The climate data for the project needed to be generated and quality-assured within a tight one-month timeframe. So, the first step was to hold express meetings with the bank and their advisory consultants to confirm the parameters for delivery. The bank required up-to-date, robust, local-scale climate data to inform next-level assessments. The data would have to withstand external peer review, and the data analysis would need transparency. The bank needed the data formatted to be fed into its Value and Risk models.

Through our association with the New Zealand Meteorological Service, we accessed the most recent historic time-series baseline data for New Zealand, including temperature, precipitation and wind. Once this data was bias-corrected with other databases to ensure its integrity, it was applied in modelling for 24 variables for each of the 230,000 assets. This allowed us to generate climate data outputs in a suitable format for rapid ingestion into the bank’s in-house assessment tool. Due to the tight timeline, we implemented a testing and validation protocol that could be applied consistently to the generated outputs as the project progressed. It was of great value to our client that our technical team could respond quickly and clearly to external review questions on the data and approaches.

A complete peer review of the risk assessment work was conducted, with full clearance given to the bank from the reviewers on the methods employed and outputs delivered.

Within the agreed timeframe, the bank received fully quantified climate risks for each of the 230,000 assets across the portfolio, accompanied by extensive documentation of data and methods. As a result, it has been able to continue with its process of voluntary disclosures. This seamlessly supports further Value at Risk and other analyses.

We continue to engage with the bank’s advisory consultants as consideration is being given to changes to the asset portfolio over time and for mandatory disclosure, which became legislation in January 2023.