This proposal addresses the Digital Economy and Financial Services research challenge by improving Small and Medium Enterprises' (SMEs) access to credit. The issue is that information in and around credit decision-making is generally limited to company and individual track record. It ignores the position and importance of a company in its business ecosystem. Credit lending decisions by finance providers therefore have unseen network effects and limit growth in unseen ways. To address this issue, SCRIBE uses emerging semantic technologies to provide disruptive innovation in the form of more accurate real-time credit risk assessment based on a dynamic understanding of the position and value of a company in relation to its business ecosystem (or network). The scientific contributions of SCRIBE are twofold. First, the project fuses the state-of-the-art in (social) network analytics and credit assessment techniques to develop its ecosystem-based understanding (and associated marketing opportunities). Second, as technical foundation, the project develops a state-of-the-art method to 'harmonise' the different conceptual models that underlie data drawn from multiple sources, preserving contextual richness in so doing. Contextual preservation is important not only for network-based decision-making, but also for audit and the legal issues considered by the project since it is relatively well-acknowledged that conventional data modelling implicitly abstracts away important aspects of context. The scientific contributions are developed and exploited via a collaborative partnership that combines understanding of credit risk and assessment at both the transaction-level (via open online accounting data and via collaboration with Lloyds) and firmographic-level (via collaboration with Creditsafe). Addressing the NEMODE ethos, the project maintains a focus on impact via the development of novel information products and applications (via collaboration with Level Business).

This proposal addresses the Digital Economy and Financial Services research challenge by improving Small and Medium Enterprises' (SMEs) access to credit. The issue is that information in and around credit decision-making is generally limited to company and individual track record. It ignores the position and importance of a company in its business ecosystem. Credit lending decisions by finance providers therefore have unseen network effects and limit growth in unseen ways. To address this issue, SCRIBE uses emerging semantic technologies to provide disruptive innovation in the form of more accurate real-time credit risk assessment based on a dynamic understanding of the position and value of a company in relation to its business ecosystem (or network). The scientific contributions of SCRIBE are twofold. First, the project fuses the state-of-the-art in (social) network analytics and credit assessment techniques to develop its ecosystem-based understanding (and associated marketing opportunities). Second, as technical foundation, the project develops a state-of-the-art method to 'harmonise' the different conceptual models that underlie data drawn from multiple sources, preserving contextual richness in so doing. Contextual preservation is important not only for network-based decision-making, but also for audit and the legal issues considered by the project since it is relatively well-acknowledged that conventional data modelling implicitly abstracts away important aspects of context. The scientific contributions are developed and exploited via a collaborative partnership that combines understanding of credit risk and assessment at both the transaction-level (via open online accounting data and via collaboration with Lloyds) and firmographic-level (via collaboration with Creditsafe). Addressing the NEMODE ethos, the project maintains a focus on impact via the development of novel information products and applications (via collaboration with Level Business).

The achievements of modern research and their rapid progress from theory to application are increasingly underpinned by computation. Computational approaches are often hailed as a new third pillar of science - in addition to empirical and theoretical work. While its breadth makes computation almost as ubiquitous as mathematics as a key tool in science and engineering, it is a much younger discipline and stands to benefit enormously from building increased capacity and increased efforts towards integration, standardization, and professionalism. The development of new ideas and techniques in computing is extremely rapid, the progress enabled by these breakthroughs is enormous, and their impact on society is substantial: modern technologies ranging from the Airbus 380, MRI scans and smartphone CPUs could not have been developed without computer simulation; progress on major scientific questions from climate change to astronomy are driven by the results from computational models; major investment decisions are underwritten by computational modelling. Furthermore, simulation modelling is emerging as a key tool within domains experiencing a data revolution such as biomedicine and finance. This progress has been enabled through the rapid increase of computational power, and was based in the past on an increased rate at which computing instructions in the processor can be carried out. However, this clock rate cannot be increased much further and in recent computational architectures (such as GPU, Intel Phi) additional computational power is now provided through having (of the order of) hundreds of computational cores in the same unit. This opens up potential for new order of magnitude performance improvements but requires additional specialist training in parallel programming and computational methods to be able to tap into and exploit this opportunity. Computational advances are enabled by new hardware, and innovations in algorithms, numerical methods and simulation techniques, and application of best practice in scientific computational modelling. The most effective progress and highest impact can be obtained by combining, linking and simultaneously exploiting step changes in hardware, software, methods and skills. However, good computational science training is scarce, especially at post-graduate level. The Centre for Doctoral Training in Next Generation Computational Modelling will develop 55+ graduate students to address this skills gap. Trained as future leaders in Computational Modelling, they will form the core of a community of computational modellers crossing disciplinary boundaries, constantly working to transfer the latest computational advances to related fields. By tackling cutting-edge research from fields such as Computational Engineering, Advanced Materials, Autonomous Systems and Health, whilst communicating their advances and working together with a world-leading group of academic and industrial computational modellers, the students will be perfectly equipped to drive advanced computing over the coming decades.

AP4L is a 3-year program of interdisciplinary research, centring on the online privacy & vulnerability challenges that people face when going through major life transitions. Our central goal is to develop privacy-by-design technologies to protect & empower people during these transitions. Our work is driven by a narrative that will be familiar to most people. Life often "just happens", leading people to overlook their core privacy and online safety needs. For instance, somebody undergoing cancer treatment may be less likely to finesse their privacy setting on social media when discussing the topic. Similarly, an individual undergoing gender transition may be unaware of how their online activities in the past may shape the treatment into the future. This project will build the scientific and theoretical foundations to explore these challenges, as well as design and evaluate three core innovations that will address the identified challenges. AP4L will introduce a step-change, making online safety and privacy as painless and seamless as possible during life transitions To ensure a breadth of understanding, we will apply these concepts to four very different transitions through a series of carefully designed co-creation activities, devised as part of a stakeholder workshop held in Oct'21. These are relationship breakdowns; LBGT+ transitions or transitioning gender; entering/ leaving employment in the Armed Forces; and developing a serious illness or becoming terminally ill. Such transitions can significantly change privacy considerations in unanticipated or counter-intuitive ways. For example, previously enabled location-sharing with a partner may lead to stalking after a breakup; 'coming out' may need careful management across diverse audiences (e.g - friends, grandparents) on social media. We will study these transitions, following a creative security approach, bringing together interdisciplinary expertise in Computer Science, Law, Business, Psychology and Criminology. We will systematise this knowledge, and develop fundamental models of the nature of transitions and their interplay with online lives. These models will inform the development of a suite of technologies and solutions that will help people navigate significant life transitions through adaptive, personalised privacy-enhanced interventions that meet the needs of each individual and bolster their resilience, autonomy, competence and connection. The suite will comprise: (1) "Risk Playgrounds", which will build resilience by helping users to explore potentially risky interactions of life transitions with privacy settings across their digital footprint in safe ways (2) "Transition Guardians", which will provide real-time protection for users during life transitions. (3) "Security Bubbles", which will promote connection by bringing people together who can help each other (or who need to work together) during one person's life transition, whilst providing additional guarantees to safeguard everyone involved. In achieving this vision, and as evidenced by £686K of in-kind contributions, we will work with 26 core partners spanning legal enforcement agencies (e.g., Surrey Police), tech companies (e.g., Facebook, IBM), support networks (e.g., LGBT Foundation, Revenge Porn Helpline) and associated organisations (e.g., Ofcom, Mastercard, BBC). Impact will be delivered through various activities including a specially commissioned BBC series on online life transitions to share knowledge with the public; use of the outputs of our projects by companies & social platforms (e.g., by incorporating into their products, & by designing their products to take into consideration the findings of our project) & targeted workshops to enable knowledge exchange with partners & stakeholders.

This Digital Economy (DE) Network Plus will deliver a vibrant community that will position the UK as the internationally leading research hub for Digitally Enhanced Advanced Services. Rather than focus on the product or service that is delivered DEAS focuses on how the product or service is used. This is a major change in how firms earn money and is being enabled by transformative digital technologies that allows for example, payment per use or availability or outcome. The impact of these changes is in firm productivity. The traditional focus of productivity (outputs/inputs) is on internal efficiency. However, digital technologies can also transform the value of the output (payment for use, availability or outcome). Haldane (Chief Economist of the Bank of England) in his recent report on productivity puzzle (essentially stagnant growth since the financial crash) argues that despite the advent of the digital age and their adoption by some leading companies there is a very long tail of poorly productive firms across all sectors. He calls for the development of, for example, online tools that will speed the process of technological diffusion to the long tail. The development of the underpinning digital technologies for the purposes of developing DEAS is the key research challenge adopted by this Network+.