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                <text>Faculty Publications</text>
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    <name>Book Chapter</name>
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          <name>Creator</name>
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              <text>Singh, Shanu; Awasthi, Yashmita</text>
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              <text>A Computational Data-Granular Model Highlighting the Evolving Fintech Landscape in India</text>
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              <text>01-01-2025</text>
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              <text>Computational Modelling Approaches to FinTech Innovation;pp.216-234</text>
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              <text>&lt;a href="https://doi.org/10.2174/9798898810818125010014" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.2174/9798898810818125010014&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105025322116?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105025322116?origin=resultslist&lt;/a&gt;</text>
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              <text>Singh S., Christ University, Bengaluru, India; Awasthi Y., Christ University, Bengaluru, India</text>
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              <text>The Fintech sector in India has undergone remarkable development, complementing the significant progress in financial technology designed to simplify financial services and provide innovative solutions. This study aims to discover and analyze two significant knowledge gaps in the Indian Fintech sector. It seeks to identify and examine the evolving patterns in web searches for potential career opportunities in the Fintech sector, providing perspectives into the trendline data from the country. Secondly, the study will assess employment in the Fintech Sector in India, emphasizing Position Titles, the geographical distribution of opportunities, and market trends from 2015 to 2023. Furthermore, it will examine the motivation and strategies essential for supporting and developing the Fintech sector in India. It performs a trend analysis on Fintech, Finance, and Accountancy searches and how they have changed over the years. By addressing these gaps, the research aims to provide valuable insights into the Fintech industry's dynamics and development in the Fintech job market over the years in the Indian context. To complement the trend analysis conducted in the paper, a computational modeling approach is used to predict future job trends in the Indian Fintech sector. The model relies on data from the years 2015 to 2023 on job openings, web searches, and geographical distribution. Therefore, the Autoregressive Integrated Moving Average (ARIMA) model has been used to understand the future patterns of job opportunities and skill requirements accordingly. This research will be helpful for companies and business owners to improve their financial operations in the long run.  2025, Bentham Books imprint.</text>
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              <text>Accountancy; ARIMA model; Computational approaches; Consumer behavior; Data granular approach; Digital transformation; Employment; Finance; Financial operations; Financial services; Financial technology; Fintech; Innovation; Job opportunity; Job portals; Job trend; Policy; Technological advancement; Transformational technology; Trend analysis; Trendline</text>
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              <text>Bentham Science Publishers</text>
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              <text>ISBN: 979-889881081-8; 979-889881083-2;</text>
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              <text>Restricted Access; Hardcopy may be available in the library</text>
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