Projects

FinTrust Trust Engineering Toolkit

We all need to be able to trust the financial services we use.

But in the age of new digital banking technologies and “FinTech”, understanding how we should build trustworthy financial services is a topic of public concern. This toolkit explores such problems inherent in engineering trust into financial services, and discusses potential tools and solutions arising through new research undertaken at Newcastle University in the FinTrust project.

Digital banking can pose challenges for citizens, raising vulnerability concerns around trust in banking institutions: branch closures, accessibility of online services, and digital skills and understanding all play a role in the inclusion and participation of people in the digital society.

FinTrust investigates digitization and its impact on society. Our Trust Engineering Tool Kit translates the understanding and techniques developed through the FinTrust project into reusable methods and software tools. The articles within these pages are aimed at FinTech stakeholders, to help your business to better understand trust and trustworthy systems within the context of increasing automation of financial services.

The articles on this page can also be downloaded as a booklet:

Download booklet (PDF)

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Can blockchain technologies support vulnerable and financially excluded customers?

Things to consider:

  • Are you serving customers who meet the FCA’s vulnerability drivers?
  • Do you know which of your customers are in a vulnerable situation?
  • Do you check and update the vulnerability status of your customers?

We found that:

  • Over 53% of the UK population sit under the four FCA drivers of vulnerability: health, life events, resilience and capabilities.
  • Most technology is not built to adapt to vulnerabilities.
  • Other forms of digital identity can meet KYC (Know Your Customer) FCA regulations to drive financial inclusion, and can help meet ESG (Environmental Social Governance) and SDG (Sustainable Development Goals) UN directives.

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Chatbot Framework

| June 2020

How can we engineer trust into conversational user interfaces?

Things to consider:

  • Do you need a chatbot?
  • Have you asked your customers what they prefer?

We found that:

  • Your customers may find it easier to trust a chatbot which seems less human
  • Hybrid chatbots which give an option to chat to a human may be preferred

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How we talk about trust is subject to assumptions on what ‘trust’ means: how we understand it at a social level is not the same as trustworthiness at the systems level.

Things to consider:

  • How does your company understand human versus technical trust?
  • How do your customers or service users perceive trust?
  • How does your organisation measure trust and build trustworthy technologies?

We found that:

  • People’s trust perceptions and beliefs surrounds that an organisation or system is honest, reliable, or safe.
  • Each of us will imagine what it means to trust in slightly different ways.
  • For engineers and designers, “trustworthiness” is concerned with the “FEAS” properties of machine learning systems: Fairness, Explainability, Auditability and Safety.

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