In September 2021, financial institutions in the UK had to start reporting their Climate Biennial Exploratory Scenario (BES) to the Bank of England. The Bank of England has provided three scenarios of evolution in financial environmental policies and institutions must provide the Bank with projections of how these scenarios, and the policies predicted, will affect their portfolios of investments. In order to prepare for this, several of the institutions invited to take part in BES decided to employ our client and their Climate Change Solution team. The Climate Change Solution team runs several models that project how investment portfolios will cope under future financial policies aiming to ease climate change, which will be used to report for BES.
Vantage Point provided a team of junior Data Analysts to the Climate Change Solution team to assist with BES reporting. Our team had the responsibility of running client data through the various models required. This involved speaking to the client team to decide the run time frame and scope for each individual client institution. Once this was agreed, the client team provided the run team with a specific format of portfolio data to run through the models. To ensure the accuracy of the output data, all results went through a strict quality assurance (QA) process, after which the data was analysed using data visualisation tools. Any outliers were bought to the attention of SMEs in the modelling team who then either rejected or incorporated these outliers to enhance their model. Following the quality assurance process, the final data was signed off by the senior stakeholders to present to the end client.
The above project outlines an entire end-to-end run, which each member of the run team was tasked with in the months leading up to BES reporting. In order to ensure accuracy and timeliness for regulatory reporting, each client institution was required to undergo a dry run with the same input data which started in May 2021, prior to which the analysts were assisting other runs in order to familiarise themselves with the process and the model in order to be able to perform end-to-end runs effectively.