大数据背景下的银行风险管控

在大数据背景下,让数据信息应用发生了巨大变化,也加快了银行经营和风险管理方式的变革,让风险识别、防范以及提高效率等有了更多全新理念.银行要用好大数据技术,加强对各种风险的管控,为自身稳定发展创造良好的条件.本文将简述银行运用大数据管控风险的优势,并提出了具体可行的策略.     

做好大数据背景下的税收调查工作的思考

数据是帮助我们认识世界、找出问题、想出办法的基础,数据质量如何,决定了我们对事物的认知及分析建议是否客观正确。正如西谚所云:"除了上帝,任何人都必须用数据说话"。云计算奠定了大数据年代的技术支撑,财税、金融与各行业的横向联网构成了财税部门大数据时代,它是信息发展到今天一个海量数据库并对其分析应用有迫切性需求的时代产物。税收数据是经济运行的晴雨表之一,直接反映了经济运行状况,不但对政府决策和预算有价值,而且对社会公众生活、生产、投资决策有不可估量的价值。税收统计调     

大数据时代的财务会计转型分析

信息技术的发展让大数据技术进入到人们生活中的很多领域,它使人们更容易获取总体数据来进行分析预测,使研究和判断不再局限于样本抽样。在大数据时代背景下,企业的财务与业务都发生了很大变化,随着大数据技术的应用范围越来越广,传统意义上按照会计准则规定主要进行事后核算的财务会计将逐渐被人工智能取代,向以分析预测为主的管理会计转型成为发展的必然。     

大数据时代与自由贸易区

大数据时代是什么意思呢?据维基百科对"大数据"的定义是:无法在允许的时间里用常规的软件工具对内容进行抓取、管理和处理的数据集合。那么,大数据时代和自由贸易区又有什么关联呢,笔者以为有以下三个方面的关系:第一,大数据时代和自由贸易区都是世界经济一体化进程的必然要求。大数据时代实质上是信息化时代进一步深化的表现形式,它能使经济进一步深化所要求的国际化全球化的实施更加便捷和有效,以人才和技术而论,任何地区进入工业化信息化发展都需要高层次人才和技术的参与。第二,自由贸易区以大数据时代为技术支撑。第三,"大数据时代"以自由贸易区等经贸模式为载体。任何科学技术进步都是以人类的需求为目标的,任何客观存在都有其复杂性,而且也不会有终点,总是具有无穷无尽的性质,所谓"一块石头可以累死一百个科学家",就是说明事情性质的不可穷尽性。     

大数据时代背景下的技术创新研究

我国目前已经初步建立起了知识产权服务体系,为我国企业技术创新和知识产权战略的实施提供了大量的知识产权服务,是我国企业开展技术创新和知识产权活动的重要辅助力量.如何让我国技术创新管理研究工作迅速适应大数据环境,更好的利用大数据技术创新,保护知识产权,并有效利用大数据环境产生的空前机遇与挑战,发展我国技术创新研究,是我国科研工作者不可避免并必须慎重考虑、深入研究的重要问题.深入研究大数据环境下技术创新的新变化与新思路,思考并探索如何让我国技术创新管理工作迅速适应大数据环境,并有效促进我国的技术创新发展.提升我国基于对知识产权的保护下技术创新研究在大数据环境下不断前进的能力,并使得我国的技术知识产权成为国家利用科技优势,利用大数据科技进步利益的工具,提高国家间技术先进性的竞争能力.     

大数据在银行业务管理中的应用

在以大数据技术为时代发展特点的大背景下,阐述了大数据技术在银行业务管理应用中的基本状况,包含大数据技术给传统金融业务带来的冲击及发展机遇.最后重点探讨了改善大数据在银行业务管理应用中的效果的措施,以期为相关银行业务管理工作者提供借鉴.     

大数据与生产力

大数据开启了新时代,它正在改变我们的思维与生活以及理解世界的方式,成为创新生产和服务的源泉。当我们研究未来我国生产力发展的时候必须要考虑大数据的影响。有专家指出"大数据与云计算是一个问题的两面,一个是问题,一个是解决问题的方法"。因此,要认识大数据必须要认识云计算。可以说,云计算是大数据时代的系统工程。本文研究了大数据的概念和特征,分析了大数据云计算的通用技术属性,论证了大数据对生产力的影响、表明了大数据促进各行业生产力发展的方面,在全面分析的基础上,提出了我国发展大数据—云计算的思考等几部分。本文对大数据对生产力的影响做了概括的论述。     

大数据时代下电子商务发展现状思考

大数据时代为电子商务的发展提供了诸多机遇与挑战.一方面,大数据技术能够提高电商营销的准确率,提升消费者体验;另一方面也存在数据信息安全、处理技术等多方面问题.本文结合大数据时代电商的发展特点,提出相应对策,希望帮助相关企业进行决策.     

论述大数据时代企业人力资源绩效管理创新

时代的发展和推进,让我们日渐进入大数据时代.在当前的大数据环境下,企业如何进行人力资源绩效管理,如何让人才在企业中发挥重要作用就显得尤为迫切.基于此,本文就大数据时代企业人力资源绩效管理创新进行分析,以供参考.     

资本赋权下的数据殖民及其批判

数字技术革新使人类社会面临数字化转型并进入以“数据”资源的生产和获取为核心的数字化时代。数据来源于人类实践,其价值生成于数字技术与人类实践的辩证运动,资本家凭借对数字技术的掌控对人类行为数据进行无规制攫取和垄断。在“数字”思维和资本逻辑的合谋下,世界一切可量化的事物都被数字化解构,人类面临数据殖民风险,人的生命政治遭受全面剥削和异化。数字技术垄断所造成的数字平台霸权以及后续引发的数据殖民行径及数字帝国主义的抬头,都源于资本权力的无规制泛用和滥用。对此,必须从思想、经济、制度、技术以及人的解放这五个维度全方位、多层次地对资本权力加以规制,推动数据从“私人占有属性”到“全体个人所有”,实现数据的社会主义应用,从根源上解决数据殖民问题。     

大数据背景下网络众包驱动科技创新的机理及路径研究

增强科技创新能力是建设创新型国家、提高综合国力的关键,大数据时代的到来为科技创新领域带来了前所未有的机遇与挑战,网络众包这一新型创新模式应时而兴。紧紧把握时代发展主题,发现并描述大数据环境下科技创新的新变化、新要求、新问题,从动力源、集聚效应、协同效应和规模效应等方面探讨了网络众包驱动科技创新的机理,并创新性地提出了网络众包模式下的科技创新实现路径,以期为推动我国科技创新提供新思路。     

Big data and complexity: Is macroeconomics heading toward a new paradigm?

The paper discusses the extent to which the availability of unprecedentedly rich data-sets and the need for new approaches – both epistemological and computational – is an emerging issue for Macroeconomics. By adopting an evolutionary approach, we describe the paradigm shifts experienced in the macroeconomic research field and emphasize that the types of data the macroeconomist has to deal with play an important role in the evolutionary process of the development of the discipline. After introducing the current debate over Big Data in social sciences, the paper presents a detailed discussion of possible and existing interactions between Big Data and Computational Behavioral Macroeconomics. We argue that Big Data applied to economic questions can lead to new styles of thinking and research methods, namely to the development of a new research paradigm.     

Using ‘big data’ to validate claims made in the pharmaceutical approval process

Abstract

Big Data in the healthcare setting refers to the storage, assimilation, and analysis of large quantities of information regarding patient care. These data can be collected and stored in a wide variety of ways including electronic medical records collected at the patient bedside, or through medical records that are coded and passed to insurance companies for reimbursement. When these data are processed it is possible to validate claims as a part of the regulatory review process regarding the anticipated performance of medications and devices. In order to analyze properly claims by manufacturers and others, there is a need to express claims in terms that are testable in a timeframe that is useful and meaningful to formulary committees. Claims for the comparative benefits and costs, including budget impact, of products and devices need to be expressed in measurable terms, ideally in the context of submission or validation protocols. Claims should be either consistent with accessible Big Data or able to support observational studies where Big Data identifies target populations. Protocols should identify, in disaggregated terms, key variables that would lead to direct or proxy validation. Once these variables are identified, Big Data can be used to query massive quantities of data in the validation process. Research can be passive or active in nature. Passive, where the data are collected retrospectively; active where the researcher is prospectively looking for indicators of co-morbid conditions, side-effects or adverse events, testing these indicators to determine if claims are within desired ranges set forth by the manufacturer. Additionally, Big Data can be used to assess the effectiveness of therapy through health insurance records. This, for example, could indicate that disease or co-morbid conditions cease to be treated. Understanding the basic strengths and weaknesses of Big Data in the claim validation process provides a glimpse of the value that this research can provide to industry. Big Data can support a research agenda that focuses on the process of claims validation to support formulary submissions as well as inputs to ongoing disease area and therapeutic class reviews.     

Introducing the Longitudinal Multi‐Agency Data Integration Project and Its Role in Understanding Income Dynamics in Australia

The opening up of access to data from the Multi‐Agency Data Integration Project provides an opportunity to fill a number of research gaps on inequality in Australia. Our paper begins the external validation of these data, focusing on what the data can tell us about the distribution, dynamics and determinants of income in Australia. It has the potential to shed new light on these aspects, but the dataset should be used with caution, taking into account some key limitations, including incomplete linkage and more limited income information for those who do not complete a tax return.     

企业大数据能力:研究综述与未来展望

大数据给企业带来变革性影响，也带来许多挑战。学者借鉴IT能力提出大数据能力概念，但对大数据能力的定义、性质和测量维度等内涵未达成统一认识，不利于深入研究。回顾了大数据能力现有研究，阐述了大数据能力的内涵及其与相似构念的异同，并基于资源基础观整合了目前大数据能力的结构维度。同时,还总结了大数据能力给企业带来的组织层价值。最后，提出了4个研究方向：①区分大数据能力与大数据支持能力，并探究大数据能力价值实现机制；②进一步明确大数据资源形成大数据能力的过程；③进一步探索不同类型企业大数据能力的差异及其影响因素；④借鉴相似构念的研究成果并用于大数据能力相关研究，进一步整合相关理论，避免其陷入碎片化。     

Measurement of Quality of Life and Well‐Being in France: The Drivers of Subjective Well‐Being

Ever since the publication of the Stiglitz Report, France has been heavily involved in the measurement of well‐being. The French Statistical Institute (INSEE) has expanded the scope of its existing surveys. It has also launched an innovative experimental survey which, drawing upon a single statistical source, aims for the first time to explore the different dimensions of both objective and subjective quality of life, as highlighted in the Stiglitz Report. It allows us to study, at the individual level, correlations between these dimensions and the accumulation of deprivations. It has enabled us to better understand the links between determinants generally referred to as objective dimensions of quality of life (such as health or education) and subjective well‐being. This information is of paramount importance for policy makers who cannot act directly on the level of people's satisfaction but can only act upon the levers of objective dimensions. This paper presents the main findings of the experimental survey.     

THE IMPACT OF NEW ACCOUNTING STANDARDS ON JAPANESE COMPANIES

Abstract. As a result of a series of reforms initiated in the latter half of 1990s, accounting standards in Japan have become virtually equivalent to international accounting standards. The impact of the accounting reform on Japanese firms has been significant. This paper reviews the so‐called ‘Accounting Big Bang’ and assesses its impact on Japanese firms. It concludes that Japanese firms are now required to place greater emphasis than previously on an improvement in the return on their assets and on an enhancement in the values of their stock market shares.     

Big Players in Slovenia

The subjectivism of Austrian economics helps to explain the statistical fact of long memory in asset prices. The theory of Big Players is an Austrian approach to understanding the effects of discretionary policymaking in markets. It leads to implications that can be tested with statistics. In particular, Big Players induce herding and, thereby, an increase of persistence in asset prices. A recent episode in Slovenian monetary theory provides a case study. This case study adds to a set of similar studies, all tending to support the theory of Big Players.     

The status of modeled claims

Abstract

The only acceptable modeled claims for costs and outcomes are those that are testable and can be validated in a timeframe that is acceptable to a formulary committee. This issue provides four papers which explore the methodological issues in validation, the UK experience with NICE, the questions a formulary committee should ask of modeled claims, and the role of Big Data in validating modeled claims.     

卖空机制、诉讼风险与审计收费

基于我国推出融资融券业务这一“自然实验”,文章考察了卖空机制如何通过改变诉讼风险而影响公司审计收费。研究发现,卖空机制的引入增加了公司股价下跌的压力,并增强了投资者挖掘公司负面消息的动机,从而导致公司审计的诉讼风险提高,会计师事务所要求更高的审计收费。进一步的分析显示,由于国有企业的信息披露环境较差,卖空机制对国有企业审计收费的提升作用更加明显;由于“四大”具有更高的赔偿能力,卖空机制更加显著地增加了“四大”审计公司的审计收费;对于法制环境较差地区的企业,由于管理层更有动机隐藏坏消息,公司审计收费因卖空机制的存在而显著提高。