Teaching Finance for wicked problems

Over the past two years, I have found myself looking at student work differently. Like the rest of the higher education sector, I have been teaching in a generative AI-dominated world. Essays are fluent. Arguments are polished. Technical explanations are often perfectly serviceable. But something began to feel flat. Linear. Detached. I could see correct applications of exchange rate models and hedging theory, yet I struggled to see students thinking. 

I realised that my assessment design might be part of the problem. If we ask for structured, model-based, linear responses, we should not be surprised when students produce them –whether independently or with technological assistance. 

The world we are preparing our students for is defined not by neat problems, but by what Rittel and Webber termed “wicked problems” (Rittel and Webber, 1973) such as climate instability, geopolitical fragmentation and systemic financial risk. These are issues characterised by feedback loops, unintended consequences, value conflicts and deep uncertainty. I found myself asking: are we assessing students’ ability to deal with that kind of complexity? 

A small change with significant consequences 

In my final-year undergraduate International Finance unit, I decided to re-design the coursework entirely around systems thinking. Students were required to construct a causal loop diagram analysing a live international finance issue – such as capital flight, exchange rate volatility or climate-related investment risk – and accompany it with a short analytical commentary. 

Instead of presenting a linear essay, they had to map reinforcing and balancing feedback loops, identify interdependencies, surface assumptions and explore second- and third-order effects. 

It was not an abandonment of technical finance. They still needed to understand monetary models, hedging instruments and international capital flows. But they now had to situate those tools within a dynamic system. The impact on the quality of work was immediate and visible. 

Students moved beyond describing variables to examining relationships. Hedging was no longer simply a risk management technique; it became part of a wider market dynamic that could dampen or amplify volatility. Capital inflows were not labelled good or bad; they were traced through feedback loops affecting exchange rates, inflation expectations, political stability and long-term growth. 

More strikingly, they began to identify trade-offs and distributional consequences. Who benefits from risk transfer? Who absorbs systemic shocks? What happens when many firms optimise simultaneously?  

Legitimising ambiguity 

The most unexpected change, however, was not only in the coursework submissions. It was in the classroom conversations.  

Systems thinking legitimises ambiguity. Traditional finance assessments can implicitly reward certainty: apply the correct model, derive the answer, defend the conclusion. Ambiguity can feel like weakness. Yet wicked problems are defined precisely by indeterminacy, contested values and incomplete information. 

By assessing students on the quality of their reasoning, the coherence of their feedback loops and the plausibility of their systemic explanations - rather than on a single “correct” outcome – ambiguity became intellectually respectable. I noticed students speaking differently in seminars. They were more willing to say “it depends”; more prepared to explore unintended consequences, and more comfortable acknowledging uncertainty rather than rushing to closure.  

Rediscovering student thinking in a GenAI world 

There was also something personally reassuring about this shift. When I met with students to discuss their diagrams, I could see their thinking. They would talk me through loops they had struggled to define, explain why they had categorised a feedback as reinforcing rather than balancing, or debate whether a policy intervention would stabilise or destabilise the system. 

These conversations were qualitatively different from discussing a conventional essay. They were less about polishing prose and more about grappling with ideas. In a context where colleagues often worry that generative AI obscures authentic intellectual effort, systems mapping made that thinking visible. It is difficult to outsource genuine understanding of interdependencies and dynamic consequences. Students had to wrestle with the structure of the system. 

Unexpectedly, it also sharpened my own thinking. Listening to students describe complex interconnections forced me to reconsider assumptions embedded in my own teaching. I found myself reflecting more critically on the simplifications within standard models and the limits of equilibrium reasoning when applied to volatile global systems.  

Finance education and wicked problems 

Business schools face growing scrutiny over their contribution to systemic crises. We often respond by adding Environmental, Social and Governance (ESG) modules or sustainability content. These are important and welcome developments. But my experience suggests that epistemology - how we teach students to think - may be just as important as what we teach. 

Wicked problems demand systems literacy. They require graduates who can hold multiple variables in tension, recognise feedback loops, anticipate unintended consequences and tolerate ambiguity without paralysis. 

Embedding systems thinking within a mainstream finance assessment did not dilute disciplinary rigour. It deepened it. Students still needed technical competence. But they were also required to confront the interconnectedness of financial decisions within social, political and ecological systems. 

The result was work that was more integrative, more critical and more attuned to real-world complexity. And, most importantly, it felt intellectually honest. Finance does not operate in isolation. Nor do the challenges our graduates will face.  

In an era defined by systemic risk and technological disruption, helping students learn to navigate ambiguity may be one of the most responsible acts of teaching we can undertake.  

References: 

Rittel, H.W.J. and Webber, M.M. (1973) ‘Dilemmas in a general theory of planning’, Policy Sciences, 4(2), pp. 155–169.