Creating fairer financial futures: A spotlight on FRIL research 

Technology-enabled advice, Regulation and the Advice Gap: 10 minute Insight from  FRIL Research. 10 Questions with Chuks Otioma, Research Associate, Adam Smith Business School

As financial services explore new ways to close the advice gap, technology enabled advice and guidance models are increasingly part of the conversation – but what do they really mean for consumers, firms and regulation? 

As part of the Financial Regulation Innovation Lab (FRIL), researchers from the University of Glasgow and University of Strathclyde are working alongside industry, fintechs and regulators to examine how innovation can be deployed responsibly in financial services. 

In this conversation, Chuks Otioma, Research Associate, reflects on his research into these digitally- enabled advice models: what they are, why they matter, and how they sit within the Advice Guidance Boundary Review. 

1. Chuks, let’s start with you first of all – what drew you to this field of research? 

Before moving into academia, I worked in industry, in telecommunications. During my PhD, I looked at the links between digital capabilities, innovation and economic performance, and the role of entrepreneurs and innovators in leveraging digital advances; work that now informs my research into AI in financial services. I was particularly interested in how firms reorganise themselves, their processes, structures and activities in order to draw value from digital technologies. 

At that stage, my work wasn’t focused on financial services specifically. It was broader, looking at firms across sectors and how they approach digital transformation. What I’m doing now is a natural progression of that work, but with a much sharper focus on financial services and the challenges firms face in deploying technologies like AI. 

2. OK, let’s explore your research Chuks. First of all can you explain to us what  “technology-enabled advice and guidance models” actually are? 

At a basic level,  the term refers to digitally enabled advice. It can be relatively simple, or more advanced, using AI to construct and refine portfolios. 

What’s important is the way technology can help streamline advice around individual needs. But this also raises important considerations. You have to think carefully about the data being used, the potential for data breaches, and whether consumers genuinely understand the advice they’re receiving. 

There are also different operating models. Some are largely consumer-led, with minimal human interaction. Others are more professional-led, where investment or wealth managers use automated tools to manage portfolios on behalf of clients. Each model raises different questions around responsibility and duty of care. 

3. The Advice Guidance Boundary Review aims to ensure that financial help is clearer, fairer and available to far more people. How do these technology-enabled models play a part here?

Some forms of digital advice function as guidance, pointing consumers towards information or helping them explore options. Others go further, making recommendations or even decisions on a client’s behalf, which brings them firmly into the realm of regulated advice. 

That distinction matters, particularly as systems become more advanced. The more decision-making is delegated to automated systems, the more important strong compliance, governance and accountability become. 

4. Can these models really help address the financial advice gap? 

There is evidence that automated advice has already improved access and inclusion, particularly among younger people and those who might not otherwise engage with traditional investment services.

Because these systems can draw on rich data and integrate information from multiple sources, they have real potential to support people who currently lack access to advice. 

What’s especially interesting is the way some platforms are beginning to connect users to independent financial advisers, recognising that investment decisions don’t exist in isolation. Financial wellbeing also involves literacy, planning and understanding long-term goals. 

“These systems have real potential to support people who currently lack access to financial advice.”

5. What risks need to be managed as technology-enabled advice and guidance becomes more common? 

In our research, we look at several dimensions. There’s the operating model, and how responsibility is shared between consumers, professionals and platforms. There’s financial risk, including market volatility, trend-chasing and over-concentration. 

We also examine data practices, including how platforms are designed, who has access to data, and how data is shared across third parties and jurisdictions. In many cases, the developer of the system is not the same as the organisation managing it, which raises important governance questions. 

“When advice becomes more automated, firms need to be clear about who is responsible when things go wrong.”

6. What has surprised you most in your research?

One of the most striking findings is the level of consumer misunderstanding. Products are often designed on the assumption that firms understand their users, but in practice there can be significant misalignment between innovation and user understanding. 

This isn’t necessarily about consumers lacking capability. It’s often about how products are designed, communicated and framed. That’s a critical lesson for firms designing these products. 

7. What big questions does this raise for firms and for the industry?

One of the big questions is around responsibility and accountability, particularly as more decision-making is delegated to automated systems. When advice becomes more automated, firms need to be clear about who is responsible when things go wrong. 

Beyond that, these developments also raise important questions about how firms organise themselves. Automated advice reshapes how services are delivered, which has implications for workforce skills and training. Technical teams increasingly need some understanding of finance, while those working in finance or customer support need a basic understanding of how AI-based systems work. 

There are also strategic questions around how these systems are developed and deployed. Firms need to decide whether to build solutions in-house or rely on third-party providers, and how external systems integrate with existing or legacy technologies. These choices affect how services are scaled and managed over time. 

Taken together, these are organisational challenges as much as they are technological ones, and they shape how firms deliver automated advice in practice. 

8. With all this in mind, what future are you trying to help shape through this research? 

For me, the most important thing is societal relevance. I’m interested in research that informs policy-making and speaks directly to real-world challenges. 

FRIL is quite unique in that sense. The challenges we work on are industry-led. You have problem owners defining the issues they face, fintechs developing solutions, and researchers contributing evidence and insight that can help shape both practice and regulation. It’s impact-oriented research, and that’s very fulfilling. 

Ultimately, the future I want to contribute to is one where research doesn’t sit in isolation, but actively helps address the problems faced by industry, policymakers and society more broadly. 

9. Can you share some examples of wider real-world challenges you’ve been working on? 

One example is our work looking at consumer complaints within financial services. By analysing the types of complaints that are escalated to the Financial Ombudsman Service, and how providers respond to them, we can better understand where things go wrong.

If we understand these friction points, there’s an opportunity to co-develop financial products differently, reducing the likelihood of harm or escalation in the first place. 

In our work on automated advice, we’ve also explored how providers can embed responsible practices into their models. That includes linking clients to green or sustainable investment opportunities, and aligning portfolios not just with financial returns, but with broader social and environmental goals. 

“Automated advice reshapes how services are delivered, with implications for workforce skills, training and how firms organise themselves.”

10. Finally, what feels special about doing this research here, in Scotland, and within the FRIL ecosystem? 

What stands out for me is the research culture and the ecosystem we’re working within. The University of Glasgow, and the Adam Smith Business School, have a strong international research culture, and we work very closely with colleagues at the University of Strathclyde and with industry partners. 

Beyond the universities, there’s something distinctive about how this work comes together in practice. Through FRIL, you have financial services providers, fintech developers, regulators and researchers working together on a daily basis. It’s what we often describe in theory as an “ecosystem”, but here it’s very real. 

That makes it a unique environment for doing this kind of research, not in isolation, but embedded in the real challenges facing industry and society. 

Explaining the terminology 

• Technology-enabled advice: A digital tool that uses information about a person to help guide or automate investment decisions based on their individual needs. 
• The Advice Guidance Boundary Review. Just what does it all mean?  
• Advice: A regulated service where a financial adviser looks at your full financial situation and gives you a personalised recommendation. 
• Guidance: Support that points you in the right direction based on limited information you share, without telling you exactly what to do. 
• Boundary: The line that separates advice from guidance, defining how much information is needed and what a firm can or can’t recommend. 
• Review: The FCA’s process of consulting industry and consumers, and government to create clear new rules that will shape how these services work in future. 

What next?  

Interested in the research generated by FRIL? Then check out our White Papers across a range of subjects. 

For more detail on this topic, see Chuk’s white paper.

If you’re interested in the work of FRIL more generally and would like to contact a member of the team email FRIL@fintechscotland.com.

About FRIL

The project is part of the Glasgow City Region Innovation Accelerator programme, funded through Innovate UK on behalf of UK Research and Innovation. The Innovation Accelerator programme is investing £130 million in 26 transformative R&D projects to accelerate the growth of three high-potential innovation clusters, including the Glasgow City Region.

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