Know your customer:balancing innovation and regulation for financial inclusion

Financial inclusion depends on providing adjusted services for citizens with disclosed vulnerabilities. At the same time, the financial industry needs to adhere to a strict regulatory framework, which is often in conflict with the desire for inclusive, adaptive, and privacy-preserving services. In this article we study how this tension impacts the deployment of privacy-sensitive technologies aimed at financial inclusion. We conduct a qualitative study with banking experts to understand their perspectives on service development for financial inclusion. We build and demonstrate a prototype solution based on open source decentralized identifiers and verifiable credentials software and report on feedback from the banking experts on this system. The technology is promising thanks to its selective disclosure of vulnerabilities to the full control of the individual. This supports GDPR requirements, but at the same time, there is a clear tension between introducing these technologies and fulfilling other regulatory requirements, particularly with respect to 'Know Your Customer.' We consider the policy implications stemming from these tensions and provide guidelines for the further design of related technologies.Comment: Published in the Journal Data & Polic

Algorithms & Fiduciaries: Existing and Proposed Regulatory Approaches to Artificially Intelligent Financial Planners

Artificial intelligence is no longer solely in the realm of science fiction. Today, basic forms of machine learning algorithms are commonly used by a variety of companies. Also, advanced forms of machine learning are increasingly making their way into the consumer sphere and promise to optimize existing markets. For financial advising, machine learning algorithms promise to make advice available 24–7 and significantly reduce costs, thereby opening the market for financial advice to lower-income individuals. However, the use of machine learning algorithms also raises concerns. Among them, whether these machine learning algorithms can meet the existing fiduciary standard imposed on human financial advisers and how responsibility and liability should be partitioned when an autonomous algorithm falls short of the fiduciary standard and harms a client. After summarizing the applicable law regulating investment advisers and the current state of robo-advising, this Note evaluates whether robo-advisers can meet the fiduciary standard and proposes alternate liability schemes for dealing with increasingly sophisticated machine learning algorithms

Mechanisms for Automated Negotiation in State Oriented Domains

This paper lays part of the groundwork for a domain theory of negotiation, that is, a way of classifying interactions so that it is clear, given a domain, which negotiation mechanisms and strategies are appropriate. We define State Oriented Domains, a general category of interaction. Necessary and sufficient conditions for cooperation are outlined. We use the notion of worth in an altered definition of utility, thus enabling agreements in a wider class of joint-goal reachable situations. An approach is offered for conflict resolution, and it is shown that even in a conflict situation, partial cooperative steps can be taken by interacting agents (that is, agents in fundamental conflict might still agree to cooperate up to a certain point). A Unified Negotiation Protocol (UNP) is developed that can be used in all types of encounters. It is shown that in certain borderline cooperative situations, a partial cooperative agreement (i.e., one that does not achieve all agents' goals) might be preferred by all agents, even though there exists a rational agreement that would achieve all their goals. Finally, we analyze cases where agents have incomplete information on the goals and worth of other agents. First we consider the case where agents' goals are private information, and we analyze what goal declaration strategies the agents might adopt to increase their utility. Then, we consider the situation where the agents' goals (and therefore stand-alone costs) are common knowledge, but the worth they attach to their goals is private information. We introduce two mechanisms, one 'strict', the other 'tolerant', and analyze their affects on the stability and efficiency of negotiation outcomes.Comment: See http://www.jair.org/ for any accompanying file

Dovetail: Stronger Anonymity in Next-Generation Internet Routing

Current low-latency anonymity systems use complex overlay networks to conceal a user's IP address, introducing significant latency and network efficiency penalties compared to normal Internet usage. Rather than obfuscating network identity through higher level protocols, we propose a more direct solution: a routing protocol that allows communication without exposing network identity, providing a strong foundation for Internet privacy, while allowing identity to be defined in those higher level protocols where it adds value. Given current research initiatives advocating "clean slate" Internet designs, an opportunity exists to design an internetwork layer routing protocol that decouples identity from network location and thereby simplifies the anonymity problem. Recently, Hsiao et al. proposed such a protocol (LAP), but it does not protect the user against a local eavesdropper or an untrusted ISP, which will not be acceptable for many users. Thus, we propose Dovetail, a next-generation Internet routing protocol that provides anonymity against an active attacker located at any single point within the network, including the user's ISP. A major design challenge is to provide this protection without including an application-layer proxy in data transmission. We address this challenge in path construction by using a matchmaker node (an end host) to overlap two path segments at a dovetail node (a router). The dovetail then trims away part of the path so that data transmission bypasses the matchmaker. Additional design features include the choice of many different paths through the network and the joining of path segments without requiring a trusted third party. We develop a systematic mechanism to measure the topological anonymity of our designs, and we demonstrate the privacy and efficiency of our proposal by simulation, using a model of the complete Internet at the AS-level

In Search of Stars: Network Formation among Heterogeneous Agents

This paper reports the results of a laboratory experiments on network formation among heterogeneous agents. The experimental design extends the basic Bala-Goyal (2000) model of network formation with decay and two-way flow of benefits by allowing for agents with lower linking costs or higher benefits to others. We consider treatments where agents’ types are common knowledge and treatments where agents’ types are private information. In all treatments, the (efficient) equilibrium network has a “star” structure. We find that with homogeneous agents, equilibrium predictions fail completely. In Contrast, with heterogeneous agents stars frequently occur, often with the high-value or low- cost agent in the center. Stars are not borne but rather develop: in treatments with a high-value agents, the network’s centrality, stability, and efficiency all increase over time. Our results suggest that agents’ heterogeneity is a major determinant for the predominance of star-like structures in real-life social networks.microeconomics ;

Notes on Cloud computing principles

This letter provides a review of fundamental distributed systems and economic Cloud computing principles. These principles are frequently deployed in their respective fields, but their inter-dependencies are often neglected. Given that Cloud Computing first and foremost is a new business model, a new model to sell computational resources, the understanding of these concepts is facilitated by treating them in unison. Here, we review some of the most important concepts and how they relate to each other

Why and How Your Traceability Should Evolve: Insights from an Automotive Supplier

Traceability is a key enabler of various activities in automotive software and systems engineering and required by several standards. However, most existing traceability management approaches do not consider that traceability is situated in constantly changing development contexts involving multiple stakeholders. Together with an automotive supplier, we analyzed how technology, business, and organizational factors raise the need for flexible traceability. We present how traceability can be evolved in the development lifecycle, from early elicitation of traceability needs to the implementation of mature traceability strategies. Moreover, we shed light on how traceability can be managed flexibly within an agile team and more formally when crossing team borders and organizational borders. Based on these insights, we present requirements for flexible tool solutions, supporting varying levels of data quality, change propagation, versioning, and organizational traceability.Comment: 9 pages, 3 figures, accepted in IEEE Softwar