SCRIBE: Semantic Credit Risk Assessment of Business Ecosystems

Lead Research Organisation: Brunel University
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).

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.

Publications

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De Cesare S. (2016) 4D-SETL a semantic data integration framework in ICEIS 2016 - Proceedings of the 18th International Conference on Enterprise Information Systems

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Jane Marrott (2017) To Score and to protect? Big data (and privacy) meet SME credit risk in the UK in International Data Privacy Law

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Marriott J (2017) To score and to protect? Big data (and privacy) meet SME credit risk in the UK in International Data Privacy Law

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Moscone F (2015) Robust estimation under error cross section dependence in Economics Letters

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Moscone F (2017) Sparse estimation of huge networks with a blockwise structure in The Econometrics Journal

Related Projects

Project Reference Relationship Related To Start End Award Value
EP/L021250/1 30/06/2014 27/11/2016 £676,567
EP/L021250/2 Transfer EP/L021250/1 28/11/2016 31/01/2018 £194,648
 
Description To date we have 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. We are currently working on an improved method of estimating networks and applying methods to data provided by our collaborators. Third a number of analytical techniques that can be applied to the transaction dat we have to develop insight. A report and demonstrator have been produced for our collaborating partner, covering a number of use cases.
Exploitation Route We are currently in discussion with one of our collaborators re pursuing the work further commercially.
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/