ISSN2456-3315
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CrossRefDOI
ESTD2016
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Paper Title
Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems
Authors
Venkata Krishna Reddy Kovvuri
Keywords
Cloud Computing, Auto-Scaling, Financial Risk Prediction, Bankruptcy Forecasting, Charge-off Prediction, Machine Learning, Real-time Processing, Dynamic Resource Allocation
Abstract
The research area of the cloud-based auto-scaling analytics is investigated as a more efficient method of improving financial risk prediction systems, especially with respect to bankruptcy and charge-off prediction. The study incorporates machine learning approaches combined with cloud computing to investigate how scalability, on-demand processing, and resource adaptation contribute to more efficient financial risk evaluation. These results show that by providing improved decision-making, optimized use of computational resources, and proactive risk management, these technologies may improve the work of financial institutions
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IJRTI — journal style
"Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.7, Issue 4, page no.120-125, April-2022, Available :https://ijrti.org/papers/IJRTI2204021.pdf
APA — 7th edition
Kovvuri, V. K. R. (2022). Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems. International Journal for Research Trends and Innovation, 7(4), 120-125. https://doi.org/10.56975/ijrti.v7i4.206176
MLA — 9th edition
Kovvuri, Venkata Krishna Reddy. "Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems." International Journal for Research Trends and Innovation, vol. 7, no. 4, 2022, pp. 120-125, https://doi.org/10.56975/ijrti.v7i4.206176.
Chicago — 17th, bibliography
Kovvuri, Venkata Krishna Reddy. "Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems." International Journal for Research Trends and Innovation 7, no. 4 (2022): 120-125. https://doi.org/10.56975/ijrti.v7i4.206176.
Harvard — author–date
Kovvuri, V.K.R. (2022) 'Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems', International Journal for Research Trends and Innovation, 7(4), pp. 120-125. Available at: https://doi.org/10.56975/ijrti.v7i4.206176
IEEE — numbered reference
V. K. R. Kovvuri, "Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems," IJRTI, vol. 7, no. 4, pp. 120-125, Apr. 2022, doi: 10.56975/ijrti.v7i4.206176.
Vancouver — biomedical
Kovvuri VKR. Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems. IJRTI. 2022 Apr;7(4):120-125. doi: 10.56975/ijrti.v7i4.206176
AMA — 11th edition
Kovvuri VKR. Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems. IJRTI. 2022;7(4):120-125. doi:10.56975/ijrti.v7i4.206176
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2204021,
author = {Venkata Krishna Reddy Kovvuri},
title = {Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems},
journal = {International Journal for Research Trends and Innovation},
volume = {7},
number = {4},
pages = {120-125},
year = {2022},
month = {April},
issn = {2456-3315},
doi = {10.56975/ijrti.v7i4.206176},
url = {https://doi.org/10.56975/ijrti.v7i4.206176}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Kovvuri, Venkata Krishna Reddy
TI - Auto-Scalable Cloud Analytics for Financial Risk Assessment: Enhancing Bankruptcy and Charge-off Prediction Systems
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 7
IS - 4
PY - 2022
SN - 2456-3315
DO - 10.56975/ijrti.v7i4.206176
UR - https://doi.org/10.56975/ijrti.v7i4.206176
SP - 120
EP - 125
ER -
Issue
Volume 7 Issue 4,
April-2022
Pages : 120-125
Other Publication Details
Paper Reg. ID
IJRTI_206176
Published Paper ID
IJRTI2204021
Downloads
205,638
Research Area
Science & Technology
Country
hyd, hyd, hyd
Published
April 2022
Published Paper PDF
https://ijrti.org/papers/IJRTI2204021.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2204021
CrossRef DOI
https://doi.org/10.56975/ijrti.v7i4.206176
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About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
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Open
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Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
