For a long time, when enterprises handle the business of public accounts in financial institutions, they will be hampered by problems such as complex handling procedures, numerous paper application materials, time-consuming approval processes, and long waiting times for opening. However, as more and more financial institutions choose independent and controllable cutting-edge technological innovation technologies represented by artificial intelligence and big data analysis to assist in the connection of internal and external systems, daily business processing and ecosystem accommodation of financial institutions, RPA platforms and products have become one of the automation processing tools commonly chosen by most financial institutions in the enterprise-to-open account scenario.
The RPA platform and products can quickly simulate the real-time interaction process between humans, computers and related systems, actively execute the operation requirements that meet the rules of the actual application scenario, efficiently complete high-frequency and repetitive scene business process work, and achieve accurate delivery. So, how can the RPA platform and products effectively ensure the safety of risk prevention and control while efficiently improving the work efficiency of open accounts in the specific subdivision of the business opening business of financial institutions?
Automated comparison of core data
In the process of dealing with the open account business of financial institutions, the staff needs a large number of corporate account data, formulas and standard requirements every day, so as to facilitate the final results after checking and comparison. As a result, financial institutions are often inevitably faced with massive amounts of data, cumbersome processes, and complex manual inputs.
In this scenario, RPA technology can provide targeted assistance for financial institutions to manage users at different levels and in different links in the comparison of public account verification data. It can not only accurately output accurate full data verification results for senior operation management personnel in a timely manner, but also quickly support grassroots operation personnel to successfully complete the automatic comparison of data collection of subordinate branches on the same day.
Automatic query of industrial and commercial information
According to the management requirements of the relevant regulatory authorities, the corresponding financial institutions shall complete the whole-process monitoring and management of the inquiry of the industrial and commercial information of the enterprises they have opened accounts and the review and dynamic review of the enterprise accounts in accordance with the timeliness, frequency and other indicators. Usually, financial institutions need to use the form of mass distribution to complete a series of work such as all the inquiry, review, review and manual entry of enterprise industrial and commercial information through manual traditional methods, and once there is an abnormal query of enterprise industrial and commercial information during this period, the staff needs to conduct a second inquiry, which is time-consuming and laborious and prone to errors.
After referring to the RPA platform and products, in the business scenario of industrial and commercial information inquiry, different financial institutions can complete the creation of customized and automated RPA execution processes according to their own needs and processes for enterprise industrial and commercial information query management, and complete the query docking with multiple external information publicity systems. The industrial and commercial information inquiry work supported by RPA technology can automatically obtain the industrial and commercial information of the enterprise customers that should be queried from the corresponding credit information publicity platform, and complete the automatic review risk reminder and review result output.
At-risk customersAutomaticIdentification
Domestic regulators and financial institutions are becoming more stringent in data quality assessment, which has led to financial institutions generally becoming more cautious about the workflow of monitoring and identifying corporate risk information. Therefore, in order to further improve the efficiency of data governance and shorten the identification and review work cycle, more and more financial institutions have taken the initiative to use RPA technology as the carrier to complete the automatic capture of the system and the accounting and evaluation of data risk coefficient.
In the process of completing the automatic capture of the system and the accounting and evaluation of the data risk coefficient, financial institutions can use RPA technology to automatically obtain credit customer information, financial statement information of the previous year, the number of employees, industry description, industry ** and many other aspects of information according to the user list and customer query on their desktop platform. At the same time, the RPA platform and products will further calculate the enterprise classification criteria for the multi-angle enterprise information and data that have been automatically captured according to the evaluation standards of the regulatory authorities, and finally complete the follow-up work of risk identification such as the input of calculation results, enterprise risk compliance judgment and automatic entry of system information.
Conclusion:
The above is only a brief introduction to the three subdivided work scenarios of RPA platforms and products in the process of serving the corporate account opening business of financial institutions. It can be seen that in these simple subdivided work scenarios, through the successful introduction of RPA platforms and products, the efficiency of these tasks that once took more than 100 hours to complete has been greatly improved, and the daily operating costs of financial institutions have been truly reduced.
The application of scientific and technological innovation technologies such as artificial intelligence, big data analysis, and cloud computing in the financial industry has made the financial industry's demand for automated and intelligent business processing more extensive and deeper. Today, RPA platforms and products have helped more and more financial scenarios automate business processes without changing the existing internal system-level architecture of financial institutions. In the future, RPA may provide more opportunities and possibilities for domestic financial institutions to promote the enrichment and growth of digital businesses.