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Transforming corporate governance assessments, setting new standards for a smarter, sustainable future.
Corporate governance is critical for building trust and sustainability in today’s business world.
The Centre for Governance and Sustainability (CGS) at the National University of Singapore (NUS) Business School, a thought leader in corporate governance research, has taken a significant step forward in transforming its processes.
Traditionally, CGS relied on manual methods to conduct corporate governance assessments, which were time-consuming and labour-intensive. Data extraction, acquisition, and analysis were performed manually, leading to inefficiencies, fatigue, and time delays.
This is where TCS stepped in, leveraging its AI-ML-driven TCS ESG Integration Solution to enable automation of corporate governance assessments.
We deployed the TCS ESG Integration Solution, which integrates the impact assessment framework and data hub.
The solution includes an end-to-end platform for data extraction, acquisition, analytics, and dashboard capabilities tailored to CGS' specific needs. The platform also has a human-in-the-loop component to validate and continuously improve the results. Customized for CGS requirements, the TCS ESG Solution Framework fetches information required for assessment from the company disclosures available to the public. The relevant information is then populated in the respective fields in various sections. The analysts validate the information gathered for sample companies and feed the correct values to the AI-ML framework for training.
TCS has also built a survey module to correlate information through survey forms with the target companies while tracking the survey status. In addition, we have built a media dashboard to gather sentiments from news feeds and generated the scores based on the evaluation and weightings. This scalable platform not only meets CGS’ current governance assessment needs but is generic and can be customized for any type of assessment framework based on published information. The parameters, weightings, and scoring are highly configurable, including the hierarchy of program setup. Hence, our solution is well-suited for scaling up and adaptive for similar purposes.