Learning disaster risk finance the playful way

Halfway through a disaster simulation game in Nairobi, a government official told us she was going to have a lot of uncomfortable questions for her department when she got back to the office. That was when we knew something was working.

Layer Up! is the Centre for Disaster Protection’s risk simulation game for disaster risk financing (DRF). We built it because the gap in DRF capacity isn't usually information - there are plenty of good resources already. What's missing is practice: reasoning under pressure, navigating institutional constraints and weighing trade-offs in teams. Layer Up! aims to simulate exactly that.

There is good reason to think play can shift thinking where conventional formats struggle. The broaden-and-build theory argues that positive emotions, the kind that play reliably produces, generate positive urges, and those urges broaden our thinking in ways that make discovery and learning possible. Layer Up! has been designed as a complement to established methods, such as workshops, slide decks and policy briefs, that do important work in transmitting technical knowledge but may not be able to generate bigger shifts in our thinking and behaviour.

Building a game that brings disasters to life  

Simulation games are not new in disaster risk and climate adaptation. The Red Cross Red Crescent Climate Centre and the World Bank both have tools in this space. Layer Up! builds on this tradition but addresses a gap we kept encountering in our own work: questions about the trade-offs between different risk financing instruments, including through our Stocktake of Financial Instruments and Comparison of Instruments work.

We wanted to make the game feel as close to real decision-making as possible. Our aim was to simulate the pressure, the uncertainty, and (as the name suggests) the challenge of layering risk financing instruments on top of each other. What sets it apart is the actuarial modelling underneath it; the scenarios teams respond to are driven by quantitative models of a country's risks, rather than by pre-scripted outcomes.

The game itself is simple. Two teams compete across parallel scenarios, each receiving information on a fictional country's disaster risks and a hundred tokens to allocate annually across five years of risk management decisions. A statistical disaster simulation model then runs the scenarios. Teams keep or lose tokens based on their choices and whatever disasters hit that year. Outcomes aren't guaranteed, forcing teams to make tough decisions and respond to the unexpected.  

Testing the game in Nairobi

We first tested Layer Up! with government officials and national disaster risk agency staff in Nairobi. The session comprised two hours of foundational DRF training followed by two hours of gameplay.

Choices that sounded good in the abstract suddenly had visible, quantifiable implications, particularly within a resource-constrained environment.  With their strategies visible and open to scrutiny, participants felt able to ask sharper questions and listen more closely to colleagues who understood parts of the system they didn't.

A game to get people talking

Participants quickly moved beyond probability and risk metrics and started grappling with political economy. How does a government actually implement a pre-arranged financing facility when a crisis hits? Which stakeholders need to be on board? In one session, participants found themselves debating how the finance ministry would bring politicians on side before a crisis, and whether those politicians would have any appetite for risk reduction investment whose benefit might only materialise long after they leave office.

The game created the space for questions that might otherwise remain unspoken in a formal workshop setting. It also surfaced starkly different priorities across contexts. Colleagues from the Caribbean tended to prioritise risk-transfer (as they have seen firsthand its utility) as opposed to African colleagues who were more supportive of risk reduction and retention measures.

In the post-game debrief discussions, participants spoke about the topic differently. They were less reliant on jargon and more confident about the questions they needed to ask. As one participant put it: "My department are going to hate me now. I've got so many questions I can ask them!"

This is the kind of learning that doesn't show up on a training evaluation form but is more relevant to how decisions actually get made. Participants left with a shared reference point they could take back to their institutions, having felt the consequences of their decisions across five simulated years, including the costs of choices that looked sensible on paper.

What the game can and can’t do

The game, of course, has its limits. It works best when participants are already motivated to engage so it doesn't solve the problem of who isn't in the room. The fictional country scenario also requires a step of translation; connecting the game's trade-offs to participants' own institutional context doesn't happen automatically. And like any simulation, it can't fully override what people bring with them. A participant anchored to a particular risk strategy may find ways to play that confirm rather than challenge it. Good facilitation can help, but it doesn't fully eliminate these constraints.

We’ve since run Layer Up! across a range of governments and institutions, and Nairobi wasn’t a one-off. The things we've found hardest to teach using a slide deck, including reasoning under pressure and navigating institutional politics, are the things that surface fastest through the informality of play.

We are continuing to develop Layer Up!, so if you are working on DRF capacity development and want to explore whether the game could work for your team or the governments you support, please get in touch.

‍If you've made it this far, we invite you to play this very short disaster risk mini-game (not to be confused with Layer Up!). Whilst playing, think about the risk strategies you might take to maximise your single-round score versus an average score over five rounds.