SCRIBE: Semantic Credit Risk Assessment of Business Ecosystems
Lead Research Organisation:
Brunel University London
Department Name: Computer Science
Abstract
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).
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).
Planned Impact
The scale of impact goes from individual companies, to networks of companies (eco-systems), networks of ecosystems, the National Economy and policy-making. In the short-term (and the 3-year duration of the project) we expect that our research will impact initially on the commercial partners involved. We foresee that the initial experimentation of the Information Product, the network-based credit model and the semantic integration hub will influence our commercial partners' businesses (e.g., products/services designed around more accurate and integrated data, credit decisions based on eco-system models, etc.). In the medium term (5-10 years) the impact will be on financial institutions and credit rating agencies, specifically in the way businesses are assessed and money is loaned. Over the same timeframe we foresee the economic model proposed here for credit to inspire other researchers who will adopt this theory to explore its application to other economic problems. In the long term (10-25 years) we envision that the deliverables of this project will have affected and rippled throughout the U.K. Economy and affect government in their policy-making by basing their economic policies and modelling also in the network effects that business eco-systems produce.
More traditionally, we will utilise academic outlets (conferences and journals) - particularly those where there is industry crossover such as the Semantic Technology Conference (SemTech), International Data Protection and Privacy Commissioners' conference and CEE Credit Risk Management. We will engage actively within the EPSRC NEMODE Network in order to present our research and to seek collaboration and support with other investigators funded by the programme. Engagement here will include: (a) organisation of and participation in NEMODE community meetings; (b) workshops at Brunel University to which NEMODE researchers will be invited to present research outcomes and discuss future progress and collaborations.
More traditionally, we will utilise academic outlets (conferences and journals) - particularly those where there is industry crossover such as the Semantic Technology Conference (SemTech), International Data Protection and Privacy Commissioners' conference and CEE Credit Risk Management. We will engage actively within the EPSRC NEMODE Network in order to present our research and to seek collaboration and support with other investigators funded by the programme. Engagement here will include: (a) organisation of and participation in NEMODE community meetings; (b) workshops at Brunel University to which NEMODE researchers will be invited to present research outcomes and discuss future progress and collaborations.
Organisations
- Brunel University London (Lead Research Organisation)
- Economic and Social Research Council (Co-funder)
- Creditsafe (Collaboration)
- Lloyds Bank (Collaboration)
- Lloyds Banking Group (United Kingdom) (Project Partner)
- Level Business Limited (Project Partner)
- Creditsafe Business Solutions Limited (Project Partner)
Publications
Jane Marriott
(2016)
Credit Risk Analysis using Big and Open Data meets Privacy: Only One Winner?
Lycett M
(2016)
4D-SETL - A Semantic Data Integration Framework
Marriott J
(2017)
To score and to protect? Big data (and privacy) meet SME credit risk in the UK
in International Data Privacy Law
Moscone F
(2015)
Robust estimation under error cross section dependence
in Economics Letters
Moscone F
(2017)
Sparse estimation of huge networks with a block-wise structure
in The Econometrics Journal
Tosetti E
(2019)
A Computationally Efficient Correlated Mixed Probit Model for Credit Risk Inference
in Journal of the Royal Statistical Society Series C: Applied Statistics
Vinciotti V
(2019)
The Effect of Interfirm Financial Transactions on the Credit Risk of Small and Medium-Sized Enterprises
in Journal of the Royal Statistical Society Series A: Statistics in Society
Description | The project developed the following. First, a way to semi-automatically extract information from existing company databases and transform it to provide richer and more detailed knowledge. Second, a spatial way to estimate company networks based around their geographical location and industry type. Third, an improved method of estimating networks and applying methods to data provided by our collaborators. Last, a number of analytical techniques that can be applied to the transaction data we have to develop insight. A report and demonstrator have been produced for our collaborating partner, covering a number of use cases. |
Exploitation Route | Discussion with one of our collaborators re pursuing the work further commercially did not lead to concrete outcomes. |
Sectors | Digital/Communication/Information Technologies (including Software) Financial Services and Management Consultancy Retail Transport |
Title | SCRIBE 4D-SETL |
Description | As part of the semantic aspect of the SCRIBE project, we have developed and applied a 4D-Semantic Extract Transform Load (4D-SETL) framework. 4D-SETL is employed within the SCRIBE project to integrate a number of large scale datasets via a foundational ontology and to persist the resultant ontology within a prototype warehouse based on a graph database. We see the advantages of the approach as: (a) The ability to combine foundational, domain and instance level ontological objects within a single coherent system; and (b) providing a clear means of establishing and maintaining the identity of domain objects as their constituent spatio-temporal parts evolve over time (enabling process and static data to be combined within a single model). |
Type Of Material | Data handling & control |
Provided To Others? | No |
Impact | A conference paper '4D-SETL A Semantic Data Integration Framework' (see publications). |
Description | SCRIBE Creditsafe |
Organisation | Creditsafe |
Country | United Kingdom |
Sector | Private |
PI Contribution | The development of network-based models of credit risk/probability of default. For this collaboration, models include spatial and other such estimations as transactional data is only available in limited form. |
Collaborator Contribution | Provision of firmographic data (e.g., company registration data, SIC codes, full accounts, late payment information, county court judgements etc.) |
Impact | Publication on estimation using spatial dependence. |
Start Year | 2015 |
Description | SCRIBE Lloyds |
Organisation | Lloyds Bank |
Country | United Kingdom |
Sector | Private |
PI Contribution | The development of novel business models, new product/service opportunities etc., based on an understanding of (transactional) client networks. |
Collaborator Contribution | Provision of sample banking transaction data. |
Impact | N/a |
Start Year | 2016 |
Description | 4th International Workshop on Ontologies and Conceptual Modelling, Annecy, France, 6th July 2016 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Workshop aimed at comparing foundational ontologies and their use to model the business domain. The foundational ontology used in both the EMBO and SCRIBE EPSRC projects was presented along with the related domain models. |
Year(s) Of Engagement Activity | 2016 |
URL | http://www.mis.ugent.be/ontocom2016/ |
Description | Credit risk model with network effects for large number of companies |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Other audiences |
Results and Impact | It was a formal presentation of a paper at University of Essex at the Institute of Big Data |
Year(s) Of Engagement Activity | 2017 |
URL | https://www.essex.ac.uk/iads/news_and_seminars/seminarDetail.aspx?e_id=11528 |
Description | Politics of Big Data Conference |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | 'Conference' comprising a series of four panel discussions on the politics, political impact and impact on politics of Big Data. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.kcl.ac.uk/artshums/depts/ddh/eventrecords/2015/bigdata-conference.aspx |
Description | SCRIBE Credit Risk Ontology Workshop (CROW) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | The CROW workshop sought shed light on the ontological nature of credit risk by bringing together domain experts from the financial industry with researchers in formal ontology. Approximately 25 people attended the workshop from financial organisations such as Lloyds Banking, Credit Suisse, Equifax. The workshop sparked interest and questions in a network-based understanding of credit risk and the use of ontology as a way of enhancing data semantics in risk models. Concrete outcomes come in the form of full-project participation by Lloyds and the development of an additional relationship with Equifax - Non-Disclosure Agreements have been signed with both. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.scribe.org.uk/event/credit-risk-ontology-workshop-crow/ |
Description | SCRIBE Networks and Estimation of Non-Linear Models with Spatial Dependence |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | The aim of the event was to discuss network-based approaches to identify, measure, and model interdependence among economic agents. The primary audience was doctoral students, researchers and academics alike - an international keynote was provided on the estimation of nonlinear models with spatial dependence. There was a good degree of discussion during the event and, as a concrete outcome, a working relationship (on the SCRIBE project) was developed with Professor Daniel McMillen of the University of Illinois. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.scribe.org.uk/event/workshop-on-big-data-networks-and-the-estimation-of-nonlinear-models-... |
Description | Workshop on Big Data and Networks |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Here is the flyer with the programme http://www.crisp-org.it/public/uploads/2015/07/FLYER_POST_19lug.pdf Professor Daniel McMillen (University of Illinois): Nonparametric and GMM Methods for Estimating Spatial Probit Models. An application in the health care sector Dr Sergio de Cesare (Brunel University London): Semantic Re-engineering of Data Prof Giorgio Vittadini (Brunel University London): Big data and administrative data The event has been introduced by Professor Franecsco Moscone from Brunel University of London, who has discussed some key aspects of the project Semantic Credit Risk Assessment of Business Ecosystems (http://www.scribe.org.uk/). Dr De Cesare has talked in details about the state of the art of SCRIBE. Prof McMillen has shown an application of the most advanced techniques in spatial econometrics to study the interaction of economic agents. This event has proved to be a unique opportunity to learn about big data and estimation of nonlinear models with spatial dependence. |
Year(s) Of Engagement Activity | 2016 |
URL | http://www.scribe.org.uk/ |