A Study of the Ideas Behind Artificial Intelligence in Financial Technology

Dr. K. Baranidharan,

doi:10.48175/ijarsct-13880

IJARSCT

2023

DOI: 10.48175/ijarsct-13880

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A Study of the Ideas Behind Artificial Intelligence in Financial Technology

Dr. K. Baranidharan

Abstract: Artificial intelligence has the potential to totally revolutionize the financial industry by providing answers that are both knowledgeable and intelligent to problems that people are unable to solve on their own. FinTech systems that are powered by artificial intelligence make use of machine learning algorithms and natural language processing in order to analyze vast volumes of data and produce forecasts or judgments. Artificial intelligence is being used in the financial technology industry to improve the eff… Show more

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Cited by 3 publications

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An Investigation into the Field of Cloud Accounting

Dr. K. Baranidharan,

Dr. T. Suganya,

R. Pavitha

et al. 2023

IJARSCT

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The accounting sector is at the forefront of the widespread adoption of cloud computing. "the cloud" means remote servers and computing resources that may be accessed online. It is critical to keep abreast of new technology developments. Your company might reach new heights thanks to the competitive edge of this innovative technology. Scalability, remote access, low maintenance, and cost reduction are all features it offers. Everything you need to automate, streamline, and improve the efficiency of your company is right here. We must participate in cloud accounting as it is the wave of the future. The article delves into the conceptual notion and examination of cloud accounting

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An Investigation into the Field of Cloud Accounting

Dr. K. Baranidharan,

Dr. T. Suganya,

R. Pavitha

et al. 2023

IJARSCT

View full text Add to dashboard Cite

show abstract

An Investigation in to Sports Analytics and Related Tools

Dr. P. Ranjith,

Dr. K. Baranidharan,

K. Sabitha

et al. 2024

IJARSCT

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This study explores the application of sports analytics and the utilization of various tools in the sports industry. Sports analytics, also known as sports data analytics, is the application of data analysis and statistical approaches to extract important insights. Additionally, it aids in making well-informed judgments and enhancing performance in the realm of sports. Sports data analytics include a diverse array of methods and approaches, such as statistical analysis, machine learning, data visualization, predictive modeling, and optimization algorithms. The objective of sports business analytics is to get practical insights from a dataset in order to enhance decision-making and foster innovation in the sports industry

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Generative Artificial Intelligence as a Lifelong Learning Self Efficacy: Usage and Competence Scale

Arslankara,

Usta

2024

Journal of Teacher Education and Lifelong Learning

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The aim of this study is to develop a scale to measure the use and proficiency levels of productive artificial intelligence among young and adult lifelong learners. Research data were collected from 248 individuals aged between 18 and 55. After a thorough review of the literature, an item pool for the scale was created. Similar scales in the related field were examined, and the item pool was developed accordingly. The items were reviewed by two experts in educational technology and lifelong learning, as well as a scale development specialist. After making the necessary revisions, the trial form of the scale was presented to the participants. To determine the construct validity of the scale, exploratory factor analysis was conducted. The results of the exploratory factor analysis indicated that the scale consisted of two factors. The first factor comprises 10 items, while the second factor consists of 9 items. Confirmatory factor analysis was performed to reveal the relationships within the factors, the relationships between the variables and the factors, and the explanatory power of the factors on the model. The internal consistency coefficient, Cronbach's alpha reliability value, was determined to be .833. In conclusion, the Artificial Intelligence Usage and Proficiency (AIUP) Scale is expected to fill a gap in the literature and to be a scalable tool.

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A Study of the Ideas Behind Artificial Intelligence in Financial Technology

Cited by 3 publications

References 4 publications

An Investigation into the Field of Cloud Accounting

An Investigation into the Field of Cloud Accounting

An Investigation in to Sports Analytics and Related Tools

Generative Artificial Intelligence as a Lifelong Learning Self Efficacy: Usage and Competence Scale

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