I’d like to learn more about Newcastle!


3 ways your business can improve customers' trust in its financial services

By Dr Karen Elliott
Financial services apps illustration

We all need to be able to trust the financial services we use. But in the age of digital banking and financial technologies or "FinTech", understanding how we build trustworthy financial services is a topic of public concern.

In this blog we share findings from our FinTrust project and highlight three ways your business can improve trust in its financial services, as well as some bonus tips.

Public trust and digital banking

Digital banking can pose challenges for citizens, raising vulnerability concerns around trust in banking institutions.

Branch closures, accessibility of online services, and a lack of digital literacy all play a role in the inclusion and participation of people in the digital society.

Some of the most vulnerable members of our society are marginalised by advances in technology. This can result in customers and users questioning an organisation or system’s honesty, reliability, or safety.

Never has it been more important for financial services to be at the forefront of helping customers manage their finances through responsible and trusted services and technology. The cost-of-living crisis and the need to implement the new Consumer Duty regulation bring financial services into sharp focus.

How to improve trust in your business’s financial services

1. Understand your customers’ vulnerability status

Advances in technology can exclude vulnerable members of our society, such as people with dementia or low digital and financial literacy.

The Financial Conduct Authority's research exploring the drivers of vulnerability found that approximately 53% of the UK’s population sit under the following drivers:

  • health
  • life events
  • resilience
  • capabilities

To identify your own customer vulnerability status, examine your records against the four drivers to evaluate whether some of your customers may fall under the categories.

For instance, when was the last time you spoke to customers who have low funds in their accounts or have let you know that they have prior financial issues? How do your current policies support their needs?

This is one of the principles of the Corporate Digital Responsibility (CDR) mechanisms — placing purpose and trust as your key activities alongside providing equal access and support across your customer supply chain.

Bonus tip:

  • Create a strategy to check and update the vulnerability status of your customers on a regular basis, as part of your CDR practices.

2. Consider designing a chatbot which is less human

Chatbots are an increasing presence in online services. They are sometimes equipped to mimic human social rules, expectations, and norms - decreasing the necessity for human-to-human interaction. However, your business may want to consider designing a chatbot which is less human.

The FinTrust Team compared two hypothetical chatbots: Emma and XRO23. Emma had more human-like features, whereas XR023 was more mechanical, functional, and impersonal.

Our study found that people were more willing to disclose sensitive financial information and behaviours to XRO23. This suggests that socio-emotional features in chatbots designed exclusively for automated financial support have little advantage in FinTech, albeit more research is required to study this emergent field.

Bonus tips:

  • Do you need a chatbot or can you support with other customer service techniques?
  • Have you asked your customers what they prefer? Your specific audience might have an opinion regarding the type of chatbot they would like to see.
  • Hybrid chatbots which give the opportunity to chat with a human may be preferred, can you include this as an option?

3. Understand how your customers perceive trust vs trustworthy technology

How we talk about trust is subject to assumptions on what “trust” means. Trust is understood differently in the social and systems engineering contexts.

In the social sense, "trust" is constructed and therefore peoples’ meaning, perception or belief that an organisation or system is honest, reliable, or safe, are unclear — each of us will form our interpretation of trust in slightly different ways.

For engineers, trustworthy digital technology, such as Machine Learning or Artificial Intelligence, is related to normative statements on the qualities of the technology, and involves the consideration of Fairness, Explainability, Auditability, and Safety (FEAS).

Trustworthiness typically requires ethical approaches, while trust is a response to the technologies developed or the processes through which they were developed.

Unless you take the time to understand how your customers or users perceive trust, it will be difficult to measure trust and assess how to build trustworthy technologies.

Bonus tips:

  • Think about gathering customer feedback on trust
  • Co-create technological solutions around ethics-by-design to avoid unintended consequences of your applications i.e. creating more exclusion for vulnerable customers.

Next steps for your business

Start to think about responsible innovation across your supply chain. You can use the toolkit to incorporate ethics-by-design principles for systems engineering. You should ensure you're assisting vulnerable consumers who also struggle with digital technologies.

Examine how your organisation uses data and digital technologies across all job families. Shift focus to generating profit with a purpose of inclusivity. This leads to evidence-based responsible innovation and aligns with broader ESG and UNSDG Directives – universal metrics that financial service providers must meet.

You might also like...

About the FinTrust project and the Trust Engineering Toolkit

The FinTrust project explores the role of machine learning in banking. It particularly looks at machine learning within the context of automated lending decisions and whether these lead to bias and financial exclusion. FinTech (financial technology) is one of the major growth industries in the UK with approximately $9bn investment in 2022.

This project is the first in a series of financial services/Fintech research projects led by former Newcastle University Professor and project Principal Investigator Professor Aad van Moorsel and Dr Karen Elliott.

As part of the research, the Trust Engineering Toolkit translates theoretical and practical insights and state-of-the-art techniques, to help businesses understand trust and trustworthy systems within automated financial services.

About the author

Dr Karen Elliott is the Co-Investigator of the FinTrust Project. Karen is a Senior Lecturer in Enterprise/Innovation (FinTech) at Newcastle University Business School, and was voted as #Standout 35 Women in FinTech Powerlist awarded by Innovate Finance, reflecting her work on the governance of FinTech within the Digital Economy, Digital Society and Responsible Innovation.

Karen is also an Ambassador for the Digital Poverty Alliance, a member of the Prime Minister's Challenge Group for Dementia as Digital Inclusion Adviser, and a member of the Corporate Digital Responsibility group.

New call-to-action

Tags: Data, Working with Business, Machine Learning, FinTech