Cash Flow Prediction of a Business Institution Using Deep Learning

Registration ID: IJNRD_185386

Published ID: IJNRD2212321

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Anagha Chaudhari , Aditya Jadhav , Amitesh Deshmukh , Uddhav Patil , Sujit Deore

In this paper, we have examined how several deep learning algorithms can be used in the daily work of a financial organization to estimate cash flow and preprocess data. The challenge is to project the company's various departments' profit and loss so that the firm may prepare for the following year's business expenditures by examining the cash flow prediction. These estimates can then be used to make sure that the right amount of money is kept by businesses in bank accounts for preventing overdraft fees or irrational investment fund usage. The company wants to increase the accuracy of its present manual, ad hoc process for calculating cash flow estimates. Unsupervised neural networks and a variety of other methods like Random Forest, Decision Tree, Linear Regression are being employed, and the results are being used to forecast profit and loss and then the results are being compared at the last to decide which algorithm is best among these algorithms.

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Anagha Chaudhari, Aditya Jadhav, Amitesh Deshmukh, Uddhav Patil, & Sujit Deore (December-2022). Cash Flow Prediction of a Business Institution Using Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(12), d194-d199. https://ijnrd.org/papers/IJNRD2212321.pdf

Volume 7 Issue 12, December-2022

Pages : d194-d199

Paper Reg. ID: IJNRD_185386

Published Paper Id: IJNRD2212321

Downloads: 000121985

Research Area: Computer Science & Technology 

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2212321.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2212321

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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