Article

Big data’s role in expanding access to financial services in China

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Abstract

General consumer and business finance companies have had limited success in serving the needs of economically active low-income families and micro-enterprises cost-effectively and sustainably in emerging economies such as China. Recent advances in computing and telecommunications technology are dramatically transforming this landscape by changing the way the financial industry operates. A key mechanism underlying this transformation concerns the use of big data in assessing, evaluating and refining the creditworthiness of potential borrowers and reducing the transaction costs. While China’s internet-only banking industry is currently small and some activities of players in this industry are akin to those in the shadow banking, this industry has potential to cause a major disruption in the Chinese financial market. A main objective of this paper is to examine the role of big data in facilitating the access to financial products for economically active low-income families and micro-enterprises in China. A second objective is to investigate how formal and informal institutions facilitate and constrain the use of big data in the Chinese financial industry and market. The paper also investigates how various inherent characteristics of big data – volume, velocity, variety, variability and complexity – are related to the assessment of the creditworthiness of low-income families and micro-enterprises. Case studies of big data deployment in the Chinese financial industry and market are discussed. The paper also looks at various categories of personal financial and non-financial information that are being used as proxy measures for a potential borrower’s identity, ability to repay and willingness to repay. Various business models involving the sources of data (internal vs. external to the big data organization) and providers of credits (big data organization vs. external partners or clients of the big data organization) are investigated. The analysis of the paper indicates that the main reason why low-income families and micro-enterprises in China and other emerging economies lack access to financial services is not because they lack creditworthiness but merely because banks and financial institutions lack data, information and capabilities to access the creditworthiness of and effectively provide financial services to this financial disadvantaged group.

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... Recently, China's digital finance has made great progress with the maturity of a series of information technologies, such as big data, cloud computing, blockchain and artificial intelligence. A few scholars found that digital finance challenges conventional one in many fields, such as operation mode, market participants, and trading tools (Kshetri, 2016;Gomber et al., 2017;Wu et al., 2018;Yao et al., 2018;Yin et al., 2019;. In terms of promoting green technology innovation, digital finance is beneficial to broaden the source of funds, reduce information asymmetry, and diversify risks in a wider range. ...
... Credit and risk control are extremely important for financial market to fulfill its role as a matcher between borrowers and lenders (Masmoudi et al., 2019). Digital finance can evaluate the credit and risk of consumers with big data technology, and lessen information asymmetry between financial institutions and consumers (Kshetri, 2016;Dendramis et al., 2018). GTI, as an investment object with huge risks and high returns, will be widely informed by investors, promoting its access to financing. ...
Article
Conventional finance has many deficiencies in promoting green technology innovation (GTI) and energy-environmental performance (EEP). The emerging digital finance is filling the gaps left by conventional finance with the support of information technology. Using panel data from 2011 to 2017, the paper explores the impact of digital finance on energy-environmental performance in China. The results show that digital finance significantly improves China's energy-environmental performance, which remains robust after a series of tests. Green technology innovation is the transmission path through which digital finance affects energy-environmental performance. The impact mechanism test proves that digital finance affects pure technical efficiency rather than scale efficiency. Furthermore, we also find that digital finance has a greater stimulus effect on energy-environmental performance where credit and capital markets are more immature. Financial supervision and environmental regulation from the Chinese government can reinforce the role of digital finance in promoting energy-environmental performance. Our study suggests that China should accelerate digitization in the financial markets, particularly in pursuit of its energy-saving and emission-reduction effects.
... . (Kshetri, 2016) . ‫التعقيد‬ Complexity ‫من‬ ‫يكون‬ ‫حيث‬ ‫املصادر،‬ ‫من‬ ‫كبرية‬ ‫جمموعة‬ ‫من‬ ‫البيانات‬ ‫مجع‬ ‫يتم‬ ‫حيث‬ ‫البيانات،‬ ‫مصادر‬ ‫تعدد‬ ‫إىل‬ ‫التعقيد‬ ‫ويشري‬ ‫املتجانسة‬ ‫غري‬ ‫البيانات‬ ‫ومعاجلة‬ ‫وختزين‬ ‫وتنظيف‬ ‫مجع‬ ‫الصعب‬ (Kshetri, 2016) . . ) ...
... . (Kshetri, 2016) . ‫التعقيد‬ Complexity ‫من‬ ‫يكون‬ ‫حيث‬ ‫املصادر،‬ ‫من‬ ‫كبرية‬ ‫جمموعة‬ ‫من‬ ‫البيانات‬ ‫مجع‬ ‫يتم‬ ‫حيث‬ ‫البيانات،‬ ‫مصادر‬ ‫تعدد‬ ‫إىل‬ ‫التعقيد‬ ‫ويشري‬ ‫املتجانسة‬ ‫غري‬ ‫البيانات‬ ‫ومعاجلة‬ ‫وختزين‬ ‫وتنظيف‬ ‫مجع‬ ‫الصعب‬ (Kshetri, 2016) . . ) ...
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In the context of the increasingly prominent contradiction between economic development and ecological environment, how to promote green development has become the core of sustainable economic development. Digital finance is an innovative financial model with a high degree of integration of finance and digital technology and provides a new opportunity for achieving green development. Based on identifying the mechanisms of digital finance and environmental regulation on green development efficiency, this research uses the directional distance function and Malmquist-Luenberger index to measure the green development efficiency of 30 provinces in China from 2011 to 2020 and then employs a dynamic panel GMM model to empirically analyze the relationships among digital finance, environmental regulation, and green development efficiency. The results of the study show the following. 1) Digital finance contributes to the efficiency improvement of green development. 2) Environmental regulation has not yet crossed the Porter’s inflection point and still has a dampening effect on green development efficiency. 3) The synergy between digital finance and environmental regulation has a positive impact on green development. 4) Digital finance alleviates the financing constraints arising from environmental regulation and to some extent weakens the negative effect of environmental regulation on the efficiency of green development. In view of this, the government should give full play to the active role of digital finance in eco-environmental governance, optimize the top-level design of environmental regulation, and promote industrial structure upgrading and optimal allocation of financial resources.
... At the same time, many business decisions that were originally made by enterprises themselves are beginning to require government intervention. For example, data privacy provisions between Internet enterprises and users are no longer purely commercial, and the determination of their relevant content requires direct government intervention (Nir, 2016). Another example is that the pricing of innovative drugs is not the result of maximizing the company's own revenue, but is often agreed upon by the government and the company with reference to clinical value. ...
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The combination of technology and finance has a great potential impact on regional social and economic development, and strategic emerging industries are the convergence of technological innovation and financial support, the development of which have great significance for industrial structure adjustment and industrial quality improvement. The geographical distribution of emerging strategic industries in China is uneven. We selected 18 provinces with relatively concentrated emerging industries. 206 STI board enterprises in 2020 were collected. A three-stage DEA model was used to measure the input–output efficiency of the integrated development of science and technology finance. Also, we used a regression model to examine the path of integrated development of science and technology innovation and financial support. The research finds that the development of strategic emerging industries has a large demand for financial support and obvious regional differences, and the government plays a strong guiding role in their development as well. At the end of the research, countermeasures and suggestions for the development of strategic emerging industries are given.
... The informational opacity in financial markets leads to difficulty with external financing for enterprises [45,46]. The Internet reduces corporate financing constraints by providing convenient financing information transmission services, ultimately supporting the green innovation activities of enterprises. ...
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Green technology innovation has become a breakthrough topic in the coordinated development of economic growth and environmental protection. Although the Internet is likely to become a key driver of transformative environmental change and innovation, studies on the impact of internet infrastructure on green innovation and analyses of the paths are still extremely scarce. Based on a sample of China’s listed companies from 2009 to 2019, this paper treats the Broadband China pilot strategy as a quasi-natural experiment and adopts the time-varying difference-in-differences (DID) model to explore the effect and the transmission path of internet infrastructure construction on green innovation. The study finds that Broadband China significantly promotes green innovation, and the result remains consistent after a series of robustness tests. The transmission path test proves that internet infrastructure construction affects green innovation by improving the degree of informatization, human capital, and internet media reports and by reducing financing constraints. Furthermore, considering the heterogeneity effect, the Broadband China strategy has a greater stimulating effect on state-owned, large-scale, high-tech enterprises; enterprises in low-competition industries; enterprises in growth and mature stages; and enterprises registered in the central and eastern regions. This paper systematically analyzes the effects of internet infrastructure on the green innovation of enterprises based on economic informatics theory, providing new insights for improving internet infrastructure and green innovation in practice.
... Thus, a complete information monitoring system and risk assessment system can be set up accordingly (Du et al., 2021). This method not only improves the information transparency of enterprises and avoids credit discrimination under the influence of information asymmetry (Kshetri, 2016;Dendramis et al., 2018), but also simplifies the credit review and evaluation process of enterprises and improves their financing efficiency (Gomber et al., 2018;Feng et al., 2022). Therefore, digital finance can meet the capital needs of enterprises through the capital replenishment effect and efficiency improvement effect, thereby mobilizing the innovation initiative of enterprises, and enhancing the innovation ability of green technology. ...
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... Furthermore, the conventional detachment between energy makers and customers keeps on obscuring as the energy framework becomes more disseminated and digitalized. The union of these advancements, every problematic without help from anyone else, enhances openings for change (Kshetri, 2016). The union of troublesome advancements, changing expense structures, and the worldwide powers depicted above can prompt and build up the ascent of digitalization stages. ...
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The financial sector is undergoing a vast transformation. It used to be physical, and now it uses I.T. and big data techniques and unique human capital. Before the transformation started, the financial sector started becoming intertwined with a high proportion of the intermediary activities and started getting market-based. For instance, banks face higher competition from the other intermediaries and increased digital services in core businesses like advisory and payment services. Many changes in using technology for developing new business models and services have been emerging with a rise in FinTech services. This can be easily understood as modern-day innovative information technology in the financial sector increases day by day. The speed with which different types of new digital innovations are being adopted and the acquisition of the users has increased markedly.
... Many large companies in developed and developing countries direct their investments in creating a cloud-based computing environment to better allocate resources, analyse financial needs and requirements, and establish an effective financial management system to achieve stakeholders' financial goals [13]. Companies are focused on sustainably improving shareholders' wealth. ...
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The rapid development of advanced technologies like Internet of Things (IoT), Cloud computing, big data analysis has enabled in transforming the financial management system effectively. Many large enterprises in developed and developing countries are channelising their investment in setting up cloud computing environment so as to offer better resource sharing, analyse the financial needs and requirements, establish effective financial management system so as to achieve the financial goals of the stakeholders. Business enterprises focuses in enhancing the wealth of the shareholders in a sustainable manner, moreover the organisation tend to perform millions of financial transactions like receipt of cash, making payments to suppliers, vendors, partners, franchises etc. hence, it is highly significant to implement sophisticate financial management system so that the transactions can be monitored and processed effectively. Also, the management needs real time information for making quick analysis and take informed decisions. Cloud computing service providers tend to offer array of innovative services which can be accessed by the business on their platforms, this helps the top management to implement better operating and financial management models for enhancing revenues, create better allocation of budget, manage the investment, automating the payments and effectively use the cash resources for enhancing better return on investment and support in increasing wealth to the shareholders. KOREA REVIEW OF INTERNATIONAL STUDIES The cloud computing technology provides enhanced opportunity in synchronising the financial management by breaking down the data across risk, financial aspects, regulatory requirements, preparing financial reports etc. The company possess massive amounts of data sets and hence they need to be stored, accessed, retrieved and analyse for making critical decision making. Hence, cloud computing provides better storage and access of critical data and information in effective manner for supporting the organisational financial management system. This paper is intended to provide detailed overview on the creation and implementation of cloud computing technologies so as to enhance financial management system in the organisational perspectives.
... Many large companies in developed and developing countries direct their investments in creating a cloud-based computing environment to better allocate resources, analyse financial needs and requirements, and establish an effective financial management system to achieve stakeholders' financial goals [13]. Companies are focused on sustainably improving shareholders' wealth. ...
Article
Full-text available
The rapid development of advanced technologies like Internet of Things (IoT), Cloud computing, big data analysis has enabled in transforming the financial management system effectively. Many large enterprises in developed and developing countries are channelising their investment in setting up cloud computing environment so as to offer better resource sharing, analyse the financial needs and requirements, establish effective financial management system so as to achieve the financial goals of the stakeholders. Business enterprises focuses in enhancing the wealth of the shareholders in a sustainable manner, moreover the organisation tend to perform millions of financial transactions like receipt of cash, making payments to suppliers, vendors, partners, franchises etc. hence, it is highly significant to implement sophisticate financial management system so that the transactions can be monitored and processed effectively. Also, the management needs real time information for making quick analysis and take informed decisions. Cloud computing service providers tend to offer array of innovative services which can be accessed by the business on their platforms, this helps the top management to implement better operating and financial management models for enhancing revenues, create better allocation of budget, manage the investment, automating the payments and effectively use the cash resources for enhancing better return on investment and support in increasing wealth to the shareholders. KOREA REVIEW OF INTERNATIONAL STUDIES The cloud computing technology provides enhanced opportunity in synchronising the financial management by breaking down the data across risk, financial aspects, regulatory requirements, preparing financial reports etc. The company possess massive amounts of data sets and hence they need to be stored, accessed, retrieved and analyse for making critical decision making. Hence, cloud computing provides better storage and access of critical data and information in effective manner for supporting the organisational financial management system. This paper is intended to provide detailed overview on the creation and implementation of cloud computing technologies so as to enhance financial management system in the organisational perspectives.
... Using big data allows digital banks to better understand different demographics, consumer behavior, and financial activity behavior. Additionally, digital banks can track and analyze all these data in bulk as opposed to traditional banks (Kshetri, 2016). As such, digital banks can use this data to personalize their platforms better and optimize their services to fulfill their client's needs better and wants, thus achieving more customer satisfaction (Parise et al., 2016). ...
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The emergence of technology, combined with the adoption and integration of new practices, has greatly affected multiple business fields, including the Philippine banking industry. This leads to the entrance of fully digital banking platforms, a potential alternative to brick-and-mortar banks. Would Metro Manila banking customers utilize fully digital banks, or would they prefer the established traditional banking institutions as their personal choice for financial services and transactions? By surveying 385 respondents, the researchers obtained and analyzed information about the preferences and behavior of banking customers to learn more about the degree to which customer characteristics affected their preferences for certain banking products. This study proved that Metro Manila banking customers have a strong inclination towards physical or traditional banks, given that 60.5% of the total respondents are traditional banking users compared to 4.4% for fully digital banks and 35.1% for both traditional and fully digital banks. Decision variables such as convenience, efficiency, customization/personalization, security, and privacy also played a significant role in evaluating and assessing customer motivation in determining a preference. The results yielded a more localized and concentrated approach that exhibits the factors regarding traditional and fully digital banks that would potentially help the Philippine banking industry to adjust and adapt to emerging technology and consumer needs.
... With the rapid rise of modern information technology represented by big data, cloud computing, artificial intelligence, and blockchain, it provides great convenience for financial services to reduce costs, improve efficiency and expand scope (Kshetri, 2016;Gomber et al., 2018), and financial development is gradually moving toward the digital age (Huang and Huang, 2018). We predict that digital finance will affect corporate green innovation in the following two ways. ...
Article
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Recently, the rapid development of digital finance in China has exerted a subtle influence on many aspects of social and economic development. However, the research on the impact of digital finance on corporate green innovation is rather lacking. In order to fill this gap, this paper uses the “Peking University Digital Finance Index” to evaluate the micro impact of financial innovation development on environmental governance from the firm level. The results show that digital finance can significantly improve the quantity and quality of corporate green innovation, and this effect still exists after considering endogeneity and a series of robustness tests. The promotion effect of digital finance on the quantity and quality of corporate green innovation is more obvious in state-owned, eastern, and mature enterprises. In addition, we find the mechanism behind the positive relationship between digital finance and corporate green innovation: digital finance makes firms more transparent and funds flow more convenient. Overall, this paper provides a micro explanation of environmental governance for the accelerated popularization of digital finance in emerging markets, which is urgently needed for most emerging economies seeking high-quality development.
... The thing that is a challenge for Islamic banking from the five factors that must be analyzed is the character factor. The problem of limited financial information to assess the character of customers in the credit analysis process has been resolved through the use of currently developed technology (Wei, Yildirim, Van den Bulte, & Dellarocas, 2016;Kshetri, 2016). The development of technology and increasing internet penetration in Indonesia can solve these challenges. ...
Conference Paper
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There is a standard method to use credit scoring to estimate borrowers' creditworthiness in a bank's consumer loan. Recently, banks consider adding information regarding borrowers' activities on social media to calculate credit scores. This study aims to examine the relationship between social media accounts' self-disclosure with borrowers' creditworthiness in Islamic Bank. We measure self-disclosure of social media accounts variables as to whether the borrower fills their loan application form with their phone number connected to their social media account, specifically Facebook and WhatsApp. The analysis was carried out on 490 existing customer data at Islamic Bank in Indonesia. The creditworthiness probability model is estimated using a binary logistic regression model. We found that self-disclosure of phone numbers connected to borrowers' social media Facebook has a significant and positive effect on creditworthiness, but this is not the case for the phone number connected to WhatsApp. We recommend that bank management consider this finding to improve their credit scoring calculation
... Other impactful and influential areas of research, as indicated by the list of top-cited publications, include access to financial services (Kshetri, 2016), asset pricing (Muniesa, 2007), corporate failure prediction (Beynon and Peel, 2001), credit scoring (Liu and Schumann, 2005), derivative pricing (Ninomiya and Victoir, 2008), FinTech (Gabor and Brooks, 2017), forecasting foreign exchange rates (Nag and Mitra, 2002), investor behavior analysis (Lee and Radhakrishna, 2000), management accounting information (Bhimani and Willcocks, 2014), scheduling (Elazouni and Metwally, 2005), trade classification (Odders-White, 2000), and volatility forecasting (Arroyo et al., 2011). Das and Chen (2007) Yahoo! for Amazon: Sentiment extraction from small talk on the web 615 Beynon and Peel (2001) Variable precision rough set theory and data discretization: An application to corporate failure prediction 213 Ravisankar et al. (2011) Detection of financial statement fraud and feature selection using data mining techniques 198 Lee and Radhakrishna (2000) Inferring investor behavior: Evidence from TORQ data 195 Humpherys et al. (2011) Identification of fraudulent financial statements using linguistic credibility analysis 142 West and Bhattacharya (2016) Intelligent financial fraud detection: A comprehensive review 117 Odders-White (2000) On the occurrence and consequences of inaccurate trade classification 115 Muniesa (2007) Market technologies and the pragmatics of prices 109 Gabor and Brooks (2017) The digital revolution in financial inclusion: International development in the Fintech era 103 Kumar and Ravi (2016) A survey of the applications of text mining in financial domain 97 Bhimani and Willcocks (2014) Digitization, big data and the transformation of accounting information 93 Nag and Mitra (2002) Forecasting daily foreign exchange rates using genetically optimized neural networks 91 Glancy and Yadav (2011) A computational model for financial reporting fraud detection 82 Liang et al. (2015) The effect of feature selection on financial distress prediction 79 Kim and Kim (2014) Investor sentiment from internet message postings and the predictability of stock returns 78 Elazouni and Metwally (2005) Finance-based scheduling: Tool to maximize project profit using improved genetic algorithms 76 Zhou and Kapoor (2011) Detecting evolutionary financial statement fraud 76 Ninomiya and Victoir (2008) Weak approximation of stochastic differential equations and application to derivative pricing 70 Oliveira et al. (2016) Stock market sentiment lexicon acquisition using microblogging data and statistical measures 69 Liu and Schumann (2005) Data mining feature selection for credit scoring models 63 Kshetri (2016) Big data's role in expanding access to financial services in China 60 Hajek and Henriques (2017a) Mining corporate annual reports for intelligent detection of financial statement fraud -A comparative study of machine learning methods ...
Article
Artificial intelligence (AI) and machine learning (ML) are two related technologies that are emergent in financial scholarship. However, no review, to date, has offered a holistic retrospection of this research. To address this gap, we provide an overview of AI and ML research in finance. Using both co-citation and bibliometric-coupling analyses, we infer the knowledge and thematic structure of AI and ML research in finance for 1986-April 2021. By uncovering nine (co-citation) and eight (bibliometric coupling) specific clusters of finance that apply AI and ML, we further identify three overarching groups of finance scholarship that are roughly equivalent for both forms of analysis: 1) portfolio construction, valuation, and investor behavior; 2) financial fraud and distress; and 3) sentiment inference, forecasting, and planning. Additionally, using co-occurrence and confluence analyses, we highlight trends and research directions regarding AI and ML in finance research. Our survey also indicates that, while studies applying AI and ML to finance have mainly appeared in operations research journals, rather than finance journals, an exception is Quantitative Finance, which has served as a unique an outlet for AI and ML research among finance-classified journals. Our results provide guidance for future researchers, as well as focus for assessing the growing emphasis on AI and ML in finance research.
... Beberapa negara yang telah mengaplikasikan penggunaan big data analytics seperti India, Rusia, dan China lebih berfokus pada industri jasa keuangan, namun sekarang telah meluas hingga industri non keuangan (Anna dan Nikolay, 2015;Kshetri, 2016;Srivastava dan Gopalkrishnan, 2015). Dalam proses pengaplikasian teknologi big data analytics pada suatu organisasi, terdapat 4 unsur utama yang menjadi tantangan yaitu data, tekonologi, proses, serta sumber daya manusia. ...
... There have been some attempts to study the impact of big data or statistical measures on socio-economic issues in the informal economy and social policy literature. In his study of big data and credit access of low-income individuals in China, Kshetri (2016) finds that big data helps financial institutions decide whether to lend the money to low-income individuals by providing richer information about their ability to repay the loan. But given the scarcity of literature in big data and the informal economy, it is difficult to draw a connection as to whether a technological change in data collection and documentation can bring positive effects to the lives of the informal actors, and likewise, the way society perceives the informal economy. ...
Article
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While many marginalised groups, including women and poor and low-income families, are working in the informal economy (Adom, 2015), these actors remain absent in major public policies. While policymakers have come to an understanding about the role of the informal economy and the imperative behind extending social protection to informal workers (Surrender and Walker, 2013), recent literature provided hints of economic growth as the unspoken mission of being on the side of the informal actors, (Joshi, Prichard, and Heady, 2014; Schneider and Klinglmair, 2004; Schneider, Buehn, and Montenegro, 2010). Example of such mission includes the rising trend of documenting the informal economy – which is less likely to bring many benefits to the informal actors, compare to firms in the formal economy that get a direct splash of the economic growth. Therefore, a previous hypothesis that data is all that is required to bring equality to the informal economy is inaccurate. This article aims to unwrap the role of data on the informal economy. More specifically, by looking at recent data innovation, the article criticised the growth narrative behind documenting the informal economy, which hinders improvement in informal actors' livelihood conditions. This article relies on the capability approach first developed by Amartya Sen (see: Sen, 1994, 2001, 2004) and later Martha Nussbaum (see: Nussbaum, 2003, 2011) to evaluate the current usage of statistics to measure the magnitude and nature of the informal economy, in addition to elaborating the ‘ideal’ of how to define objectives of documenting the informal economy through data innovation.
... Our theory has been derived from having studied multiple cases [1,[13][14][15][16][17]. We selected only cases for which sufficient information could be obtained from secondary sources. ...
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While prior research has looked at big data’s role in strengthening the environmental justice movement, scholars rarely examine the contexts, mechanisms and processes associated with the use of big data in monitoring and deterring environmental offenders, especially in the Global South. As such, this research aims to substitute for this academic gap through the use of multiple case studies of environmental offenders’ engagement in illegal deforestation, as well as legal deforestation followed by fire. Specifically, we have chosen four cases from three economies in the Global South: Indonesia, Peru and Brazil. We demonstrate how the data utilized by environmental activists in these four cases qualify as true forms of big data, as they have searched and aggregated data from various sources and employed them to achieve their goals. The article shows how big data from various sources, mainly from satellite imagery, can help discern the true extent of environmental destruction caused by various offenders and present convincing evidence. The article also discusses how a rich satellite imagery archive is suitable for analyzing chronological events in order to establish a cause-effect chain. In all of the cases studied, such evidentiary provisions have been used by environmental activists to oblige policy makers to take necessary actions to counter environmental offenses.
... Determining how to use these massive data to improve the work efficiency and effect of banks and promote the improvement of the banking business is the main purpose of the application of financial big data and fintech in the financial field. There are many studies on financial big data or big data in finance and fintech, separately [16][17][18], but few studies focused on the combination of financial big data and fintech. The main goal of this study was to demonstrate how to integrate financial big data and fintech to promote the development of the financial industry through an asset allocation example. ...
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An asset allocation optimization model for key clients and financial products is developed and deployed on a business platform by compiling a program to a module using MATLAB to show how to integrate financial big data and fintech in a real application for a bank. Firstly, we establish a single objective linear programming model with the percent of assets in products as the decision variables, the minimum-weighted duration as the objective, and the business requirements as constraints. Then, we select non-integer linear programming as the model solver by testing two algorithm solvers with six real test cases separately, according to the solving time. Finally, we directly compile the model and the algorithm program into a module to complete the deployment into a business platform to quickly complete the transformation of data and model the actual productivity of the bank.
... Fin-tech, the portmanteau of nance and technology, often refers to the industries that use digital technologies to provide nancial products and services (Chishti & Barberis, 2016). It is considered an innovative business sector not only because it is based on high technologies but also for its disruption to the existing structures of the traditional nancial industries (Kshetri, 2016;Wang, 2018a). In the development of digital nancial technologies, the design, di usion, and institutionalization of technologies at the structural/market level are intertwined with the routinization of the everyday use of n-techs at the company or consumer level. ...
Chapter
Digital 􀁼nancial technologies or so-called 􀁼n-techs have reshaped the 􀁼nancial practices worldwide. Around the year 2014 when 􀁼n-tech just came into shape and was primarily run by IT corporations or start-ups, it was normally considered “alternative finance”—the non-mainstream, or the supplement to the traditional 􀁼nance managed by banks. While banks run as the dominant entities in traditional 􀁼nance and get 􀁼nancial licenses from the government, the regulators often consider fin-tech companies as informational agencies rather than 􀁼nancial intermediaries. However, in less than 􀁼ve years, almost all the major banks have set up a department or business sector to develop their 􀁼n-tech businesses. In the meantime, some of the leading 􀁼n-tech companies, (e.g., Ant Financial) are considered the most valuable companies in the world. How have digital technologies played a transforming role in the financial domain? In addition to enhancing e􀁹ciency and innovation, what are the social and cultural consequences that are often ignored amid academic and public discussions? This chapter sets its foundation in these two questions and critically examines the performative nature of 􀁼ntechs. Through a case study of Yu’ebao, a popular consumer investment app rolled out by Ant Financial in 2013 and has accumulated the largest money market fund in the world, this chapter analyzes how the political economic and cultural conditions have rendered the rise of financial technologies in China.
... Recently, big data has attracted extensive attention from academic circles [33,34]. The emergence of big data has made a significant impact on the development of high-tech platform enterprises [35] and has promoted the transformation of enterprises from being traditionalfactor driven to being innovation driven [36]. ...
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This research aims to create a hierarchical framework for the development of a platform business model based on big data. However, this hierarchical framework must consider unnecessary attributes and the interrelationships between the aspects and the criteria. Hence, fuzzy set theory is used for screening out the unnecessary attributes, a decision-making and trial evaluation laboratory (DEMATEL) is proposed to manage the complex interrelationships among the aspects and attributes, and interpretive structural modeling (ISM) is used to divide the hierarchy and finally construct a hierarchical framework. The results reveal that (1) value proposition and community building in value production are fundamental links; (2) information technology and information management in value production are technical supports; (3) customer development in value marketing is the power source; and (4) value acquisition is the last link, which is established on the basis of and influenced by value marketing and value network. This hierarchical framework aims to guide the platform toward the application of big data. This study also proposes engagement of stakeholders for promoting value creation and establishing a sound business model from multiple levels and links.
... For example, complexity in decision making starts as information available to financial institutions reduce, reducing the ability to undertake any risk in lending to farmers. A study conducted in China indicates that the lack of creditworthiness of low-income families are merely because banks and financial institutions have information opacity and face high transaction costs to assess the creditworthiness of low-income families (Kshetri 2016). The ability to screen borrowers with a high degree of accuracy face bottlenecks due to information asymmetry and transaction costs in developing countries, which ultimately plays to the advantage of informal lenders who can then use the leverage to impose their own terms (e.g. ...
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... Operations in financial institutions are tailored to offer credit services to formally registered businesses, which meet .criteria such as proper maintenance of book of accounts and verifiable asset base (Kshetri, 2016) Some financial institutions such as banks offer debit micro and small enterprise, but overall the country lacks investment in these micro-businesses. Due to the country's debt, the micro and small enterprises did not receive any investment from the local or international financial institutions. ...
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... 41 Wildau 2017;Kshetri 2016. 42 Wang, Jing 2018b Interview with the CEO of Huarui Bank, Shanghai, July 2017. ...
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Chapter
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Chapter
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Chapter
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The authors argue that high borrowing costs discourage many rural poor in low income countries from using formal loans. Borrowing costs are defined as nominal interest payments, plus borrower loan transaction costs, plus changes in the purchasing power of money. Farm level information from Bangladesh, Brazil and Colombia is presented to show that small borrowers incur substantially higher borrowing costs on formal loans than do large borrowers. It is suggested that higher nominal interest rates may induce lenders to reduce overall borrowing costs for the small and new borrower.
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This article challenges the recent uncritical enthusiasm for the potential of micro-finance institutions to reduce poverty. It is argued that, although understanding about how to design anti-poverty financial intermediation has improved, the current campaign to increase resource allocation in this sector may undermine the very sustainability that is being sought. Further, studies of the impact of micro-enterprise credit suggest that it is not necessarily beneficial to very poor people. Interventions in the provision of financial services should not be made without locally specific analysis of the functions of existing savings and credit facilities. An emphasis on scale acts as a disincentive to such analysis, and increases the risk of the reemergence of a 'blueprint' approach to anti-poverty action.
Article
This chapter discusses the operationalization of transaction cost economics. Vertical integration, an understanding of which serves as a paradigm for helping to unpack the puzzles of complex economic organization more generally, is described in the chapter. Some empirical tests of the transaction cost hypotheses are summarized in the chapter. Transaction cost economics adopts a contractual approach to the study of economic organization. As compared with other approaches to the study of economic organization, transaction cost economics (1) is more microanalytic, (2) is more self-conscious about its behavioral assumptions, (3) introduces and develops the economic importance of asset specificity, (4) relies more on comparative institutional analysis, (5) regards the business firm as a governance structure rather than a production function, (6) places greater weight on the ex post institutions of contract, with special emphasis on private ordering, and (7) works out of a combined law, economics, and organization perspective. Friction, the economic counterpart for which is transaction costs, is pervasive in both physical and economic systems.
Article
This paper studies the impact of foreign bank entry on domestic firms’ access to bank credit using a within-country staggered geographic variation in the policy of foreign bank lending in China. The paper finds that after foreign bank entry profitable firms use more long-term bank loans; whereas firms with higher value of potential collateral do not. It also finds that non-state-owned firms become able to substitute some trade credit with long-term bank loans. The findings suggest that less opaque firms and non-state-owned firms benefit more from foreign bank entry and that collateral may only play a limited role in mitigating the problem of information asymmetry when creditors’ rights are not well protected in a host country.
Article
Theory predicts that information sharing among lenders attenuates adverse selection and moral hazard, and can therefore increase lending and reduce default rates. Using a new, purpose-built data set on private credit bureaus and public credit registers, we find that bank lending is higher and credit risk is lower in countries where lenders share information, regardless of the private or public nature of the information sharing mechanism. We also find that public intervention is more likely where private arrangements have not arisen spontaneously and creditor rights are poorly protected.
Article
Historical research offers perspectives on phenomena that are unavailable by any other methodological means. They reflect the cultural circumstances and ideological assumptions that underlie phenomena and the role played by key decision makers together with long-term economic, social, and political forces in creating them. Each of these benefits is accompanied by limitations such as, in most cases, a lack of mathematical tractability. The careful application of historical methods can overcome some of these limitations. A seven-step methodology is proposed: begin with focusing questions, specify the domain, gather evidence, critique the evidence, determine patterns, tell the story, and write the transcript.
Article
Existing evidence on the effect of foreign bank penetration on lending to small and medium-size enterprises is ambiguous. Case studies of developing countries show that foreign banks lend less to such firms than domestic banks do. But cross-country studies find that foreign bank entry fosters competition and reduces interest rates, benefits that should extend to all firms. The authors use data from a large cross-country survey of enterprises to investigate this issue. Their results suggest that foreign bank penetration improves financing conditions (both the quantities of financing and the terms) for enterprises of all sizes, although it seems to benefit larger firms more.
Article
This paper describes the recent trends in foreign bank ownership in developing countries, summarizes the existing evidence on the causes and implications of foreign bank presence, and reexamines the link between banking crises and foreign bank participation. Using data on the share of banking sector assets held by foreign banks in over 100 developing countries during 1995-2002, the results show that countries that experienced a banking crisis tended to have higher levels of foreign bank participation than those that did not. Furthermore, panel regressions indicate that foreign participation increased as a result of crises rather than prior to them. However, post-crisis increases in foreign participation did not coincide with increased credit to the private sector, perhaps because in many cases foreign banks acquired distressed banks.
Article
Theory predicts that information sharing among lenders attenuates adverse selection and moral hazard, and can therefore increase lending and reduce default rates. We construct a new international data set on credit bureaus and public credit registers. The theoretical predictions are broadly consistent with our data. We also study why central banks often supplement private arrangements by creating public credit registers and distribution of information about borrowers` credit histories. Public intervention is more likely where creditor rights are poorly protected and private arrangements have not arisen spontaneously.
Article
Using a unique database for 74 countries and for firms of small, medium, and large size we assess the effect of banking market structure on the access of firms to bank finance. We find that bank concentration increases obstacles to obtaining finance, but only in countries with low levels of economic and institutional development. A larger share of foreign-owned banks and an efficient credit registry dampen the effect of concentration on financing obstacles, while the effect is exacerbated by more restrictions on banks' activities, more government interference in the banking sector, and a larger share of government-owned banks.
Article
Many evaluations would be more useful to decision makers if their results were both explanatory and generalizable. In view of the limitations of traditional methods in meeting both these goals at the same time, the authors describe a research design explicitly intended for generalizing about the range of applicability of “explanatory patterns” (within a designated “target” population of cases). The paper presents an overview of the main features of a “multiple case study design,” shorthand for a multiple site, structured case study design. It then discusses the nature of explanatory patterns, how case study investigators pursue and recognize valid patterns, and how an analyst can apply the same logic to cross-site analysis in order to make valid inferences about the limiting conditions under which particular explanatory patterns apply to particular populations.
Article
This paper provides a survey on studies that analyze the macroeconomic effects of intellectual property rights (IPR). The first part of this paper introduces different patent policy instruments and reviews their effects on R&D and economic growth. This part also discusses the distortionary effects and distributional consequences of IPR protection as well as empirical evidence on the effects of patent rights. Then, the second part considers the international aspects of IPR protection. In summary, this paper draws the following conclusions from the literature. Firstly, different patent policy instruments have different effects on R&D and growth. Secondly, there is empirical evidence supporting a positive relationship between IPR protection and innovation, but the evidence is stronger for developed countries than for developing countries. Thirdly, the optimal level of IPR protection should tradeoff the social benefits of enhanced innovation against the social costs of multiple distortions and income inequality. Finally, in an open economy, achieving the globally optimal level of protection requires an international coordination (rather than the harmonization) of IPR protection.
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