EconPapers    
Economics at your fingertips  
 

Bias Mitigation and Fairness in AI-Based HR Tools

Anshul Shetty and Dr. Shreevamshi N.
Additional contact information
Anshul Shetty: Department of Management Studies, Dayananda Sagar College of Engineering, Bangalore, India
Dr. Shreevamshi N.: Department of Management Studies, Dayananda Sagar College of Engineering, Bangalore, India

International Journal of Research and Innovation in Applied Science, 2025, vol. 10, issue 6, 1049-1067

Abstract: Forecasting has long served as a cornerstone of strategic decision-making in financial services. Traditionally grounded in econometric models, statistical inference, and time series analysis, financial forecasting has been employed to anticipate market movements, project economic trends, and guide investment strategies. Early models such as the Autoregressive Integrated Moving Average (ARIMA), Generalized Autoregressive Conditional Heteroskedasticity (GARCH), and Vector Autoregressions (VAR) formed the bedrock of quantitative finance, offering structured approaches to interpreting historical data and identifying trends. These methods, while rigorous, often rely on assumptions of linearity, stationarity, and normality that may not hold in complex, volatile, and non-linear market environments.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijrias/ ... ssue-6/1049-1067.pdf (application/pdf)
https://rsisinternational.org/journals/ijrias/arti ... n-ai-based-hr-tools/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjf:journl:v:10:y:2025:i:6:p:1049-1067

Access Statistics for this article

International Journal of Research and Innovation in Applied Science is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Innovation in Applied Science from International Journal of Research and Innovation in Applied Science (IJRIAS)
Bibliographic data for series maintained by Dr. Renu Malsaria ().

 
Page updated 2025-08-05
Handle: RePEc:bjf:journl:v:10:y:2025:i:6:p:1049-1067