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Financial Modelling 2.0: The Machine Learning Transformation
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Author(s): Sai Nomitha Yarabolu (Sree Vidyanikethan Engineering College, India)and A. V. Sriharsha (Sree Vidyanikethan Engineering College, India)
Copyright: 2025
Pages: 30
Source title:
Data Analytics and AI for Quantitative Risk Assessment and Financial Computation
Source Author(s)/Editor(s): Mohammad Gouse Galety (Samarkand International University of Technology, Uzbekistan), Jimbo Henri Claver (Samarkand Interntional University of Technology, Uzbekistan), A. V. Sriharsha (Mohan Babu University, India), Narasimha Rao Vajjhala (University of New York Tirana, Tirana, Albania)and Arul Kumar Natarajan (Samarkand International University of Technology, Uzbekistan)
DOI: 10.4018/979-8-3693-6215-0.ch004
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Abstract
Traditional financial modeling involves the use of historic data with preset formulae. However, the rising complexity of financial markets calls for more advanced tools. This chapter discusses how machine learning and its algorithms will revolutionize financial modeling by moving into a new realm of Financial Modeling 2.0. We will discuss how ML algorithms can analyze large amounts of data and discover hidden patterns and relationships that may elude classic techniques. This will yield more accurate and adaptive financial models, which will be built to predict future performance and, with time, to improve on their predictions. The chapter thus focuses on specific ML applications to financial modeling, underscoring their potential use for tasks and their advantages. The chapter concludes by asserting that machine learning is revolutionizing financial modeling to give one an edge in today's dynamic financial landscape.
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