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https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16146
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DC Field | Value | Language |
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dc.contributor.author | Anand, Siddhartha | - |
dc.contributor.author | Kashni, Tarun | - |
dc.date.accessioned | 2024-07-22T03:54:50Z | - |
dc.date.available | 2024-07-22T03:54:50Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | 36p. | en_US |
dc.identifier.uri | https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16146 | - |
dc.description.abstract | The rapid evolution of the financial landscape today could not occur without the embedding of Artificial Intelligence as a powerful driver has almost become a reality. The ones who became pioneers in integrating AI-based solutions to streamline actions and reduce errors have changed the industry’s standards to the ground. The work offers to overview the combination of human-based and AI capacities to reveal the possible patterns of leveraging the full potential of both under the financial decisions. Emerging AI technologies have drastically impacted many areas of the financial sector. These range from algorithmic trading to risk management and from customer support to fraud control. Indeed, AI enables systems to analyse enormous data sets, detect patterns, and make precise predictions. Yet, even with all their assertiveness, AI applications are still devoid of the subtleties and ethical reasoning characteristic of human professionals | en_US |
dc.language.iso | en | en_US |
dc.publisher | Alliance School of Business, Alliance University | en_US |
dc.relation.ispartofseries | 2022MMBA07ASB173 | - |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Human-Ai Partnershi | en_US |
dc.subject | Finance | en_US |
dc.subject | Collaborative Decision-Making | en_US |
dc.title | Enhancing Collaborative Decision-Making In Finance Through Human-Ai Partnership | en_US |
dc.type | Other | en_US |
Appears in Collections: | Dissertations - Alliance School of Business |
Files in This Item:
File | Size | Format | |
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2022MMBA07ASB173.pdf Restricted Access | 667.85 kB | Adobe PDF | View/Open Request a copy |
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