Sustainable Fitch builds new ESG rating platform using AWS

There is a growing interest around environmental, social, and governance (ESG) ratings and insights in the marketplace. This interest has created new opportunities for information and products that provide clarity about the ESG footprint of a variety of entities, from companies to investments, among others.

This blog will enable organizations to better understand how Sustainable Fitch manages the complex workflows, and associated distributed data, involved in discerning ESG ratings using Amazon Web Services (AWS).

Sustainable Fitch and ESG Ratings

Sustainable Fitch, a Fitch Solutions company, provides granular and transparent ESG ratings, data and analysis at an entity, framework and instrument level. This allows investors to distinguish between ESG impact, outcome, and performance at a detailed individual factor level. Investors can also compare individual characteristics of entities and debt issuance between entities within a sector, across different sectors and across asset classes.

Understanding the Complex ESG Regulatory Ecosystem

ESG’s regulatory ecosystem is not standardized and is continually evolving—taking different forms at the national and regional levels. Figure 1 provides a mapping of the main standards across countries.

Figure 1 – Regulatory ecosystem of ESG and mapping of the main standards across countries

ESG Rating Challenges: Complicated processes and disorganized data

Developing ESG ratings presented a few challenges that were addressed using AWS services:

Complex Workflow: ESG rating information is not standardized across companies; each company reports the information in their own format. Therefore, analyzing ESG data involves multiple, complex steps focused on researchers gathering data from ESG reports, and analysts analyzing the details and verifying the data.
Scattered Data: Since ESG data is disorganized and scattered across multiple resources, automated data gathering across sources, as well as centralized and scalable storage, was required.
Carbon Footprint: Sustainable Fitch sought to build a new technology solution running many new systems, but without increasing their overall carbon footprint.

Architecture and Data Flow

Figure 2 – Sustainable Fitch architecture overview

The Sustainable Fitch architecture presented in Figure 2 is centered around an Amazon Simple Storage Service (Amazon S3)-based data lake governed by AWS Lake Formation. It uses serverless services like AWS Glue, AWS Lambda and Amazon Athena for data processing. Data in the lake is governed by AWS Lake Formation to allow for secure querying by Amazon Athena. It ingests topics into Amazon Managed Streaming for Apache Kafka (Amazon MSK) for delivery to the downstream Amazon Elastic Kubernetes Service (Amazon EKS)-based backend services for consumption.

ESG rating creation starts in two places (step 1a and 1b in Figure 2). Industry market data required for building a rating is ingested into the data lake (step 1b). Some of that data is Sustainable Fitch intellectual property. Other data, like meteorological data, is acquired from third-party providers. Data comes as flat files, and lands in the raw zone of the data lake.

Separately, Sustainable Fitch analysts enter their research into an internal Java-based application called the Ratings Capture Tool (step 1a). The application runs as a set of microservices in Amazon EKS. It uses various AWS managed data stores like Amazon Aurora, Amazon DynamoDB and Amazon Relational Database Service (Amazon RDS), dictated by individual service needs. The changes to the data are posted to Amazon MSK topics (step 2) and ingested into the raw zone of the data lake (step 3).

Later, data in the raw zone is read, validated and transformed by using AWS Glue and Amazon Athena. It is stored in a consumption-ready file format (such as Apache Parquet) in the staging layer of the data lake. The data is also indexed and metadata is stored in a table in the AWS Glue Data Catalog.

At this point, the engineering teams responsible for individual micro-services that power Sustainable Fitch’s flagship customer portal can shop for the required data and hydrate purpose build datasets in the data lake analytics layer. A dedicated process uses Amazon Athena to query the data lake and to post the data to a set of Amazon MSK topics (step 4) where the microservices serve the data for user’s requests (step 5). The data is retained in the Amazon MSK topics for resiliency to allow consumers to reprocess the data in case of failure.

On the other end of this flow, Sustainable Fitch customers use the platform to access ESG ratings. After being authenticated and authorized, the customer’s API request is directed to a GraphQL server (step 7). There it combines the ESG score read from the Amazon MSK topics (step 6) with other data provided by some of the 50+ Fitch microservices to present a response to the customer. It should be noted that Sustainable Fitch’s platform is a subscription-based paid service.

Business and Technology Outcomes

Based on the solution outlined in the preceding section, Sustainable Fitch was able to address key business challenges through their coordination with AWS.

The five key business and technology benefits for Sustainable Fitch are as follows:

1. Improved data integrity for structured data.

2. Reduced time-to-market for launching new instruments and entities on the Sustainable Fitch platform.

There are now over 5,000 instruments and 1,000 entity ratings published. The entity ratings focus on how organizations affect sustainability, while instrument ratings focus on how specific debt issuances affect sustainability.

3. Ability to scale the platform globally by adding additional instruments and bond ratings incrementally.

4. Productivity of the data collection team improved by 25%.

5. Addition of significant new technology with minimal increase to their carbon footprint by using AWS services for their technology platform. (Note: Renewal energy plays a significant role in reducing carbon footprint of AWS services. According to a new 451 Research report, moving on-premises workloads to AWS can lower the workload carbon footprint by 88% for the median surveyed US enterprise data centers and 72% on average for the top 10% most efficient enterprises surveyed.)

The next steps for Sustainable Fitch will be to use generative AI services for appropriate customer-centered use cases.

Summary

Sustainable Fitch was able to use AWS services to build a scalable ESG ratings platform and manage the complexities related to ESG regulations and unstructured data analysis from multiple sources. Financial services companies can leverage an understanding of these challenges, and how AWS services helped alleviate them, to better plan for their own ESG journey.

Contact an AWS Representative to know how we can help accelerate your business.