BARAC investigates the feasibility of using blockchain technology for automating regulation and compliance producing a proof-of-concept platform and facilitating knowledge transfer by means of a bottom-up cross-disciplinary approach developed together with industry and regulators. Blockchain Distributed Ledger Technologies (DLT) are of great interest to the financial industry because they have the potential to improve efficiency, augment security, eliminate duplications, simplify compliance and increase settlement speed, transparency and verifiability while preserving privacy and anonymity. These technologies are also of great interest to regulators because they provide very powerful auditing tools which can be used for automatic compliance reporting and algorithmic regulation. These technologies introduce several disruptive innovations in this area giving access to auditable data which are hard to tamper with and include both real time and the entire history; providing new instruments to monitor and quantify reputation of users; generating transparent, yet securely encrypted, environments where rules can be implemented enforced and adapted. In this project we investigate technical, legal and managerial aspects related to use of DLT in the services industry including the significance of new business models and their effects on industry structure. BARAC aims to: i) demonstrate that blockchain technologies can be used to acquire and record financial activity data and to securely retrieve them for regulation and compliance purposes; ii) implement a case-study proof-of-concept platform for automatic compliance and algorithmic regulation from blockchain data; iii) transfer knowledge to industry and regulators and disseminate results to academic community and the wider public. This will be achieved by adapting existing DLT systems, such as hyperledger (open source DLT project from Linux Foundation) and Corda (DLT project from R3-CEV for financial applications), to provide access to regulatory and compliance data for regulators and by designing smart contracts that automatically verify and execute regulations using smart contracts. We intend to set up a proof-of-concept platform where the feasibility of using DLT technology for compliance and regulation of financial services can be tested in practice addressing industry-relevant case studies. This platform will be built with a bottom up approach working together with our industry and regulator partners and constructed around their requirements and perspectives. BARAC addresses several challenges that span across many disciplines; therefore a cross-disciplinary effort is essential and indeed this project has gathered together PI and co-Co-Is from five different Departments including Computer Science, Mathematics, Law, Economics, Management and Finance from four different institutions. Together with academia, the proponents' consortium includes regulators, financial industry and the technology sector. This project has the potential to radically change the way in which regulation and compliance are performed essentially reverting the present approach. Firms will no longer have the duty to report to regulators but instead regulators will access auditable data directly from the DLT. This will radically reduce the burden on firms increasing efficiency, transparency and eliminating the risk of unintentional breaching of compliance and regulation rules. The impact will not only be felt on the financial services sector but will also ripple across the entire services sector from healthcare to the food industry and education. Indeed all industries and services are regulated and need to comply by reporting information to the relative authorities and government bodies. It will also have impact upon business models and managerial practices.

How can we trust autonomous computer-based systems? Autonomous means "independent and having the power to make your own decisions". This proposal tackles the issue of trusting autonomous systems (AS) by building: experience of regulatory structure and practice, notions of cause, responsibility and liability, and tools to create evidence of trustworthiness into modern development practice. Modern development practice includes continuous integration and continuous delivery. These practices allow continuous gathering of operational experience, its amplification through the use of simulators, and the folding of that experience into development decisions. This, combined with notions of anticipatory regulation and incremental trust building form the basis for new practice in the development of autonomous systems where regulation, systems, and evidence of dependable behaviour co-evolve incrementally to support our trust in systems. This proposal is in consortium with a multi-disciplinary team from Edinburgh, Heriot-Watt, Glasgow, KCL, Nottingham and Sussex, bringing together computer science and AI specialists, legal scholars, AI ethicists, as well as experts in science and technology studies and design ethnography. Together, we present a novel software engineering and governance methodology that includes: 1) New frameworks that help bridge gaps between legal and ethical principles (including emerging questions around privacy, fairness, accountability and transparency) and an autonomous systems design process that entails rapid iterations driven by emerging technologies (including, e.g. machine learning in-the-loop decision making systems) 2) New tools for an ecosystem of regulators, developers and trusted third parties to address not only functionality or correctness (the focus of many other Nodes) but also questions of how systems fail, and how one can manage evidence associated with this to facilitate better governance. 3) Evidence base from full-cycle case studies of taking AS through regulatory processes, as experienced by our partners, to facilitate policy discussion regarding reflexive regulation practices.