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on Payment Systems and Financial Technology |
| By: | Dong He; Ross B Leckow; Vikram Haksar; Tommaso Mancini Griffoli; Nigel Jenkinson; Mikari Kashima; Tanai Khiaonarong; Celine Rochon; Hervé Tourpe |
| Abstract: | A new wave of technological innovations, often called “fintech,” is accelerating change in the financial sector. What impact might fintech have on financial services, and how should regulation respond? This paper sets out an economic framework for thinking through the channels by which fintech might provide solutions that respond to consumer needs for trust, security, privacy, and better services, change the competitive landscape, and affect regulation. It combines a broad discussion of trends across financial services with a focus on cross-border payments and especially the impact of distributed ledger technology. Overall, the paper finds that boundaries among different types of service providers are blurring; barriers to entry are changing; and improvements in cross-border payments are likely. It argues that regulatory authorities need to balance carefully efficiency and stability trade-offs in the face of rapid changes, and ensure that trust is maintained in an evolving financial system. It also highlights the importance of international cooperation. |
| Keywords: | Central banks;Financial sector;International cooperation;Fintech, cross border payments, market structure, financial regulation, financial stability, monetary policy, virtual currencies, digital currencies, competition, entry, intermediaries, concentration, market contestability, vertical integration, horizontal integration, product differentiation, network externalities, economies of scale, barriers to entry, sunk costs, fixed costs, information asymmetries, transaction costs, matching, innovation, adoption, cross-border payments, General, Government Policy and Regulation, Government Policy and Regulation |
| Date: | 2017–06–19 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfsdn:17/05&r=pay |
| By: | Simplice Asongu (Yaoundé/Cameroun); Nicholas Biekpe (Cape Town, South Africa) |
| Abstract: | This study investigates government quality determinants of ICT adoption using Generalised Method of Moments on a panel of 49 Sub-Saharan African (SSA) countries for the period 2000-2012. ICT is measured with mobile phone penetration, internet penetration and telephone penetration rates while all governance dimensions from the World Bank Governance Indicators are considered, namely: political governance (consisting of political stability and “voice & accountability”); economic governance (entailing government effectiveness and regulation quality) and institutional governance (encompassing the rule of law and corruption-control). The following findings are established. First, political stability and the rule of law have positive short run and negative long term effects on mobile phone penetration. Second, the rule of law has a positive (negative) short run (long term) effect on internet penetration. Third, government effectiveness and corruption-control have positive short run and long term effects on telephone penetration. Institutional governance appears to be most significant in determining ICT adoption in SSA. |
| Keywords: | ICT; Governance; Africa |
| JEL: | G20 O38 O40 O55 P37 |
| Date: | 2017–05 |
| URL: | http://d.repec.org/n?u=RePEc:agd:wpaper:17/024&r=pay |
| By: | Carin van der Cruijsen |
| Abstract: | For policymakers seeking to protect consumer data or financial stability and financial institutions that wish to keep their customers satisfied it is key to know consumers' attitudes towards payments data usage. This paper provides detailed insight into these attitudes based on unique surveys held among Dutch consumers. Privacy is considered an important payment instrument attribute, especially by low-educated, low-income, and elderly consumers and consumers who have little trust in other people or in their bank. Attitudes towards payments data usage depend on the context. For example, most people support the use of payments data to improve security or services but find sharing payments data with other companies unacceptable. Moreover, the latter practice would result in a significant decline of trust in banks. Depending on the purpose of the data use, attitudes relate to socio-demographic factors, online behaviour, satisfaction with the bank and perceptions of current data usage practices. Lastly, many consumers are unwilling to share their payments data with non-banks to use a payment app or get a financial overview. This holds especially for consumers with low trust in other people and in banks |
| Keywords: | privacy; payments data; consumer attitudes; consumer survey; banks; trust |
| JEL: | D14 D12 |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:563&r=pay |
| By: | Sally Murray |
| Abstract: | This paper argues that new technologies—for communication, such as mobile phones and the internet, but also for manufacturing, agriculture, energy, and transport—have the potential to bridge many of the productivity gaps between sub-Saharan Africa and more advanced developing and developed countries. Technology can help to overcome distances between producers and consumers, knowledge and skills gaps, and energy shortfalls, and can bring down the costs of living to make wages competitive. However, new technologies will not deliver these gains unaided: supportive policies are required to create an environment where these new technologies can deliver on their potential. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:unu:wpaper:wp2017-156&r=pay |
| By: | Dominique Guegan (Centre d'Economie de la Sorbonne and LabEx ReFi); Bertrand Hassani (Group Capgemini and Centre d'Economie de la Sorbonne and LabEx ReFi) |
| Abstract: | The arrival of big data strategies is threatening the lastest trends in financial regulation related to the simplification of models and the enhancement of the comparability of approaches chosen by financial institutions. Indeed, the intrinsic dynamic philosophy of Big Data strategies is almost incompatible with the current legal and regulatory framework as illustrated in this paper. Besides, as presented in our application to credit scoring, the model selection may also evolve dynamically forcing both practitioners and regulators to develop libraries of models, strategies allowing to switch from one to the other as well as supervising approaches allowing financial institutions to innovate in a risk mitigated environment. The purpose of this paper is therefore to analyse the issues related to the Big Data environment and in particular to machine learning models highlighting the issues present in the current framework confronting the data flows, the model selection process and the necessity to generate appropriate outcomes |
| Keywords: | Financial Regulation; Algorithm; Big Data; Risk |
| JEL: | C55 |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:17034&r=pay |
| By: | Joachim Freyberger; Bradley J. Larsen |
| Abstract: | This study provides new identification and estimation results for ascending (traditional English or online) auctions with unobserved auction-level heterogeneity and an unknown number of bidders. When the seller's reserve price and two order statistics of bids are observed, we derive conditions under which the distributions of buyer valuations, unobserved heterogeneity, and number of participants are point identified. We also derive conditions for point identification in cases where reserve prices are binding (in which case bids may be unobserved in some auctions) and present general conditions for partial identification. We propose a nonparametric maximum likelihood approach for estimation and inference. We apply our approach to the online market for used iPhones and analyze the effects of recent regulatory changes banning consumers from circumventing digital rights management technologies used to lock phones to service providers. We find that buyer valuations for unlocked phones dropped after the unlocking ban took effect. |
| JEL: | C1 C57 D44 L0 L96 O3 |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23569&r=pay |
| By: | V. Bhaskar; Robin Linacre; Stephen Machin |
| Abstract: | The economic functioning of online drug markets using data scraped from online platforms is studied. Analysis of over 1.5 million online drugs sales shows online drugs markets tend to function without the significant moral hazard problems that, a priori, one might think would plague them. Only a small proportion of online drugs deals receive bad ratings from buyers, and online markets suffer less from problems of adulteration and low quality that are a common feature of street sales of illegal drugs. Furthermore, as with legal online markets, the market penalizes bad ratings, which subsequently lead to significant sales reductions and to market exit. The impact of the well-known seizure by law enforcement of the original Silk Road and the shutdown of Silk Road 2.0 are also studied, together with the exit scam of the market leader at the time, Evolution. There is no evidence that these exits deterred buyers or sellers from online drugs trading, as new platforms rapidly replaced those taken down, with the online market for drugs continuing to grow. |
| Keywords: | dark web, drugs |
| JEL: | K42 |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1490&r=pay |
| By: | Xiaojiao Yu |
| Abstract: | Online leading has disrupted the traditional consumer banking sector with more effective loan processing. Risk prediction and monitoring is critical for the success of the business model. Traditional credit score models fall short in applying big data technology in building risk model. In this manuscript, data with various format and size were collected from public website, third-parties and assembled with client's loan application information data. Ensemble machine learning models, random forest model and XGBoost model, were built and trained with the historical transaction data and subsequently tested with separate data. XGBoost model shows higher K-S value, suggesting better classification capability in this task. Top 10 important features from the two models suggest external data such as zhimaScore, multi-platform stacking loans information, and social network information are important factors in predicting loan default probability. |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1707.04831&r=pay |
| By: | Ngotran, Duong |
| Abstract: | We build a dynamic monetary model with two types of electronic money: reserves for transactions between bankers and zero-maturity deposits for transactions in the non-bank private sector. Using this model, we discuss about unconventional monetary policy during the Great Recession. Committing to keep the federal funds rate at the zero lower bound for a long time is very effective in the short run, but it creates deflation and lowers output in the long run. At the time of raising interest on reserves, if the central bank also commits to target the growth of money supply in responding to inflation, both output and inflation paths will be smooth. In short, “raise rate and raise money supply” is a good way to get out of the zero lower bound. |
| Keywords: | reserves; interest on reserves; zero lower bound; quantitative easing; money supply |
| JEL: | E4 E40 |
| Date: | 2017–07–10 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:80207&r=pay |
| By: | Nadim Ahmad; Jennifer Ribarsky; Marshall Reinsdorf |
| Abstract: | The digital economy has created some new measurement challenges for macroeconomic statistics and may have exacerbated some older ones, raising some concerns about the scope and estimation of GDP. Against a backdrop of slowing rates of measured productivity growth, this has raised questions about the conceptual basis of GDP and output, and whether current compilation methods are adequate to capture them (known as the mismeasurement hypothesis). In response to these concerns the international statistics community has reinforced efforts to investigate these concerns, chiefly under the vehicle of OECD-IMF collaboration and a newly formed Advisory Expert Group working under the auspices of the OECD’s Committee for Statistics and Statistical Policy. This paper is intended to provide momentum to these on-going efforts and to address immediate concerns about the potential scale of GDP mismeasurement in key areas where mismeasurement is often suspected. Notwithstanding the need for further work in some areas, notably with regards to cross-border transactions as well as potential mismeasurement in other macro-economic statistics, such as the consumer prices index, this paper concludes that even if mismeasurement is occurring, its scale is not sufficient to explain the widespread slowdown in measured GDP growth or multi-factor productivity growth. Nevertheless it’s important to note that this is a backward looking exercise. Even though the distortionary impact of any potential mismeasurement is currently thought to be small the growing size of digitised transactions could point to larger impacts in the future. |
| Keywords: | digitalisation, GDP, mismeasurement, prices, Productivity |
| JEL: | E1 E22 E24 E30 |
| Date: | 2017–07–21 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stdaaa:2017/9-en&r=pay |
| By: | Bailey, Michael; Cao, Ruiqing; Kuchler, Theresa; Ströbel, Johannes; Wong, Arlene |
| Abstract: | We introduce a new measure of social connectedness between U.S. county-pairs, as well as between U.S. counties and foreign countries. Our measure, which we call the 'Social Connectedness Index' (SCI), is based on the number of friendship links on Facebook, the world's largest online social networking service. Within the U.S., social connectedness is strongly decreasing in geographic distance between counties: for the population of the average county, 62.8% of friends live within 100 miles. The populations of counties with more geographically dispersed social networks are generally richer, more educated, and have a higher life expectancy. Region-pairs that are more socially connected have higher trade flows, even after controlling for geographic distance and the similarity of regions along other economic and demographic measures. Higher social connectedness is also associated with more cross-county migration and patent citations. Social connectedness between U.S. counties and foreign countries is correlated with past migration patterns, with social connectedness decaying in the time since the primary migration wave from that country. Trade with foreign countries is also strongly related to social connectedness. These results suggest that the SCI captures an important role of social networks in facilitating both economic and social interactions. Our findings also highlight the potential for the SCI to mitigate the measurement challenges that pervade empirical research on the role of social interactions across the social sciences. |
| Keywords: | Diffusion of Information; homophily; Measurement; migration; Patent Citations; Social Networks; Trade |
| JEL: | D8 F1 J6 L14 O33 R23 |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12146&r=pay |