Greenwashing danger in the banking sector

Judicial greenwashing convictions can result in heavy fines for banks. Even accusations of misleading sustainability claims - justified or not - can lead to significant reputational damage. The effective management and monitoring of greenwashing risks is complex in the face of increasing ESG reporting requirements. We explain how this management can be optimised in the financial sector and how greenwashing can be avoided in the white paper "When the green coat crumbles". Innovative technologies from KPMG can be a relevant success factor.

One thing is clear: greenwashing is at the top of the EU's agenda. Regulators have recently published a common definition and warn of risks. At the same time, there is a need to catch up in the management of risks in banks across Europe. In a recent KPMG industry survey on the implementation of internal ESG measures, only one in two respondents said that procedures exist to identify, prevent and manage greenwashing risks in the company. Definitions of greenwashing based on thresholds or quantitative metrics are often missing.

Banks are therefore exposed to concrete uncertainties. In addition to legal claims due to negligence, breach of contract or fraudulent misrepresentation, consumer lawsuits or pressure from activists are a growing danger. Potential damage to the image, loss of turnover and loss of income must be prevented in a targeted manner.

In the white paper, our experts present six fields of action and recommendations. A compact overview:

1. Understand your greenwashing risk - from regulatory and legal factors to market factors and internal factors.
2. Agree on your risk appetite: focus on thresholds and monitoring indicators
3. Establish a governance structure for greenwashing risks - from identification to assessment to reporting
4. Rely on training, awareness-raising and culture: focus on values, policies and best practices
5. Leverage new technologies: support from KPMG Impact ESG IQ platform and KPMG Business Environment Monitor - focus on AI tools, machine learning, predictive analytics
6. Prepare for incidents with crisis management plans