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- W4313893995 abstract "This chapter aims to draw readers' attention on the challenges of modeling in finance. The new quantitative methods offer extraordinary capabilities with the latest algorithms using AI, ML, etc., aided by high technological computational power. However, the adoption of the latest tools and techniques comes with many challenges that are limited by human resources and nuances of financial industries. Unlike the recommendation-based models in the technology industry, real money is at stake in the financial industry. Hence, it is not very prudent to accept the result of quantitative methods without understanding the inherited risks. Despite the hype created by data scientists, the financial industry cautiously adopted the highly complicated learning tools after due diligence because investor and shareholder money is at stake and experts want to strategize financial decisions based on the data model outputs. Further, the chapter brings the key highlights of financial models." @default.
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- W4313893995 date "2023-01-09" @default.
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- W4313893995 title "Data Modeling in Finance Challenges" @default.
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- W4313893995 doi "https://doi.org/10.4018/978-1-6684-4483-2.ch012" @default.
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