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Abstract
This paper analyses the demands on integration and scalability that the Environmental, Social and Governance (ESG) theme has placed on financial institutions and how modern digital technologies can help banks quickly scale and solve this business need. It starts with evaluating both internal and external factors that are not only driving ESG but also radically altering banking business models. It then discusses at length the integration issues faced by banks in this sector. While keeping the nature of these integration issues at the centre, the paper goes on to evaluate why modern digital stack complemented with artificial intelligence offers a good architecture to industrialise ESG in a bank. Factors like a tenfold increase in ESG data, new ways of greenwashing and falsification of ESG efforts coupled with terabytes of unstructured data are some of the themes the paper discusses at length. It also looks at how artificial intelligence helps solve these issues. The idea is to enable and complement human intelligence by reducing the time and effort taken for investigation and thus bringing operational efficiencies to help analysts and management focus on more valuable services like advisory, structuring and executing ESG offerings. It also looks at the maturity and scalability of artificial intelligence (AI) in this area. The paper concludes by suggesting a practical and implementable blueprint for AI-based ESG workflow that can be industrialised at scale.
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Author's Biography
Kovid Bhardwaj , CFA has close to 16 years of global experience working in investment banking and consulting in the areas of wholesale banking, mergers and acquisitions, corporate finance, derivatives pricing and valuations, credit and market risk, operations and accounting. He is an expert in leveraging strategic studies, digital approaches, statistics and machine learning to derive actionable business insights, help transform business models and remodel processes. Currently, he leads the initiatives on asset monetisation, machine learning and artificial intelligence in risk and finance space at Société Générale. As the global chair for machine learning for risk and finance, he is in charge of evaluation, execution and providing guidance on methodologies and implementation for strategic transformational projects in credit risk, market risk and accounting. His areas of interest are leveraging ML for pricing, client performance, behavioural finance and risk areas. He is passionate about data. Kovid is a CFA charter-holder from Chartered Financial Analyst (CFA) Institute, USA, and an MBA from Indian Institute of Management, Lucknow.