ESG

ESG in Private Credit. Overcoming the challenges

Private credit has been growing in popularity as an asset class and with no slow down, growth looks set to continue. And this asset class is not immune from investor ESG targets and objectives.


The IMF estimates the size of the private credit market at just over $2 trillion USD, although industry commentators estimate it as much higher, at around $3.1 trillion already. In 2022, the Preqin 2024 global report predicted that by 2028, private credit and private debt would account for $2.8 trillion, but it seems we may have already surpassed that, such is the demand.  

This rapid growth brings with it heightened scrutiny from investors who are keen to understand the ESG impacts of their investments. As a result, private credit firms are under increasing pressure to provide detailed, transparent, and reliable ESG reports.  
Once an afterthought for many credit managers due to lack of control and access to useful data, ESG reporting is now something most firms (especially those marketing in the EU) can no longer ignore. 

 

Unique Challenges in ESG Data Collection for Private Credit Firms 


ESG reporting has become crucial for demonstrating responsible investment practices and attracting capital, but when applied to private credit firms, there are both broad and unique challenges these firms face in collecting and aggregating ESG data:

Data challenges

Private lending is not as simple as direct PE investment from a data management perspective. Often loans may be provided for specific assets/SPVs meaning that certain data points like board diversity must be recorded at a project sponsor level and others such as energy consumption or emissions avoided need to be tracked at an SPV level.  

Prioritising lenders, complex ecosystem and data silos

There are multiple stakeholders; borrowers, assets, SPVs and sponsors. Borrowers may be reluctant or unable to provide the required data due to various reasons, including lack of resources, insufficient understanding of ESG metrics, concerns over data privacy and a general disconnect from their lender. When a PE fund takes a majority stake in a company and sits on their board, it may be much easier to influence change when compared with a credit fund.  

Fragmented data sources

Information is often stored in disparate systems, making it difficult to aggregate and validate. This fragmentation hampers the ability to generate comprehensive and accurate ESG reports, which are essential for meeting investor expectations and regulatory requirements. 

Access to quality data and validation

Private markets are characterized by their opaque nature. Data is often proprietary and confidential. Obtaining consistent and comparable data across their portfolios is particularly challenging. Each borrower and asset may have different reporting capabilities and standards, resulting in a heterogeneous data set that complicates analysis and aggregation. Ensuring data integrity and comparability across various entities relies on robust data management systems and processes. 

Evolving Investor Expectations

Investors are increasingly requesting detailed, transparent, and reliable ESG reports from private credit firms. They are asking, not only for information on how ESG factors are integrated into the investment strategy but also expect ongoing updates on the performance and impact of these factors. 

Operational Challenges

Operationally, private credit firms often need significant changes to established practices and systems. Training staff and borrowers on ESG reporting standards and methodologies is essential but can be resource-intensive.  
It’s important to strike a balance between getting ESG data and the operational realities of their borrowers, many of whom may lack the necessary infrastructure or expertise to report accurately. They’ll need ongoing support and collaboration to build capacity and ensure high-quality data collection. 

 

So how can technology bridge the gaps? 

Dasseti’s Approach to Overcoming ESG Data Challenges

We have worked hard to build a unique platform that can support private credit firms in overcoming the many ESG data collection and reporting challenges. The platform is built to address the specific needs of private credit firms, offering tools that streamline the collection, validation, and reporting of ESG data. 

 
Secure Data Collection Portal 

Dasseti’s portal allows private credit firms to collect ESG data from various entities within their ecosystem, including borrowers, assets, and sponsors. This portal ensures that data is collected in a consistent and secure manner, reducing the risk of data breaches and inaccuracies. 


Data Interconnection and Benchmarking 

The Dasseti platform integrates data from external sources, benchmarking tools, and proxy data providers. This interconnection enables private credit firms to validate the data they collect and compare it against industry standards, ensuring that their ESG reports are accurate and comprehensive. 

 

Support for LPs and GPs 

Dasseti’s platform is designed to support both Limited Partners (LPs) and General Partners (GPs) in their ESG data collection and reporting efforts. With tools for efficient data collection and management, the platform helps private credit firms meet the growing demands of their investors and regulatory bodies. 

 

Strategies for Improving ESG Data Coverage in Private Credit 

Enhancing ESG data coverage is a major pain point but crucial for private credit firms aiming to meet investor expectations and regulatory requirements. Dasseti offers several strategies to improve data coverage and ensure the collection of high-quality ESG data. 


Clear Communication and Early Notification 

Effective communication is essential for successful data collection. Private credit firms should notify borrowers in advance about the data they need to collect and the reasons for its collection. This helps build trust and ensures that borrowers are prepared to provide the necessary information. 

Leveraging Loan Agreements 

Incorporating ESG reporting requirements into loan agreements can significantly improve data coverage. By tying data submission to credit facilities, private credit firms can incentivize borrowers to provide the required information consistently. 

 

Data Preparedness Surveys 

Implementing data preparedness surveys helps firms understand the readiness of their borrowers to report ESG data. These surveys identify potential gaps and areas where borrowers may need additional support, allowing firms to plan ahead and ensure comprehensive data coverage. 
 

Standardized Templates and Industry Guidance 

Using standardized templates and industry guidance simplifies the data collection process. By providing clear instructions and definitions, private credit firms can ensure that the data collected is consistent and comparable across different entities. 

Supporting Borrowers with Tools and Guidance 

Providing borrowers with the necessary tools and guidance for ESG reporting is critical. This support can include training sessions, access to reporting software, and assistance with complex calculations such as carbon emissions. 

 

Tailored Data Collection Templates 

Tailoring data collection templates to the specific needs and materiality factors of different borrowers enhances the relevance and accuracy of the data collected. This approach reduces the burden on borrowers and ensures that only pertinent data is requested. 
 

Achieve Better ESG Reporting in Private Credit 

Dasseti also offers several tips for improving the accuracy, efficiency, and comprehensiveness of ESG data collection and reporting. 

Supporting Early-Stage and Emerging Market Borrowers 

Early-stage and emerging market borrowers often lack the infrastructure and expertise needed for comprehensive ESG reporting. Offer tailored support and tools to help these borrowers understand and report ESG metrics accurately. 


Adapted Data Collection Based on Entity Growth Stage 

Recognizing that the data collection needs of early-stage investments differ from those of large entities, you can adapt data collection templates accordingly. This means the data requested is relevant and manageable for borrowers at different stages of growth. 
 

Intelligent Data Management Solutions 

Dasseti leverages advanced data management solutions, including semantic search and generative AI, to help firms manage large volumes of data efficiently and generate accurate reports. 

Managing Increasing Requests 

Private credit firms receive a growing number of ESG-related requests which often involve detailed and varied data points that take up a huge amount of resource. Approaches to these challenges are: 


Content Management 

Dasseti includes content management to allow firms to reuse and manage responses to investor queries. By leveraging semantic search and generative AI, the platform suggests previous responses and generates new answers based on historical data, streamlining the response process. 

Early Preparation 

Being proactive in managing investor expectations is essential. Dasseti enables firms to anticipate investor needs and provide relevant ESG data upfront. This proactive approach reduces the burden of responding to ad-hoc requests and ensures that investors have the information they need. 


Repurpose Responses 

Dasseti’s intelligent content management allows firms to reuse responses to similar investor queries. This reduces the time and effort required to generate new responses and ensures consistency in the information provided to different investors. 

 

The Future  

Dasseti ESG has been designed as a unique solution to help private credit firms stay ahead of: 

New regulations, such as the Corporate Sustainability Reporting Directive (CSRD), which  impact ESG reporting requirements for private credit firms.  

Demands for greater transparency and accountability in ESG reporting. 

Continuous improvement and feedback from borrowers and investors 

Leveraging advanced technologies like AI and machine learning 

Reach out for a demo or consultation to learn more about how Dasseti ESG is designed specifically for private credit firms and teams to build robust ESG data collection and analysis systems. 

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