When a multinational bank needed to take action and improve its ability to manage Environmental, Social, and Governance (ESG) data, it partnered with Capgemini to develop a tailored ESG data and risk management solution. This project has streamlined complex reporting processes and advanced data analytics across multiple data sources via a centralized platform enabling the bank to remain compliant with ESG guidance while improving efficiency.

Cracking the code on ESG complexity

A top-tier global systemically important bank (G-SIB) faced increasing pressure to assess and manage ESG risks across its extensive client portfolio. ESG considerations had become critical due to growing regulatory requirements, investor expectations, and market pressures for transparency and responsible investment.

To meet these expectations, the bank required a robust, scalable solution to accurately evaluate its clients’ ESG performance. This would involve integrating complex data from external sources such as the Carbon Disclosure Project (CDP) and the International Energy Agency (IEA), alongside internal data sources.

As a result, the bank looked to enhance its ability to evaluate clients based on their net-zero commitments and ESG risk profiles. This assessment capability was essential for making strategic decisions regarding whether to extend support to environmentally sustainable businesses, proactively manage risk-heavy clients, or withdraw from emission-intensive relationships.

Traditional approaches to ESG data collection and risk assessment were manual, fragmented, and resource intensive, significantly slowing the client onboarding process and limiting transparency. Failure to effectively manage these risks could expose the bank to considerable regulatory, reputational, and operational challenges.

Recognizing these complexities, the bank partnered with Capgemini to develop solutions that would streamline ESG risk assessment processes. To facilitate successful implementation, the joint teams would need to integrate diverse external and internal ESG data sources, simplify manual processes, ensure compliance with EU taxonomy and Commercial Entities Substance Requirements Act (CESRA) guidelines, and enhance transparency through digital audit trails.

Charting a course to ESG simplicity and success

Capgemini collaborated closely with the bank to develop and implement a tailored ESG data and risk management solution, which was designed to meet its unique requirements and ambitious sustainability goals. The solution was anchored by the creation of an ESG reporting data lake capable of seamlessly ingesting and processing diverse data from reputable external sources.

Our cross-functional team, comprising Capgemini’s ESG team, data scientists, and data engineers, partnered with the bank’s business teams, sustainability experts, Relationship Managers (RMs), Product Owners (POs), and technology leads. Together, the team designed a comprehensive ESG model to accurately assess risks and opportunities, streamlining ESG reporting and aligning with net zero targets.

Key to this was the development of an ESG Risk Assessment Tool, enabling RMs to quickly evaluate ESG risks in line with CESRA and EU taxonomy standards through an intuitive questionnaire-based interface. By automating and digitizing this process, the tool significantly reduced the manual effort required during client onboarding.

Data integration challenges required Capgemini and the bank to ingest diverse datasets from internal client data as well as external vendors like CDP and IEA into the unified ESG data lake. Leveraging data and AI-driven models, the integrated system enabled precise risk evaluation and efficient reporting.

Unlocking greater insights for a sustainable future

The adoption of the ESG reporting data lake and ESG risk assessment tool has drastically reduced the time required to evaluate risks and compliance metrics. RMs now benefit from automated, standardized ESG assessments, substantially decreasing manual inputs and accelerating the client onboarding due diligence process. This automation has made it easier to obtain accurate physical risk scores and significantly expanded the bank’s client data coverage.

In addition, the bank has experienced a dramatic reduction in the manual input required by the Climate Analytics teams for asset location verification, enabling faster and more accurate ESG risk assessments. Additionally, the availability of new critical attributes, such as business disruption impact metrics, has enhanced the banks’ decision-making capabilities.

Looking ahead, the bank plans to extend the solution, leveraging the ESG risk assessment tool and ESG reporting data lake across more regions and business units. The organization will also further digitize and operationalize its EU taxonomy alignment, particularly within the German market, to streamline regulatory compliance and audit readiness.

By continuously refining and expanding this solution, the bank is poised to strengthen its market leadership in sustainability, drive deeper engagement with eco-conscious clients, and enhance overall business resilience.