Designing an AI-Powered Climate Risk Intelligence Platform

The challenge was not simply visualising data, but operationalising predictive intelligence at scale. The client had developed what it called “The Forward Look” — a highly sophisticated macroeconomic modelling engine capable of forecasting how industry-level economic changes would cascade down into borrower-level risk exposure. Rather than relying on static historical reporting, the system introduced a forward-looking approach to risk modelling, enabling banks to simulate future economic conditions and understand how borrowers may perform over the next several years. Our role focused on transforming this highly complex modelling capability into an intuitive suite of enterprise-grade digital products that relationship managers, underwriters, risk officers, and C-suite stakeholders could actually use to make faster, more informed decisions.

The flagship product within the ecosystem was ON Climate — an AI-powered climate transition risk platform built specifically for modern banking institutions navigating the path toward NetZero 2050. The platform scanned lending portfolios and analysed how exposed borrowers were to evolving climate legislation and transition requirements. Using industry-standard climate modelling frameworks such as NGFS, the application could estimate the capital expenditure required for businesses to remain compliant over time, identify which borrowers were most at risk, and surface opportunities for banks to lend into climate adaptation and transition initiatives. Rather than treating climate compliance as purely a regulatory burden, the platform repositioned it as a strategic lending opportunity powered by predictive intelligence.

From a product design perspective, the challenge was creating a connected ecosystem across multiple greenfield applications while maintaining clarity in highly data-dense environments. We worked closely with cross-functional product, engineering, and risk teams to unify three independently developed applications — ON Climate, ON Scenarios, and ON Monitoring — into a single coherent product ecosystem. Shared information architecture became critical, particularly through the implementation of NAICS industry classification structures that allowed users to navigate seamlessly between borrower, industry, and sector-level risk insights. Extensive research and discovery sessions were conducted with banking professionals across multiple disciplines to understand how financial institutions assess borrower risk in practice, ensuring the platforms aligned with real operational workflows rather than theoretical use cases.

A major focus of the engagement was designing advanced data visualisation systems capable of transforming large-scale financial and macroeconomic datasets into actionable intelligence. In high-pressure risk environments, visual clarity directly impacts decision-making speed and confidence. We designed interfaces that enabled users to rapidly identify emerging risks, model future scenarios, stress test portfolios against changing economic assumptions, and monitor borrowers in real time through early warning indicators. Through multiple phases of iterative user testing and continuous collaboration with subject matter experts, the platform evolved into a highly sophisticated AI-powered risk intelligence ecosystem. The result was a scalable suite of products that positioned the client at the forefront of predictive banking technology — enabling financial institutions to move from reactive reporting toward proactive, AI-assisted strategic risk management.