Exploring responsible applications of deep learning for consumer credit risk assessment

Aim
To explore how to apply deep neural networks for consumer credit risk assessment in a responsible manner.

Research Questions:
Can we benefit from using deep learning as a traditional tool for credit risk assessment?

How can we design an interpretable deep neural network algorithm for responsible decision making in the lending sector?

Overview and Context:
With an increased demand for credit cards and other loans, lenders such as banks are faced with the challenge of effectively measuring the risk of lending to borrowers. The financial industry is continuously researching efforts to make

Constructing machine learning credit scoring models to assess consumer credit risk automatically is a typical approach banks use to tackle the issue. In recent years, there has been a widespread adoption of deep neural network models in many application areas as object recognition, natural language processing and pose estimation. However, there has been minimal attention given to deep neural networks in the lending sector. The reason being their use in decision making systems such as credit scoring raises questions of trust, accountabilty and fairness. The focus of this research is to explore how deep neural network models can be used to make lending decisions in a transparent way that promotes trust and ensures responsible use of the algorithm in the credit industry.

We will collaborate with over 40 partners drawn from across FMCG and Food; Creative Industries; Health and Wellbeing; Smart Mobility; Finance; Enabling technologies; and Policy, Law and Society. These will benefit from engagement with our CDT through the following established mechanisms:

- Training multi-disciplinary leaders. Our partners will benefit from being able to recruit highly skilled individuals who are able to work across technologies, methods and sectors and in multi-disciplinary teams. We will deliver at least 65 skilled PhD graduates into the Digital Economy.

- Internships. Each Horizon student undertakes at least one industry internship or exchange at an external partner. These internships have a benefit to the student in developing their appreciation of the relevance of their PhD to the external societal and industrial context, and have a benefit to the external partner through engagement with our students and their multidisciplinary skill sets combined with an ability to help innovate new ideas and approaches with minimal long-term risk. Internships are a compulsory part of our programme, taking place in the summer of the first year. We will deliver at least 65 internships with partners.

- Industry-led challenge projects. Each student participates in an industry-led group project in their second year. Our partners benefit from being able to commission focused research projects to help them answer a challenge that they could not normally fund from their core resources. We will deliver at least 15 such projects (3 a year) throughout the lifetime of the CDT.

- Industry-relevant PhD projects. Each student delivers a PhD thesis project in collaboration with at least one external partner who benefits from being able to engage in longer-term and deeper research that they would not normally be able to undertake, especially for those who do not have their own dedicated R&D labs. We will deliver at least 65 such PhDs over the lifetime of this CDT renewal.

- Public engagement. All students receive training in public engagement and learn to communicate their findings through press releases, media coverage.

This proposal introduces two new impact channels in order to further the impact of our students' work and help widen our network of partners.

- The Horizon Impact Fund. Final year students can apply for support to undertake short impact projects. This benefits industry partners, public and third sector partners, academic partners and the wider public benefit from targeted activities that deepen the impact of individual students' PhD work. This will support activities such as developing plans for spin-outs and commercialization; establishing an IP position; preparing and documenting open-source software or datasets; and developing tourable public experiences.

- ORBIT as an impact partner for RRI. Students will embed findings and methods for Responsible Research Innovation into the national training programme that is delivered by ORBIT, the Observatory for Responsible Research and Innovation in ICT (www.orbit-rri.org). Through our direct partnership with ORBIT all Horizon CDT students will be encouraged to write up their experience of RRI as contributions to ORBIT so as to ensure that their PhD research will not only gain visibility but also inform future RRI training and education. PhD projects that are predominantly in the area of RRI are expected to contribute to new training modules, online tools or other ORBIT services.