The complex challenge of simultaneously dealing with multiple stressors relating to climate change highlighted the need for scaling-up the role of engineering knowledge in informed decisions on investment sustainability. As such, integrating environmental, social and governance (ESG) factors into equity investment analysis has been adopted as the most widespread responsible investment practice in the financial engineering to holistically cater for climate risks and resilience. However, while tremendous progress has been made on raising awareness on the aspects of ESG, its integration with investment strategies remains sparse and inconsistent, which makes it difficult for investors to measure, benchmark, and identify ESG stewardship practices that genuinely add financial value.

To respond to investors’ demand, actions must be scaled-up to redefine ESG integration and application process (as underlined during the 27th Conference of Parties (COP27) of the UN Framework Convention on Climate Change). The model incorporates three stages including qualitative analysis (gather information from corporate reports and third-party analysis to identify ESG material factors affecting the corporate governance); quantitative analysis (elucidate data from block-chain, satellite, artificial intelligence, mobile technology, internet and cloud, corporate documents, to evaluate the impact of material factors on investors’ portfolio securities, and adjust the financial forecasts and valuation appropriately); and investment decision (decide to buy or increase weighting to trigger or support corporate ESG engagements, hold or maintain weighting, sell or decrease weighting).

The model implementation requires diverse engineering process consisting of fundamental strategy (translate forecasted financials into impacts of ESG factors); systematic process (fully integrate ESG factors along financial value, size, momentum, growth, and volatility); sell-side (evaluate the commitments of external stakeholders to ESG integration); smart beta process (use ESG factors and scores as weights in portfolio construction to create excess risk-adjusted returns, reduce downside ESG risk and enhance portfolios’ sustainability); and indexing (adjust the overall ESG and sustainability risks profile with index weights).

In sum, the model and engineering process aim at systematically and explicitly determining the fair corporate value at each stage of investment decision with accurate integration of ESG factors into the economic and industrial context, analysing the quality of corporate governance and strategy, adjusting earnings forecasts (accurately highlight future risks and opportunities) and valuation discount rates to reflect corporate-specific climate resilience and sustainability status.

This article is contributed by Ir Dr Alex Gbaguidi with the coordination of the Environmental Division.