The Social Meaning of Mobile Money: Navigating Digital Payments, Savings and Credit in the Global South

by Janaki Srinivasan, PhD, IIIT-Bangalore and IMTFI Fellow

"The Social Meaning of Mobile Money," Chapter 7 of Data-Centric Living: Algorithms, Digitization and Regulation, edited by V. Sridhar; November 30, 2021; Routledge India, 344pp.

ABSTRACT 

Financial transactions have been an integral part of people’s everyday transactions the world over. Whether in the form of cash, credit, plastic cards or today, using digital platforms, these transactions continue to both structure and be shaped by the existing social order . Using a “social meaning of money” framing , this chapter draws on examples from around the world to better understand how people give, receive and save money in the Digital Age. In the process, it attempts three shifts in focus: (1) from the inherent value of monetary technologies to how this value is constituted in practice within specific constellations of norms, values, power relations and resource distribution, (2) from the use of digital platforms to the integration of their use with non-digital artefacts in practice, and (3) from the innovativeness of technology design to the innovativeness of its users. The chapter finds that while mobile financial tools and associated data may well be making the world of financial transactions more inclusive in some ways, they simultaneously risk excluding certain categories of people, practices and geographies from the economy. By alerting us to the promise and perils of newly introduced modes of transacting our finances, this chapter will urge its audience to think more realistically about how to better design such tools and the policies regulating them.

Download full chapter online here: https://www.taylorfrancis.com/chapters/edit/10.4324/9781003093442-7/social-meaning-mobile-money-janaki-srinivasan

This chapter is part of the collection: Data-Centric Living: Algorithms, Digitization and Regulation, edited by V. Sridhar and is available online. The book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book  investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world.

A timely intervention in this fast-evolving field, this book is useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It is also of immense interest to the general readers seeking insights on daily digital lives.

Opportunities and Risks of Conversational AI for Credit Unions: Empathy and Intimacy in Automated Financial Customer Service

by Scott Mainwaring, UCI and Melissa Wrapp, UCI, Filene's Center for Emerging Technology

As the use of digital channels continues to grow for credit unions, conversational artificial intelligence (AI) technologies provide an opportunity for improved service delivery and the potential for new service offerings such as financial advice.

EXECUTIVE SUMMARY

Conversational AI technologies create new ways for credit unions to serve their members, from providing alternatives to interacting with human agents to creating new channels for more tailored financial services. They provide opportunities to build upon the trust and appreciation members place in credit unions as more human-centered, nonpredatory, and community based. But conversational AI technologies risk invading members’ privacy and being frustrating and opaque.

WHAT IS THE RESEARCH ABOUT?

This exploratory study looks at existing consumer relationships with conversational AI and digital assistants, on one hand; and with credit unions, banks, and other businesses, on the other, to begin to sketch the dimensions of, and provide examples of, points within a “design space” of possible financial digital assistants. While operational hurdles remain high for credit unions to deploy these new technologies, the opportunity will continue to grow in coming years. 

Through ethnographic research with consumers, this report anticipates how credit union members might come to value, or reject, digital assistants. For this exploratory study, we focused on one main question: What are the implications of digital assistant technologies for how members and credit unions could relate to one another in the next five years?

Interviews covered three broad topics: experiences using banks and credit unions; experiences using digital assistant technologies; and reflections on the idea of a financial digital assistant and issues of privacy, trust, and potential bias. This report summarizes findings on these themes and provides insight into how credit unions could take advantage of digital assistants to improve service delivery and differentiate offerings by incorporating elements from their mission and value proposition into their digital assistants. The way forward is to develop particular product proposals and related data transparency policies that can provide members with a new understanding of what they could achieve by relating with their credit unions through “talking computers.”

WHAT ARE THE CREDIT UNION IMPLICATIONS? 

Credit unions have an opportunity to deploy digital assistants in ways that improve service delivery and member experience and provide new types of service offerings. In thinking about what types of digital assistants would provide the best fit for your credit union and member needs, keep the following research findings in mind: 

• People like the promise of bots as part of a modern, organized, and simplified life.
• The realities of existing bots fall short of expectations and can limit imagination.
• People are resigned to the constant advance of technology without transparency or the ability to meaningfully opt out.
• Relations with credit unions are valued for their human element and trustworthiness, even if this means older, clunkier tech.
• The design space is complex, including diverse combinations of technologies, member needs, and business opportunities worth considering.
• The idea of talking with/through bots is becoming mundane, but credit unions could pleasantly surprise members with unique service features.
• Credit unions could tailor these technologies to show their strengths and to educate members not just about finances but also about data. 

In order to create a competitive advantage, credit union digital assistants would have to not only be useful and usable but also embody and express the core values of the credit union system. By building upon these core values of empathy and respect, credit unions could focus their development of digital assistant technologies in a way that creates differentiation, even with fewer resources than are available to larger financial services providers. 

We use findings from our research to generate design ideas that are meant to illustrate pathways worth exploring, developing, and evaluating: 

• Build a helpful, always-accessible agent. This kind of digital assistant could serve as the voice of the specific credit union and provide basic support but also demonstrate the “members not customers” ethos of the credit union value proposition.
• Provide an assistant to help members maintain, augment, and monitor their personal financial support systems.
• Provide robot counsel. This financial digital assistant could serve as a “second pair of eyes” as members conduct transactions with any financial services provider, intervening if necessary but always being available for reassurance or advice.
• Connect members to each other. This assistant would embody the credit union as a member cooperative, helping connect members to each other.

Access complete report, summary slides, and design principles here.

Digital Transformation in the Age of COVID-19: What Should Credit Unions Deliver?

by Bill Maurer and Scott Mainwaring, Center of Excellence for Emerging Technology at UC Irvine

The old era of neighborhood branch gathering places no longer looks tenable as a new era dawns of self- and curbside-service, constant online connectivity, and conversation in virtual spaces.

Digital transformation is here with a vengeance, whether we like it or not. The global COVID-19 pandemic has people paying with mobile apps instead of cash, applying for and receiving assistance online, and coping with anxieties around housing, employment, debt, and even bankruptcy. The cascading consequences of the pandemic means that credit unions must urgently engage with business reinvention in order to continue their mission of service to their members’ financial well-being. How can this mission be sustained even as online becomes the dominant way they deliver products, offer support, and work with members to solve problems?

We have been researching the implications for credit unions of emerging technologies that use so-called artificial intelligence techniques to support “natural” conversations, though text, voice, and/or graphics, between people and artificial agents that more or less pose as people in enacting a service. Amazon’s Alexa and Apple’s Siri are well-known examples, through financial service-specific versions like Bank of America’s Erica have also launched.

As social scientists, we start from a broad set of questions about how people experience and expect these systems to behave, both positively and negatively. And for these “conversational agent” technologies, we start in particular with questions of intimacy and empathy.

Intimacy of AI
In 2018 the popular parenting website BabyCenter released results of a survey it conducted on new parents and their use of AI assistants like Alexa and Siri. The results were striking—seven in ten parents own a smart device; and a third of those said that having one made them a better parent. 22% percent said their virtual assistants are “like another part of the family,” and 42% of device owners say that they speak to their virtual assistants like an actual person. The “intimacy of AI,” as AdWeek calls it, seems inevitable.

Voice and AI aside, intimacy is already central to smartphones themselves. These personal and personalized devices are our constant, daily, bodily companions. Add an always-available virtual assistant to chat with, and our relationship with our phones—especially in a time of social distancing—becomes even closer.

“Intimacy” from virtual assistants being rolled out by the big banks is threatening to credit unions precisely because credit unions have historically prided themselves on the quality of their customer service and their knowledge of their members. Take Bank of America’s Erica. Via your smartphone, she can help you plan a spending path, manage your expenses, alert you to when bills or other recurrent payments are coming due, give your FICO score, and even provide rudimentary credit counseling.

If interactions with financial digital assistants are to replace person-to-person conversations with customer service agents, is the credit union system back in a familiar position of trying to play catch-up with the big banks and their big pockets? Not entirely – to employ new technologies that put people first, credit unions have advantageous positions as member cooperatives that place well-being over profits.


Continue reading about intimacy, empathy, and opportunities for credit unions in the age of COVID-19, full post on the Filene Research Institute blog available here: https://filene.org/blog/digital-transformation-in-the-age-of-covid-19-what-should-credit-unions-deliver

A Survey of Fair and Responsible Machine Learning and Artificial Intelligence: Implications for Consumer Financial Services

by Stephen C. Rea, PhD, Research Assistant Professor at Colorado School of Mines and former IMTFI Research Assistant

Capital One Eno Chatbot

Stephen Rea recently published a white paper surveying literature in computer science, law, and the social sciences on developments in machine learning and artificial intelligence, with special focus on their implications for consumer financial services in the United States. This project grew out of a joint collaboration between IMTFI and Capital One's Responsible AI Program. We present here an excerpt from the introduction to the white paper, followed by some updates about recent developments in this space. 

Excerpt
Machine learning (ML) algorithms and the artificial intelligence (AI) systems that they enable are powerful technologies that have inspired a lot of excitement, especially within large business and governmental organizations. In an era when increasingly concentrated computing power enables the creation, collection, and storage of “big data,” ML algorithms have the capacity to identify non-intuitive correlations in massive datasets, and as such can theoretically be more efficient and effective than humans at using those correlations to make accurate predictions. What is more, AI systems powered by ML algorithms represent a means of removing human prejudices from decision-making processes; since an AI system renders its decisions based solely on the data available, it can avoid the conscious and unconscious biases that often influence human decision-makers.

Contrary to this rosy picture of ML and AI, though, decades of evidence demonstrate how these technologies are not as objective and unbiased as many perhaps wish they were. Biases can be encoded in the datasets on which ML algorithms are trained, arising from poor sampling strategies, incomplete or erroneous information, and the social inequalities that exist in the actual world. And since ML algorithms and AI systems cannot build themselves, the humans who construct them may, however unintentionally, introduce their own biases when deciding on a model’s goals, selecting features, identifying which attributes are relevant, and developing classifiers. Additionally, the inherent complexities of ML algorithms that defy explanation even for the most expert practitioners can make it difficult, if not impossible, to identify the root causes of unfair decisions. That same opacity also presents an obstacle for individuals who believe that they have been evaluated unfairly, want to challenge a decision, or try to determine who should—or even ​could​—be held accountable for mistakes.

Compared to other fields, the financial services industry has taken a relatively conservative approach to ML/AI integrations. Consumer-facing applications like robo-advisors for portfolio management, AI-powered banking assistants, algorithmic trading programs, and proactive marketing tools, as well as harnessing the power of ML to do sentiment analysis of social media feeds and news stories in search of trendlines, have garnered a lot of media attention. However, the visibility of initiatives like these in press releases and news items exaggerates their role in financial services today, as they represent less than one-tenth of the funding received in the financial technology, or “fintech,” vendor space. Thus far, financial institutions have primarily invested in ML and AI for automating routine, back-office tasks, improving fraud detection and cybersecurity, and making regulatory compliance easier. 

The current state of ML and AI in consumer financial services, then, is one in which there is still enormous opportunity for innovation, but also reasons to be cautious. To paraphrase the feminist geographer Doreen Massey, some individuals and groups are more on the “receiving end” of these technologies than others. In other words, ML and AI’s advantages and disadvantages are not equally distributed. Nor are the vulnerabilities entailed by digital surveillance techniques for data creation and collection, the sorts of harm that can occur from an erroneous data entry and the burden for correcting it, or the ability to affect how an algorithm interprets one’s individual attributes and characteristics. In many ways, ML/AI research’s most important contributions have been demonstrating the extent to which structural inequalities—that is, conditions by which one or more groups of people are afforded unequal status and/or opportunities in comparison to other groups—persist by providing quantifiable, documented evidence of social disparities. If an organization’s reason for integrating ML- and AI-powered systems is to improve its decision-making procedures so as to make them both more accurate and fairer, then it is imperative to understand and account for persistent inequalities in the social contexts where those systems are embedded. Furthermore, assessing how exactly an algorithmic and/or automated decision-making system could impact specific populations, the risk that it could violate legal standards prohibiting discrimination, and the extent to which the system could perpetuate structural inequalities are of the utmost importance when deciding whether or not to make the integration in the first place.

You can read the rest of the white paper on SSRN.

Updates

Work in ML and AI is fast-moving, and in the time since this paper was published, there have been a number of developments that will affect how these technologies are integrated with the consumer financial services industry and beyond. Two in particular merit attention here:

1) Congressional action: On February 12, 2020, the U.S. House Committee on Financial Services' Task Force on Artificial Intelligence heard testimony from experts on AI, ML, and race and inclusion in a panel titled “Equitable Algorithms: Examining Ways to Reduce AI Bias in Financial Services.” The Committee acknowledged the usefulness of standards for the fairness and accuracy of AI applications in financial services, while also noting that existing laws such as the Equal Credit Opportunity Act, the Fair Housing Act, and the Fair Credit Reporting Act are inadequate in many respects for regulating AI's impact. The panel of experts recommended drafting a definition of "fairness" that could be used for evaluating ML, developing audit and assessment methods for locating biases in data and models, and requiring ML/AI developers to implement and report upon continuous monitoring plans that can detect new biases as they emerge. They also voiced concern regarding the Department of Housing and Urban Development's plans to revise the Fair Housing Act's disparate impact standards, and how such action might exacerbate the discriminatory effects of AI in home lending. 

2) Sandvig v. Barr decision: In March 2020, the U.S. District Court for the District of Columbia delivered its ruling in Sandvig v. Barr, which challenged a provision in the Computer Fraud and Abuse Act (CFAA) that made it a crime for researchers and journalists to use "dummy" accounts for the purposes of auditing algorithms in order to identify possible discrimination. The American Civil Liberties Union had initially brought the lawsuit in 2016 on behalf of a group of academics and journalists led by Christian Sandvig of University of Michigan's School of Information. The plaintiffs argued that the CFAA violated their First Amendment rights, and noted that comparable research activities were not illegal in offline contexts. The Court ruled in favor of the plaintiffs, thereby opening the door for more independent review of ML/AI applications and scoring an important victory for researchers' ability to hold algorithms and the institutions that use them accountable.

Additional Resources

AI Now Institute: https://ainowinstitute.org
Data and Society's AI on the Ground initiative: https://datasociety.net/research/ai-on-the-ground/

In Search of the Human Face of Artificial Intelligence

by Bill Maurer and Daivi Rodima-Taylor in Backchannels, Society for Social Studies of Science (4S)

“Once bots gained human rights, a wave of legislation swept through many governments and economic coalitions that later became known as the Human Rights Indenture Laws. They established the rights of indentured robots, and, after a decade of court battles, established the rights of humans to become indentured, too. After all, if human-equivalent beings could be indentured, why not humans themselves?” – Annalee Newitz, Autonomous

Figure 1. At the Symposium. Credits: Daivi Rodima-Taylor

We recognize the grim logic governing unfree labor in Annalee Newitz’s 2017 novel about future forms of property. Contemporary forms of human slavery and indenture occupy the same world as new intelligent computational systems and human-computational assemblages that are shifting the nature of work and contract—see, for instance, ride hailing, which is only a prelude to broader changes in augmented labor relations. This conjuncture brings to the fore urgent questions of autonomy, infrastructure, and ethics.

The symposium “The Human Face of Artificial Intelligence: Infrastructures, Narratives, Ethics” that took place at the University of California, Irvine on October 17, 2019, brought together an interdisciplinary and international group of scholars to discuss new challenges and opportunities around the systems of AI. Broadly defined as intelligent automated systems that can analyze their environment, make decisions and adapt their behavior by learning from experience, systems of AI steadily permeate social and political spaces, fomenting novel conversations about law, ethics, governance, sociality, and humanity.

If a complex AI system malfunctions and causes harm to humans, who or what should be found liable and according to which criteria? Should AI be viewed as a mere technological tool, or an autonomous agent with a free will? How does artificial intelligence reshape our conversations about legal personhood and human spirituality within this increasingly complex intersection of humanity and technology? Exploring the conceptualizations of a legal person in the history of Anglo-American jurisprudence, Summer Kim of UCI Law School discussed the challenges around prescribing new rights and obligations to artificially intelligent autonomous agents. Reflecting on lessons from arguments that corporations have used to enjoy some of the rights that natural persons have, she examined the ways how corporate law could guide the responsible use of technology in society.

Read the full post on Backchannels, Society for Social Studies of Science (4S) here: https://www.4sonline.org/blog/post/in_search_of_the_human_face_of_artificial_intelligence

Blockchain Narratives, Property and Belonging in Post-Soviet Eastern Europe

by Daivi Rodima-Taylor, Boston University

The kratt. Source: Medium.com

In Estonian folklore, the kratt or “firetail” was a creature humans assembled out of old household objects and animated by drops of blood to performs tasks for its human master. In the current day, this mythological critter has gained prominence in the cultural and political space of post-socialist Estonia – including recent efforts around the implementation of artificial intelligences or ‘kratts’ in the country’s e-governance and private sector, and discussions of KrattLaw around the legal status of AI. Why has this folk metaphor from an Eastern European peasant tradition become central in debates about emerging digital technologies that we often think about as so definitively global?

Looking at the cases of Estonia and Georgia, I am interested in how post-socialist Europe’s historically and locally specific adoption of these new digital technologies may offer insights into the social imaginaries of blockchain. There is an increasing understanding that digital technologies such as blockchain are not merely technological tools, but carry important social and political implications. The use of blockchain in the public administration systems of post-socialist Eastern Europe offers interesting perspectives on how attitudes in popular culture cast light on how these technologies are instituted and used.

BLOCKCHAIN
Blockchain is a software protocol that facilitates electronic transfer of information without the need for third-party intermediation. Changes in its ledger are added to the data structure when multiple distributed parties come to consensus based on pre-agreed rules. The new modes of decentralized value transfer, identity verification, and business and asset management enabled by crypto-codes raise novel questions about the nature of social trust and institutions such as property and citizenship as mediated by the new technology.

With its origins partly in crypto-utopian pursuits of decentralized monetary and governance technologies, blockchain has increasingly appealed to more traditional institutions of finance and governance. Governments are pursuing blockchain technologies to render their populations and property systems legible while enhancing transparency.

Blockchain has been hailed as a key technology to help formalize property rights by facilitating secure and transparent land registries – a technology that would “unlock the value of landholding” and boost the entrepreneurial potential of its owners. It is perhaps no wonder that the assumed potential of blockchain to facilitate order and formality in situations of instability is particularly pronounced in post-socialist and post-conflict states. Specific histories of post-socialist property restructuring and decollectivization efforts to (re)construct private property have been marked by legal and administrative ambiguities and alternative institutional arrangements. New property forms may blur distinctions between private and public, resulting in “recombinant” property forms that can be assessed by multiple standards of measure. The promise of a secure digital public database may therefore particularly appeal to societies characterized by fuzzy normative frameworks and unclear land use practices.

Farmland in Tanzania. Photo: Daivi Rodima-Taylor

Currently existing application cases, however, cast doubt on the potential of blockchain to automatically rectify the vast expanses of informality, signaling logistical and political challenges, as in the examples of Honduras and Ghana. Blockchain land registration is underway in Georgia, offering interesting glimpses into the political and social rationale of such initiatives, as well as the implications for existing infrastructure.

GEORGIA
Selling land in post-socialist Georgia used to be a long process, prone to bribery. The development of the Georgian land registry was seen as justified by popular sentiments that “politicians could influence transactions.” Georgia re-gained its independence from the Soviet Union in 1991 after a centuries-long history of foreign invasions, reducing public trust in government. Many property records had disappeared or were non-verifiable after the fall of the Soviet Union. The expansive land denationalization reintroduced the notion of private property, and in doing so created a vast database of recent land titles.

Georgia’s blockchain adoption built on its openness to other digital technologies. The arrival of blockchain-empowered land registries in Georgia was preceded by a decade-long effort to digitize property and business registries of the country, with the help of international development banks and aid agencies. The National Agency of Public Registry (NAPR) partnered with the blockchain company Bitfury in 2016, to elevate the protection of property rights “from national to global levels.” The blockchain layer was thus designed to function as an addition to the already existing IT infrastructure of the database. Over 300,000 titles were transferred to blockchain, drastically reducing transaction speeds and operational costs, and smart sales contracts for property transactions were piloted in 2017.

Bitfury had been operating bitcoin mining centers in the area since 2015, so residents and government institutions were already somewhat familiar with the blockchain technology. Due to popular awareness about cryptocurrencies, many individuals took up small-scale mining activities in their garages. The World Bank estimated in 2018 that up to 5% of households in Georgia were engaged in cryptocurrency mining or investments.

Bitcoin mining in Georgia. Source: NPR

ESTONIA
Elsewhere in post-socialist Eastern Europe, Estonia’s innovative e-governance demonstrated a similar embeddedness between distributed digital technologies and existing digital infrastructures, initiatives, and political rationales. The e-Estonia system is considered the most ambitious nation-wide digital initiative globally. With a small population of 1.3 million, Estonia has a unique socio-political background, including a desire to re-connect with the outside after the Soviet-era isolation. Security was a significant factor - the organized cyber-attacks against the Estonian Internet infrastructures by Russia’s hackers in 2007 mobilized a unified digital response. Since 2000, Estonia has employed a distributed data exchange layer for secure online transfers between information systems – X-Road. In 2007, a team of Estonian software and security specialists designed the digital signature system that would lead to Keyless Signature Infrastructure (KSI) Blockchain Technology Stack that is used in a variety of state registries.

The well-established national digital services framework served as a basis for the innovative e-Residency initiative. Offering a transnational digital identity to citizens of any part of the globe, it allows anyone outside Estonian borders to engage in commercial activities with public and private sectors. About 35,000 e-residents have applied from 160 countries, with thousands of new companies established. As the first program in the world to provide a government-authenticated digital identity to foreigners, it could be seen a step towards a novel idea of a borderless state. The e-Residency platform also serves as a site of expansion for other blockchain initiatives in the country such as decentralized public notary services with blockchain startup Bitnation, and Nasdaq’s blockchain applications with Tallinn Stock Exchange. While the distributed technologies allow the users of Estonian e-governance initiatives better control over their data, the country’s digital embeddedness is viewed as serving an important security protection for the small state with turbulent history. E-Estonia likens blockchain to “digital defence dust” that covers data and smart devices for protection from corruption and misuse, noting that blockchain could be compared to the deterring effects of NATO allies in Estonia.

AMBIGUITY AND EMBEDDEDNESS 
The growing use of blockchain in public administration systems also gives rise to new risks and vulnerabilities. By enabling an “unbundling” of property rights, blockchain registry facilitates a market for small real estate investments, and as other digital registries, may foster an illusion of immutable land rights, while backgrounding other relevant relationships around the landholding. The entry of private startups working with governments in the blockchain space may entail implicit privatization of land registries, creating private markets in public data. The increasing financialization of land may thus be part of the tendency to “re-risk” that often accompanies blockchain applications.

While it is too early to evaluate the actual impact of these technologies in Eastern Europe, it is evident that rather than cutting out the middleman, blockchain registries build on existing social and political frameworks and infrastructures. In order to understand the ongoing reintroduction of intermediaries and the types of “recombinant” collectivities and property forms blockchain registries facilitate, one should study the social imaginaries and metaphors that surround the technology. It is perhaps unsurprising, then, that figures like the kratt from folklore suggest themselves to help narrate the new relationship between technologies with globalizing potentials, and post-socialist projects of the re-emerging nation state.

The kratt could be seen as a broader cultural metaphor of how Estonians think of their digital infrastructures - as a pragmatic combination of different elements and layers of technology, animated by human agency and desire – but also a creature with a separate subjectivity. Estonian digital progress could be seen as an expression of an important continuity embodied in the character of the kratt – as representing indigenous inventiveness and resilience that has sustained Estonians throughout their difficult history. This cultural metaphor for a particular kind of symbiosis between humanity and technology also entails an acknowledgement of an inherent unpredictability of the digital technology that, similarly to the kratt, could turn against its creators and has to be managed by smart policies and “KrattLaws.” The folkloric creature - the kratt - has thus become an important popular metaphor for efforts to grapple with the emerging ethical issues around digital technologies, while calling attention to the fruitful connections fostered through these, as well as their inherent precariousness.

November (2018) Exclusive Clip "Kratt Needs Work" HD

While the implementation of digital technology often accompanies a global sense of oneness, the example of Estonian ‘recombinant’ nationhood that defines allegiances in terms of virtual and not territorial or ethnic affinities, and the blockchain land registry in Georgia that legitimizes private property after long decades of socialist rule, suggest these national distributed digital projects need to be studied in their own terms. Only then is it possible to evaluate the promise of decentralizing digital technologies for enhancing democratic and participatory governance.

Daivi Rodima-Taylor is reachable at rodima@bu.edu.

Understanding fintech from the U.S. to China

By Melissa Wrapp and Bill Maurer

On September 28-29, the 2018 California-Shanghai Innovation Dialogues hosted by UC Irvine brought together scholars, policymakers, and industry professionals from across the globe to discuss the ethics and broader social impact of emergent technologies, from insurtech to blockchain to roboadvising. Filene’s newest Fellow, Bill Maurer, gave a talk analyzing the burgeoning cryptocurrency ‘ICO’ phenomenon focusing on the power of big data and digital platforms to create seemingly totalizing systems. Here, Maurer teases out some of the major financial innovations headed our way and the socioeconomic implications that credit unions should be attuned to.

Photo credit: Marilyn Nguyen

What changes are happening in the international fintech space?
We are living in an increasingly digital world. The decreasing costs and rising quality of smart devices is accelerating fintech use. More and more we can expect to see technologies developing around what some are calling the ABCDs: AI, Blockchain, Cloud, and big Data. In China in particular, apps that create an ecosystem of different utilities, such as WeChat Pay and Alipay, are becoming giants in the mobile payments space—and reaching beyond payments into transit, bike sharing, credit, dog walking, you name it. Although their rise in China is in part linked to particularities of the local context, it is important for us to understand these technologies as companies like Facebook, Apple, and Google make moves toward integrating payments, social media, news, and other applications.

Filene Fellow Bill Maurer. Photo Credit: Marilyn Nguyen.

Americans sometimes struggle to understand what they see as Chinese consumers’ relaxed attitude toward data aggregation. What is the appeal of these apps?
For many in China, it is the same as the reason we in the US unthinkingly click through user license agreements without reading: convenience. Analysts are often quick to jump to a framework of surveillance and oppression in conceptualizing Chinese financial innovations. This isn’t unreasonable given the government’s proclivities toward censorship. There are already signs that “social credit” schemes (think Uber ratings, but for everything in your life) may be used to silence political dissidents. And products like Zhima Credit (also known as Sesame Credit), a new social credit scoring system offered by Ant Financial, coincide with broader government plans to collect citizens’ social credit data. However, as scholars at the conference pointed out, these possibilities for algorithmic governance fit into a much broader system of regulation geared toward promoting and maintaining trust in China’s low-trust market environment. So it is important to keep in mind that “convenience” in China is bound up in the social value of stability, concerns over fraudulent goods, and transparent pricing; and that it means something completely different than it does in the American context.

What is something unexpected social scientists have discovered about how people are engaging with new fintech?
People in the tech space often pitch their products in terms of revolutionary, wholesale disruption. However, what we are finding is that rather than entirely replacing things that came before, fintech is creating new layers of possibilities. Turning again to social credit schemes in China, for example, researchers have found that migrant workers are using new apps to access credit in order to extend longstanding patterns of informal lending to friends. Migrants’ efforts to improve their credit scores, therefore, are not linked to a desire to consume more for themselves, but to be able to lend to relations and friends. It is important to pay attention to the way new technologies mix up formal and informal practices, as well as older traditions and tendencies around money with new delivery channels, interfaces, and possibilities. All these continue to be informed by culturally specific moral logics around money, as well as existing financial practices.

Insurtech panel (LtoR): Lei Guang, Liz McFall, Xian Xu, Robert Collins
Photo Credit: Marilyn Nguyen 

What do participants in the credit union movement need to understand about new fintech products?
Despite our best efforts to channel our customers’ behavior toward certain ends, humans will always find workarounds. No matter how “intelligent” roboadvising becomes, for example, it will never fully exclude affect and emotion. No matter how much data is collected by insurtech companies, there will always be a smoker who lives forever and a marathoner who dies young. Sociologist Liz McFall reminds us that the origins of the word risk are related to “things to avoid in the sea.” There will always be things to avoid in the sea: sea monsters, rocks, and reefs lurking beneath the surface that are not fully known. It is better to recognize when people are tinkering, subverting, and otherwise creatively repurposing our technology and try to understand what they are up to and why, than to assume they will adopt tech the way we intend.

Take this conversation to the next level with Filene Fellow, Bill Maurer, when he speaks to how credit unions should analyze the risks of adopting new fintech with its promises and opportunity costs at big.bright.minds.2018. big.bright.minds. brings together experts from each of Filene’s Centers of Excellence to help us redefine consumer financial wellness. Join Bill Maurer and Filene in San Diego on December 6-7.

See original post - https://filene.org/blog/understanding-fintech-from-the-us-to-china

Melissa K. Wrapp
PhD Candidate, Department of Anthropology
University of California, Irvine

Bill Maurer
Dean, School of Social Sciences; Professor, Department of Anthropology and School of Law; Director, Institute for Money, Technology and Financial Inclusion
University of California, Irvine

Market Watch: How artificial intelligence could replace credit scores and reshape how we get loans

“In the abstract, having access to credit is better than not having access to credit and certainly better than having access to really predatory credit at extremely high interest rates,” said Stephen Rea, IMTFI Fellow cited in Market Watch, Oct. 15, 2018. Still, he cautions that while increased credit access has the potential to meaningfully improve the standard of living in emerging markets, companies and consumers must tread carefully.

Image credit: Peter Grundy

Market Watch: How artificial intelligence could replace credit scores and reshape how we get loans

Alternative credit scores — using data, in part, from customers’ smartphones — will be migrating from emerging economies to the U.S.

by Emily Bary

You may not think the number of words in an email subject line says anything about you, but at least one company is betting that the metric can help determine your likelihood of paying back a loan.

LenddoEFL, based in Singapore, is one of a handful of startups using alternative data points for credit scoring. Those companies review behavioral traits and smartphone habits to build models of creditworthiness for consumers in emerging markets, where standard credit reporting barely exists.

In addition to analyzing financial-transaction data, Lenddo’s algorithm takes into consideration things such as whether you avoid one-word subject lines (meaning you care about details) and regularly use financial apps on your smartphone (meaning you take your finances seriously). Lenddo also looks at the ratio of smartphone photos in your library that were taken with a front-facing camera, since selfies indicate youth, helping the company divide people into customer segments.

The data points are unconventional, but Darshan Shah, Lenddo’s managing director for South Asia, says the company’s overall algorithm is a reliable predictor of creditworthiness for the so-called underbanked. For those who lack formal credit histories, Lenddo and others say artificial intelligence can help sort through a variety of data points that, in sum, indicate financial responsibility.

For the full story, please visit https://www.marketwatch.com/story/ai-based-credit-scores-will-soon-give-one-billion-people-access-to-banking-services-2018-10-09