Cryptocurrencies such as Bitcoin are challenging the way we perceive money. Offering new models for financial transactions, based on trust, and maintained through its open transactional database, currencies such as Bitcoin challenge the government-regulated fiat currencies that we currently use today. However, users of cryptocurrencies are beginning to realise that it is the underlying technology of the blockchain that is likely to have the most profound effect on how we understand money. The blockchain is an global open ledger that records and verifies transactions, whilst encrypting the identity of users changes entirely how value is accounted for. No longer are banks or governments the mediators of currencies, with the power to divest or invest to dictate the flow of value within society, the blockchain decentralises money and offers a platform for its creative use. Presenting money as code, users of the blockchain are starting to explore new opportunities for how values can be represented, as technologies such as the blockchain change the representation of value. This project will introduce the underlying principles of the blockchain to audiences that would otherwise not be consulted on the development of new currencies. Using a design-led and participatory approach, the research project will explore potential use cases for money as software through involvement with families, small businesses and local civic services. The research represents a significant contribution to contemporary debates around the emergence of new forms of value exchange and offers tangible outcomes for local, economic and academic communities. This 18 month project addresses directly the ESRC priority area: 'Economic performance and sustainable growth'. The innovative design of this research project, its relationship with actual high street environments and involvement of the New Economic Foundation and the Royal Bank of Scotland constitutes transformative research at the high risk, high reward end of the research spectrum.

Information holds the key to success. The accuracy of data determines operational performance, regulatory compliance and the effectiveness of business strategy. Organisations in every industry worldwide have an increased awareness of the costs and risks caused by data that is inconsistent, inaccurate, stale or deliberately falsified. The Data Warehousing Institute estimates that poor quality data costs US businesses $600 billion annually. Many companies are investing in data quality solutions that help increase transparency and productivity and, as a result, the data quality market is experiencing rapid growth. Whilst these companies are making progress on internal clean up and consolidation tasks, such activities require large amounts of manual effort. A new breakthrough which provides theoretical background and practical algorithms for data quality management has been pioneered at the School of Informatics. This approach, based on a novel extension of classical dependency theory, increases the level of automation and improves accuracy in the data quality process. In 2008, Prof. Wenfei Fan was awarded with the British Computer Society Roger Needham award along with the Chinese Yangtze River Scholar award for his research in this area. Building on the output of this award-winning research, we aim to deliver a concept system, Quaid, which scales to real commercial datasets and addresses the needs of industrial customers. Through Quaid, we envisage new products and services will be generated from existing digital data sources.

Some parts of the UK have persistently higher unemployment rates than others - Figure 1 in the Case for Support shows the unemployment rate in 2011 and 1981 in the largest cities. Although some parts of the South perform poorly and some parts of the North perform well, it is remarkable how marked is the 'North-South' divide in the level and persistence of unemployment. It is often argued that migration is the main force that would be expected to equalize economic opportunity across areas - with people moving from disadvantaged to more advantaged areas thus reducing the competition for jobs in high unemployment areas and increasing it in low unemployment areas. According to this view, the persistence in unemployment is primarily caused by a weak migration response and that the solution to the North-South divide is policies to increase migration rates. But in fact, the migration response in the UK is quite strong -Figure 2 in the Case for Support shows that areas with a poorly performing labour market in 1981 had significantly lower subsequent population growth than areas with relatively low unemployment in 1981. Putting these two pieces of information based on Figures 1 and 2 together makes it clear that migration is failing to equalize economic opportunity across areas and we need a better understanding of why. This project aims to do just that. First, it may be that migration alters the mix of the population in the area moved out of and not in a way that improves the economic prospects of those who are left behind. For example, it may be that more educated individuals are more mobile geographically so that migration from deprived areas acts to depress the skill base there. Our project will use Understanding Society, its predecessor (the British Household Panel Survey) and the Birth Cohort Studies to investigate how individual migration decisions respond to economic opportunity and how this responsiveness varies across different types of individuals. Using the Birth Cohort Studies with their very detailed information on both educational attainment and on non-cognitive skills, we will be able to provide much better evidence of the types of people who move in response to economic opportunity e.g. are more 'dynamic' individuals more mobile as is sometimes claimed? Secondly, it may be that whilst individuals facing economic hardship are more likely to move out of an area, they may nevertheless be compelled to return to the support of their wider family who may live in an area with no greater economic opportunity than the one they moved out of. Using our data sets one can also investigate the destinations of those who move because of economic shocks. Finally, the project will also help us to understand the channels by which economic opportunity affects migration decisions. Much discussion assumes it is directly through the labour market. But it is possible that economic shocks to an area cause a deterioration in non-economic aspects of the neighbourhood e.g. because of a rise in crime or a fall in the level of amenities offered. Using the reasons for moving and questions about satisfaction with neighbourhood in Understanding Society and the BHPS the project will disentangle the economic and non-economic channels. The project will lead to academic research papers to publish in leading peer-reviewed journals. But we also hope to influence the debate around regional policy and how regional inequalities can be reduced. We will write accessible summaries for more popular outlets such as the CEP's Centrepiece magazine and the LSE Public Policy blogs. We will work with our non-academic partners to disseminate the research widely across the country. We will engage with stakeholders through our partners Manchester New Economy and RBS and use the conduit of the What Works Centre, (a partnership between the LSE, government departments, ARUP and the Centre for Cities) as a vehicle for disemmination.

The Covid-19 pandemic together with the unprecedented and radical economic policy response on the part of government has resulted in severe disruption to consumer finances and small business finances. There is an urgent and timely need to evaluate the extent of disruption and the effectiveness of recent policy innovations. This project will use a new and unique set of real-time, high frequency data available to evalute these far faster can be achieved with traditional ONS data sources. The project involves the creation of a new real-time economic characterisation of consumer and firm behaviour from mass transaction data. Specifically, the work will evaluate impact on consumer finances (reduced incomes, non-payment of debts, patterns of saving and expenditure) and small business finances (turnover and business continuity). The research will be co-produced with four organisations. First, working with the Financial Conduct Authority, the regulator of the consumer financial sector in the UK, to evaluate the impact on consumer indebtedness and evaluate the FCA's policy response, the Consumer Credit (Temporary Covid-19 Support Measures) Order 2020 (CCO220) and the 3 month mortgage forbearnce scheme. Second, working with the National Employee Savings Trust, the largest provider of pensions to low income workers in the UK, to understand the effects on incomes and short-term and long-term saving behaviour. Third, working with the UK's largest financial aggregator app, Moneydashboard, to model the impact of 'lockdown' measures on consumer spending and business survival across sectors. Fourth, working with Natwest to evaluate the impact of the government's Coronavirus Business Interruption Loan Scheme (CBILS). Findings will be presented to policymaker sponsors the researchers will continue to work with policymakers in real-time policy design.

Cumulative Revelations in Personal Data takes a multidisciplinary approach to investigating how small, apparently innocuous pieces of employees' personal information, which are generated through interactions with/in networked systems over time, collectively pose significant yet unanticipated risk to personal reputation and employers' operational security. Such cumulative revelations come from personal data that are shared intentionally by an individual, from data shared about an individual by others, from recognition software that identifies and tags people and places automatically, and from common cross-authentication practices that favour convenience over security (e.g. signing into AirBnB via Facebook). Brought together, these data can provide unintended insights to others into (for example) an individual's personal habits, work patterns, personality, emotion, and social influence. Collectively these data thus have the potential to create adverse consequences for that individual (e.g. through reputational damage), their employer (e.g. by creating opportunities for cybercrime), and even for national security. The research brings together multidisciplinary expertise in Socio-Digital Interaction, Co-design, Interactive Information Retrieval, and Computational Legal Theory, all working in collaboration with a key industry partner, the Royal Bank of Scotland, which employs more than 92,000 staff across 12 national, international and private banks and for which security concerns are paramount, as well as UK Government security agencies, via the Government Office for Science and the Centre for Research and Evidence on Security Threats. The research will examine the potential adverse revelations delivered by an individual employee's holistic digital footprint through the development of a prototype software tool that maps out a portrait of a user's digital footprint and reflects it back to them. This tool will enable individuals to understand the cumulative nature of their personal data, and better comprehend the associated vulnerabilities and risks. Responding to employers' concerns over organisational security risks created by cumulative revelations of their employees' data, the research will also identify conflicts and ambiguities in security service design and implementation when the motivations and actions of individual employees are balanced against organisational security philosophy, enabling mitigation against the attendant risks, issues and consequences of cumulative revelations from organisational and individual perspectives.