子商务在虚拟市场条件下的交易效率与市场交易总成本呈反比关系,要提高B2B电子商务交易效率,需要降低各个环节的交易成本。文章结合影响因素从三个方面分析如何降低交易成本,提高企业绩效,对于大中型企业转型以及B2B电子商务的运营发展提供一定的改进策略及建议。     

推进东中西一体化促进西部大开发

在充分发挥东部地区港口和港口城市作用的基础上,进一步推进我国东部中部西部经济一体化,是实施“西部大开发”的重要途径。 东中西一体化是今日大背景的要求 跨入新世纪,我国经济面临迎接加入WTO、实施西部大开发、加快城市化三个新课题。每个课题都有许多专门工作要做。但运作起来,都不能孤立地进