nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2020‒11‒30
fourteen papers chosen by

  1. Costos del comercio en el procesamiento de los pagos en Colombia By Carlos A. Arango-Arango; Yanneth Rocío Betancourt-García
  2. Identifying Consumer Preferences from User- and Crowd-Generated Digital Footprints on by Leveraging Machine Learning and Natural Language Processing By Jikhan Jeong
  3. An early stablecoin? The Bank of Amsterdam and the governance of money By Jon Frost; Hyun Song Shin; Peter Wierts
  4. Financial Inclusion, Information and Communication Technology Diffusion and Economic Growth: A Panel Data Analysis By Amrita Chatterjee; Nitigya Anand
  5. Fintech Borrowers: Lax-Screening or Cream-Skimming? By Marco Di Maggio; Vincent Yao
  6. Biased sampling of early users and the direction of startup innovation By Cao, Ruiqing; Koning, Rembrand; Nanda, Ramana
  7. Data-driven mergers and personalization By Zhijun Chen; Chongwoo Choe; Jiajia Cong; Noriaki Matsushima
  8. Disinformation and digital dominance: Regulation through the lens of the election lifecycle By Marsden, Christopher T; Brown, Ian; Veale, Michael
  9. Fintech, Bigtech, and Financial Inclusion By Loretta J. Mester
  10. Prospects and challenges of quantum finance By Adam Bouland; Wim van Dam; Hamed Joorati; Iordanis Kerenidis; Anupam Prakash
  11. Encouraging digital security innovation: Global Forum on Digital Security for Prosperity By OECD
  12. Central bank digital currency in an open economy By Ferrari, Massimo Minesso; Mehl, Arnaud; Stracca, Livio
  13. Selling Cross-Border in Online Markets: The Impact of the Ban on Geoblocking Strategies By Marc Bourreau; Fabio M. Manenti
  14. Can Fintechs Stabilize the Financial Sector? By Windl, Martin

  1. By: Carlos A. Arango-Arango (Banco de la República de Colombia); Yanneth Rocío Betancourt-García (Banco de la República de Colombia)
    Abstract: En Colombia se han logrado importantes avances en el acceso a productos transaccionales ofrecidos por el sistema financiero, sin embargo, su uso aÚn es bajo, y las empresas y los consumidores continúan utilizando de manera intensiva el efectivo. Una de las razones por las cuales los colombianos prefieren el efectivo para realizar sus pagos cotidianos es la limitada aceptación de pagos electrónicos por parte de los comercios, lo que se explica en parte por la percepción que tienen éstos sobre los altos costos relativos de operar con pagos electrónicos versus operar con efectivo. Con el fin de tener una medición integral de los costos privados de los comercios en la aceptación y uso de diferentes instrumentos de pago, el Banco de la República realizó en 2018 una encuesta a comercios que aceptan tanto efectivo como tarjetas de pago. Este documento presenta los resultados de dicha encuesta. Las estimaciones muestran que el efectivo es significativamente menos costoso que las tarjetas débito y crédito a la hora de recibir pagos en los comercios. Dicha estructura de costos se replica para los pagos que realizan los comercios asociados con sus gastos de funcionamiento, para los cuales se encuentra que los costos de los pagos electrónicos llegan a ser más del doble que los de los pagos en efectivo. Así las cosas, para los comercios, operar con efectivo resulta más económico que operar con instrumentos de pago electrónicos. **** ABSTRACT: Although Colombia has made significant progress in the access to transactional products offered by the financial system, their use by the public is still low, and merchants and consumers continue to use cash intensively. One of the reasons why Colombians prefer cash to make their daily payments is the limited acceptance of electronic payments by merchants. This can be partly explained by the merchants’ perception of the high relative costs of operating with electronic payments versus operating with cash. To have a complete measure of merchants’ private costs of acceptance and use of different payment instruments, the Banco de la República conducted a survey in 2018 of merchants who accept both cash and payment cards. This paper presents the main results of the survey. Estimates show that cash is significantly less expensive than debit and credit cards when merchants receive payments. This cost structure is replicated for payments that merchants make for their operating expenses, for which the costs of making electronic payments more than double those of cash payments. Altogether, for merchants, operating with cash results much cheaper than with electronic payment systems.
    Keywords: Efectivo, instrumentos de pago, procesamiento de pagos, costos del comercio, tarjetas de pago, Cash, payment instruments, processing payments, merchants´ costs, payment cards.
    JEL: C81 C83 D23 E41 E42 E58
    Date: 2020–11
  2. By: Jikhan Jeong
    Abstract: Inexperienced consumers may have high uncertainty about experience goods that require technical knowledge and skills to operate effectively; therefore, experienced consumersâ prior reviews can be useful for inexperienced ones. However, the one-sided review system (e.g., only provides the opportunity for consumers to write a review as a buyer and contains no feedback from the sellerâs side, so the information displayed about individual buyers is limited. This study analyzes consumersâ digital footprints (DFs) to identify and predict unobserved consumer preferences from online product reviews. It makes use of Python coding along with high-performance computing to extract reviewersâ DFs for a specific product group (programmable thermostats) from a dataset of 141 million Amazon reviews. It identifies consumersâ sentiment toward product content dimensions (PCDs) extracted from review text by applying topic modeling and domain expert annotations. However, some questionable reviews (posted by âsuspicious one-time reviewersâ and âalways-the-same rating reviewersâ) are excluded. This paper obtains three main results: First, I find that the factors that affect consumer ratings are: (a) userâ DFs (e.g., length of the product review, average rating across all categories, volume of prior reviews overall and in sub-categories), (b) reviewersâ attitudes toward eight product content dimensions (smart connectivity, easiness, energy saving, functionality, support, price value, privacy, and the Amazon effect), and (c) other prior reviewers DFs (e.g., length of the review summary.) All the heteroskedastic ordered probit models with DF and sentiment variables show a better model fit than the base model. This paper is the first to identify the effect of service quality of the online platform ( on ratings. Second, extreme gradient boosting (XGBoost) is found to obtain the highest F1 score for predicting the ratings of potential consumers before they make a purchase or write a review. All the models containing DF and sentiment variables show a higher prediction performance than the base model. Classifications with a lower range of labels (three-class or binary classifications) show better prediction performance than the five-star rating classification. However, the performance for the minority class is low. Third, a convolutional neural network (CNN) on top of Bidirectional Encoder Representations from Transformers (BERT) embedding shows the highest F1 score for classifying consumersâ sentiment toward a specific PCD. Overall, this approach developed in this paper is applicable, scalable, and interpretable for distinguishing important drivers of consumer reviews for different goods in a specific industry and can be used by industry to identify and predict unobserved consumer preferences and sentiment associated with product content dimensions.
    JEL: D80 M21 M31 C45
    Date: 2020–11–10
  3. By: Jon Frost; Hyun Song Shin; Peter Wierts
    Abstract: This paper draws lessons on the central bank underpinnings of money from the rise and fall of the Bank of Amsterdam (1609-1820). The Bank started out as a "stablecoin": it issued deposits backed by silver and gold coins, and settled payments by transfers across deposits. Over time, it performed functions of a modern central bank and its deposits took on attributes of fiat money. The economic shocks of the 1780s, large-scale lending and lack of fiscal support led to its failure. Using monthly balance sheet data, we show how confidence in Bank money gave way to a run equilibrium, where the fall of the premium on deposits over coins ("agio") into negative territory was swift and precipitous. This holds lessons for the governance of digital money.
    Keywords: stablecoins; crypto-assets; central banks; money
    JEL: E42 E58 N13
    Date: 2020–11
  4. By: Amrita Chatterjee (Assistant Professor, Madras School of Economics); Nitigya Anand (Associate Solution Advisor, Deloitte & Touche Assurance and Enterprise Risk Services India Pvt. Ltd.)
    Abstract: There have been enough evidences to accept that Financial Inclusion (FI) and Information and Communication Technology (ICT) play positive role in economic growth, even though there are some exceptions. Moreover, we cannot deny the fact that ICT like mobile phone and internet penetration can strengthen the inclusiveness of formal banking sector. The present study has first examined whether ICT development can be an important determinant of Financial Inclusion by using a fixed effect panel data model. The results show that ICT is indeed an important determinant of FI. The same panel data of 41 countries was then used to test whether the growth process of the countries are influenced by Financial Inclusion and ICT diffusion in a dynamic Panel Data Model. Further the paper has investigated the role of FI powered by a better ICT penetration in fostering the growth of the nations using system GMM method by incorporating interactions between FI and ICT indicators. The results suggest that both FI and ICT individually and together through their close interaction can improve current year’s growth. However, we need education, awareness and technical assistance to get sustained growth.
    Keywords: Financial Inclusion, Growth, Information and Communication Technology, Dynamic Panel data model, System GMM estimator
    JEL: L86 L96 C23 O0 G2
  5. By: Marco Di Maggio; Vincent Yao
    Abstract: We study the personal credit market using unique individual-level data covering fintech and traditional lenders. We show that fintech lenders acquire market share by first lending to higher-risk borrowers and then to safer borrowers, and mainly rely on hard information to make credit decisions. Fintech borrowers are significantly more likely to default than neighbor individuals with the same characteristics borrowing from traditional financial institutions. Furthermore, they tend to experience only a short- lived reduction in the cost of credit, because their indebtedness increases more than non-fintech borrowers a few months after loan origination. However, fintech lenders' pricing strategies are likely to take this into account.
    JEL: G21 G23
    Date: 2020–10
  6. By: Cao, Ruiqing; Koning, Rembrand (Harvard Business School); Nanda, Ramana
    Abstract: Using data from a prominent online platform for launching new digital products, we document that the composition of the platform's `beta testers' on the day a new product is launched has a systematic and persistent impact on success. Specifically, we use word embedding methods to classify products launched on this platform as more or less focused on the needs of female customers, and show that female-focused products launched on a typical day—when nine-in-ten users on the platform are men—experience 40% less growth and are 5 percentage points less likely to have an any users a year after launch. Using exogenous variation driven by the platform's daily newsletter, we find that that the product gender gap shrinks on days when women are more likely to engage with the platform. Conversely, entrepreneurs who happen to launch a female-focused product on an especially male-dominated day reduce their product development efforts by roughly 30% and are 4 percentage points less likely to raise venture funding. Overall, our findings suggest that sample bias can systematically corrupt signals of a startup's market potential, bias entrepreneurial strategy, and so lead to a dearth of innovations aimed at consumers who are underrepresented among early-users.
    Date: 2020–11–06
  7. By: Zhijun Chen; Chongwoo Choe; Jiajia Cong; Noriaki Matsushima
    Abstract: Recent years have seen growing cases of data-driven tech mergers such as Google/Fitbit, in which a dominant digital platform acquires a relatively small firm possessing a large volume of consumer data. The digital platform can consolidate the consumer data with its existing data set from other services and use it for personalization in related markets. We develop a theoretical model to examine the impact of such mergers across the two markets that are related through a consumption synergy. The merger links the markets for data collection and data application, through which the digital platform can leverage its market power and hurt competitors in both markets. Personalization can lead to exploitation of some consumers in the market for data application. But insofar as competitors remain active, the merger increases total consumer surplus in both markets by intensifying competition. When the consumption synergy is large enough, the merger can result in monopolization of both markets, leading to further consumer harm when stand-alone competitors exit in the long run. Thus, there is a trade-off where potential dynamic costs can outweigh static benefits. We also discuss policy implications by considering various merger remedies.
    Date: 2020–11
  8. By: Marsden, Christopher T; Brown, Ian; Veale, Michael
    Abstract: Forthcoming in Martin Moore & Damian Tambini (eds.) Dealing with Digital Dominance (OUP 2021) This chapter elaborates on challenges and emerging best practices for state regulation of electoral disinformation throughout the electoral cycle. It is based on research for three studies during 2018-20: into election cybersecurity for the Commonwealth (Brown et al. 2020); on the use of Artificial Intelligence (AI) to regulate disinformation for the European Parliament (Marsden & Meyer 2019a; Meyer et al. 2020); and for UNESCO, the United Nations body responsible for education (Kalina et al. 2020). The research covers more than half the world’s nations, and substantially more than half that population, and in 2019 the two largest democratic elections in history: India’s general election and the European Parliamentary elections.
    Date: 2020–11–13
  9. By: Loretta J. Mester
    Abstract: Since the beginning of this conference series, the discussions have consistently been very topical, and the agenda for the next two days does not disappoint on that score. The conference will cover many of the hot issues confronting practitioners, academics, and policymakers as financial system innovation proceeds at a rapid pace. Today I will discuss the implications of digitalization for financial inclusion and some steps that need to be taken to ensure that digitalization helps to foster inclusion rather than promote exclusion. The views I will present today are my own and not necessarily those of the Federal Reserve System or my colleagues on the Federal Open Market Committee.
    Date: 2020–11–09
  10. By: Adam Bouland; Wim van Dam; Hamed Joorati; Iordanis Kerenidis; Anupam Prakash
    Abstract: Quantum computers are expected to have substantial impact on the finance industry, as they will be able to solve certain problems considerably faster than the best known classical algorithms. In this article we describe such potential applications of quantum computing to finance, starting with the state-of-the-art and focusing in particular on recent works by the QC Ware team. We consider quantum speedups for Monte Carlo methods, portfolio optimization, and machine learning. For each application we describe the extent of quantum speedup possible and estimate the quantum resources required to achieve a practical speedup. The near-term relevance of these quantum finance algorithms varies widely across applications - some of them are heuristic algorithms designed to be amenable to near-term prototype quantum computers, while others are proven speedups which require larger-scale quantum computers to implement. We also describe powerful ways to bring these speedups closer to experimental feasibility - in particular describing lower depth algorithms for Monte Carlo methods and quantum machine learning, as well as quantum annealing heuristics for portfolio optimization. This article is targeted at financial professionals and no particular background in quantum computation is assumed.
    Date: 2020–11
  11. By: OECD
    Abstract: This document summarises discussions held at the second annual event of the OECD Global Forum on Digital Security for Prosperity. The event, held on 14-15 November 2019 in London, brought together 160 experts and 30 speakers from government, business, civil society, the technical community and academia to discuss how to encourage digital security innovation. Participants explored the roles that different stakeholders can play in stimulating digital security innovation, including how governments can support it for example by implementing tax incentives, acting as an early customer for innovative products, and enacting flexible and outcome-based regulation. A digital security innovation ecosystem is the most important component of a strategic approach, as it brings together different stakeholder groups in a dedicated location. Participants discussed how different ecosystems can learn from one another through international co-operation and considered how governments can encourage digital security by design in innovation more generally.
    Date: 2020–11–20
  12. By: Ferrari, Massimo Minesso; Mehl, Arnaud; Stracca, Livio
    Abstract: We examine the open-economy implications of the introduction of a central bank digital currency (CBDC).We add a CBDC to the menu of monetary assets available in a standard two-country DSGE model with financial frictions and consider a broad set of alternative technical features in CBDC design. We analyse the international transmission of standard monetary policy and technology shocks in the presence and absence of a CDBC and the implications for optimal monetary policy and welfare. The presence of a CBDC amplifies the international spillovers of shocks to a significant extent, thereby increasing international linkages. But the magnitude of these effects depends crucially on CBDC design and can be significantly dampened if the CBDC possesses specific technical features. We also show that domestic issuance of a CBDC increases asymmetries in the international monetary system by reducing monetary policy autonomy in foreign economies. JEL Classification: E50, F30
    Keywords: central bank digital currency, DSGE model, international monetary system, open-economy, optimal monetary policy
    Date: 2020–11
  13. By: Marc Bourreau; Fabio M. Manenti
    Abstract: We develop a model of strategic geoblocking, where two competing multi-channel retailers, located in different countries, can decide to block access to their online store from foreign consumers. We characterize the equilibrium when firms decide unilaterally whether to introduce geoblocking restrictions. We show that geoblocking results in a “puppy dog” strategy (Fudenberg and Tirole, 1984) for firms, which allows them to soften competition, but that it comes at the cost of lower demand. In the short term, a ban on geoblocking leads to lower prices, both offline and online. However, in the longer term, when firms can invest in increasing the demand from online shoppers, the ban may have adverse effects on investment and social welfare. We extend our analysis to account for price discrimination and investigate the role of shipping costs.
    Keywords: cross-border sales, geoblocking, e-commerce, investment
    JEL: L13 L41 L81
    Date: 2020
  14. By: Windl, Martin
    Abstract: The growing popularity of fintechs has led the Financial Stability Board (FSB) to publish considerations about the effects of this emerging industry on stability and efficiency in the financial sector. Against this background, this paper compares the effects of competition and collaboration between banks and fintechs on stability and efficiency. Using a partial equilibrium model and a general equilibrium model with moral hazard between investors and the financial sector based on Martinez-Miera and Repullo (2017), this paper shows that cooperation between banks and fintechs increases stability and efficiency compared to the case of a competitive equilibrium. The findings are robust to changes in bargaining power within the financial sector but depend critically on contestable loan markets.
    Keywords: fintech,bigtech,financial stability,general equilibrium
    JEL: G21 G23 G28
    Date: 2020

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