SCRIBE addresses the Digital Economy and Financial Services research challenge to improve Small and Medium Enterprises’ (SMEs) access to credit. Our observation 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 observation, 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. This richness is important for both network-based decision-making and for audit and the legal issues considered by the project.
The scientific contributions are developed and exploited via industry collaborations that combine understanding of credit risk and assessment at both the transaction-level and firmographic-level. The project maintains a focus on (commercial) impact via the development of novel information products and applications.