UST helped global asset management company accelerate ESG data processing by 70%
This European multinational company provides investment management solutions to clients around the world. With more than £200 billion in assets under management, the company employs nearly 1,000 people.
Difficulty integrating and analyzing ESG data
With an increasing focus on sustainable investing, the company wanted to integrate environmental, social, and governance (ESG) data into its portfolio optimization processes. However, the teams working on the ESG initiative struggled with rudimentary tools and manual processes. They found it hard to compile, consolidate, and integrate external data from sources like the World Bank Group, Reporters Without Borders, and the World Inequality Database with internal portfolio asset information. The ESG teams also wanted to transform and enhance the data so asset managers could easily access and understand the information to make ESG-based investment decisions.
Automated data analytics pipelines replaced tedious manual processes
UST provided a managed data science services solution using our xpresso.ai platform, an enterprise framework with accelerators to help companies create artificial intelligence (AI) and machine learning (ML)-based analytics solutions. The data engineering system was designed to run automated data analytics pipelines dailyto help asset managers optimize portfolios for sustainable investing. The solution:
- Collects, transforms, and maps data—from third parties and open sources with internal portfolio asset information for automated downstream processing.
- Applies a consistent data processing methodology—to ensure resulting analytics and metrics are valid and reliable—which was not present previously.
- Enhances data—with advanced data science methodologies, such as banding and Z-scoring, and also augmenting data with indicators and ESG-based metrics and scoring methods.
- Gives users a visualization dashboard—so asset managers can intuitively understand and analyze data to make informed decisions for ESG portfolio investments.
Reducing 70% of manual work effort to collect, analyze, and share ESG data
Now, the company can easily run data analytics pipelines on a daily basis—a task that previously took three full-time employees to accomplish in the same timeframe. The automated processes eliminated 70% of the manual work effort to collect, process, and share ESG data with portfolio managers. The visual dashboard provided asset managers an intuitive tool to analyze ESG data and optimize investments.
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