“Exploring the Boundaries of Knowledge in AI and ML”

iRM: An Explainable Al based Approach for Environmental, Social, and Governance Risk Management

Risks arising out of Environment, Social and Governance (ESG) are currently a vibrant topic for corporate boardroom discussion. The pandemic and climate change related disasters across the globe are stark facts that are calling for actions beyond words. For corporate leadership, there are various risks due to a volatile geo-political environment coupled with an enhanced regulatory load. Companies running for profit have realized that ESG has the potential for delivering value to top-line revenue and bottom line growth. There are various commercially available tools that benchmark various ESG related initiatives of a company. Often such tools help in tracking, estimating and forecasting carbon footprint, resource utilization efficiency. Data driven and statistical approaches, such as “what-if analysis” based on machine learning and deep learning models help in forecasting …

An Explainable AI approach for End-to-End Procurement Process Risk in SAP ERP, A Customer's Perspective

In the realm of enterprise resource planning, an innovative frontier emerges with the implementation of an Explainable AI framework designed to scrutinize and mitigate risks within the End-to-End Procurement Process. From a customer’s vantage point, this groundbreaking approach within the SAP ERP environment offers unparalleled transparency and insight. It not only identifies potential vulnerabilities but also elucidates the rationale behind decision-making, ensuring a higher level of trust and control. By providing a clear understanding of the AI’s thought process, this system empowers organizations to make more informed and strategic decisions, ultimately enhancing the efficiency and reliability of their procurement operations.

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