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Automation has a substantial influence on improving Operational Excellence and Decision Making. Executives' strategic decision-making abilities are being enhanced by Machine Learning (ML) in an increasing number of firms nowadays.

Global research done by MIT Sloan Management Review in collaboration with Google, involving 4,700 CEOs and a number of Key Informant Interviews, indicates that ML is increasingly transforming how firms generate and analyze value. This is largely due to the capacity of

ABMs aid in the implementation of the ABM methodology. By utilizing the ABM approach, we can automate and streamline the time-consuming process of identifying target accounts and reduce the effort, time, and cost required to court these prospective clients.

ABM systems facilitate the generation of most qualified leads, creation of customized purchasing journeys, enhancement of lifetime value of customers, and ensuring a robust pipeline of promising accounts. These solutions can be integrated with

This is a transcription of our interview with Terisa Roberts, Director and Global Solution lead for Risk Modeling and Decisioning at SAS about the role of AI/ML in Risk Management.

You can watch the original video interview here or tune in to this episode on our Risk Management Show podcast here https://globalriskcommunity.libsyn.com/terisa or via iTunes, Spotify and other podcast apps by searching "Risk Management Show"

Boris: Welcome to our interview with Terisa Roberts. She is a Director and

AI in Asset Management is trending and making a Wave in the Industry. Here is what You Need to Know About artificial intelligence and its application in asset management. The artificial intelligence finds its applications in various fields of industries. Presently, the main areas where AI is gaining more attraction is financial assets management that include investment banking, personal financial management, and fraud detection. With the advancement in technology, application of machine learning