Portfolio alignment makes it possible to measure the climate performance of a portfolio of assets. A number of alignment methodologies have been developed in the wake of the Paris Agreement to meet the objective of making financial flows compatible with a low level of emissions. To date, existing methodologies do not take account of the risk dimension. As a result, a portfolio can be aligned with a 2°C trajectory and still be significantly exposed to climate risks.
The use of machine learning comes up against ‘data scarcity’, i.e. poor data ‘quality’, which can only be exploited if it has been ‘labelled’ before and according to the analysis you want to carry out.
Network design determines the structure of a business network and influences its costs and performance. This covers a range of strategic decisions, such as determining the number, size, and location of facilities in the Network, and can include tactical decisions (such as distribution, transport, and stock management policies) as well as operational decisions (such as meeting customer demand).
Regulatory and ethical developments, linked to anti-discrimination law and the promotion of equality, are making it increasingly necessary to ensure that diversity and inclusion are respected and exemplified within an organisation. The same applies to talent management and employer branding.
In December 2019, the European Commission presented the European Green Deal, which aims to ‘transform the EU into a fair and prosperous society, with a modern, resource-efficient, and competitive economy where there are no net emissions of greenhouse gases in 2050 and where economic growth is decoupled from resource use.’
Artificial intelligence models are used in a number of fields (e.g. granting credit, fraud detection) and they deliver very good results. However, they lack transparency and explicability, which hinders their adoption by business teams and management, as well as their use in the eyes of regulators.
