<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>RPA technology as one of the key technologies to drive financial digital transformation, this paper combines it with AI technology to build an enterprise financial intelligent audit model to realize financial digital operation. Based on the essential operation of RPA technology in the field of financial management and the sorting of financial automation process, the financial intelligent audit process under RPA technology is designed, and the decision tree algorithm is combined with the financial intelligent audit early warning index system to carry out enterprise financial crisis judgment and risk early warning. Taking Enterprise A as an example, early warning simulation of financial accounts and rolling budget simulation of funds are carried out respectively. The audit early warning indicator has a threshold of 0.06, and the average weight of each indicator’s characteristics and the early warning interval are calculated. Taking the indicator A1 as an example, the weight of the characteristic evaluation is 0.153, and the audit early warning signal will be output when the proportion of the balance of the accounts receivable ledger reaches 4.03%. The audit warning signal provides substantial operable space for enterprise financial management and operation.</p>
</abstract>

RPA technology as one of the key technologies to drive financial digital transformation, this paper combines it with AI technology to build an enterprise financial intelligent audit model to realize financial digital operation. Based on the essential operation of RPA technology in the field of financial management and the sorting of financial automation process, the financial intelligent audit process under RPA technology is designed, and the decision tree algorithm is combined with the financial intelligent audit early warning index system to carry out enterprise financial crisis judgment and risk early warning. Taking Enterprise A as an example, early warning simulation of financial accounts and rolling budget simulation of funds are carried out respectively. The audit early warning indicator has a threshold of 0.06, and the average weight of each indicator’s characteristics and the early warning interval are calculated. Taking the indicator A1 as an example, the weight of the characteristic evaluation is 0.153, and the audit early warning signal will be output when the proportion of the balance of the accounts receivable ledger reaches 4.03%. The audit warning signal provides substantial operable space for enterprise financial management and operation.

Exploration of Finance Digital Transformation Path Based on RPA Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Exploration of Finance Digital Transformation Path Based on RPA Technology"}

RPA technology as one of the key technologies to drive financial digital transformation, this paper combines it with AI technology to build an enterprise...

Exploration of Finance Digital Transformation Path Based on RPA Technology

Published Online: May 03, 2024

Page range: -

Received: Apr 04, 2024

Accepted: Apr 21, 2024

DOI: https://doi.org/10.2478/amns-2024-0976

Keywords
Decision tree algorithm, Audit early warning, Risk early warning, RPA technology, Financial digitalization

© 2024 Yunhao Zhang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Exploration of Finance Digital Transformation Path Based on RPA Technology

Published Online: May 03, 2024

Page range: -

Received: Apr 04, 2024

Accepted: Apr 21, 2024

DOI: https://doi.org/10.2478/amns-2024-0976

KeywordsDecision tree algorithm, Audit early warning, Risk early warning, RPA technology, Financial digitalization

© 2024 Yunhao Zhang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Decision tree algorithm, Audit early warning, Risk early warning, RPA technology, Financial digitalization