Under the tide of the digital economy, the development and application of financial technology brings "creative threats" to traditional banking institutions. Accelerate the construction of the digital economy, comprehensively promote the digital transformation of the banking industry, promote high-quality financial development, and better serve the real economy and Meeting the needs of the people is of great significance to the stable operation of banking institutions.
Making full use of technologies such as big data, artificial intelligence, cloud computing, and RPA to build digital employees and accelerate the construction of a digital, intelligent, and platform-based value ecosystem will be the "core" for banking institutions to move towards digital banking.
Then, before using "bank digital employees" to promote the digital transformation of banks, we must first clearly understand the pain points of banks in order to prescribe the right medicine.
Possible Pain Points for Banks
1. There are many platforms and systems, huge business data, and high interoperability costs: the bank has many customer bases, as well as a large number of business types and data, and the manual efficiency is low and error-prone; the business involves many internal and external platform systems, frequent data island problems, and cross-system data synchronization , Filling in, comparing and other operations are time-consuming and labor-intensive.
2. The process is mostly manual, and it is difficult to improve safety, compliance, stability and efficiency: in response to the requirements of the China Banking and Insurance Regulatory Commission, the cost of business process compliance has risen, there are many verification and audit scenarios, the business process is lengthy, manual repetitive operations are required, and there are many banking personnel. Man-made risks are inevitable. In the process of serving customers, cross-system manual operations are inefficient; in the process of information collection, employees manually enter paper documents and electronic documents into the system, which is time-consuming and error-prone.
3. The competition in the industry is fierce, and the requirements for customer experience are high: the competition for banks is fierce, and the requirements for customer experience are increasing day by day. Timely and fast care and service, as well as the aggregation and synchronization of real-time information are required.
All the above pain points can be optimized with RPA bank digital employees. General and transactional work that needs to be repeated or batched, as long as the standard process can be extracted, can be replaced by digital employees to realize operation automation. While improving efficiency, it also ensures data security and compliance, thereby releasing the innovation potential of employees .
Application scenarios of RPA in banking:
The following are some business scenarios where real RPA banking robots can be used.
1. Account change report
Through the IPA digital employee technology, the standardization, intensification and leanness of corporate account management can be achieved, in order to better control operating risks, optimize the human structure, reduce operating costs and improve operational efficiency, and further optimize the business process of corporate bank settlement accounts. Improve the service efficiency of corporate bank accounts.
The RPA robot can complete the reporting tasks on a regular basis or manually regardless of holidays, day and night. At the same time, the operation of the RPA robot is error-free, avoiding manual operation errors, and realizing the complete automation of account reporting.
And after adopting the RPA robot, it can effectively liberate the human labor force, only need to use 0.5 robots for processing, high timeliness, fast speed, more manpower release, 100% accuracy, and meet the timeliness requirements of the People's Bank of China and the China Banking Regulatory Commission for account changes.
2. Account opening information inquiry
A bank has an average of 7,000 corporate account opening transactions per day, but the business process of corporate account opening is complex and involves multiple operational links, and it needs to log in to the PBOC system for verification and filing. There are inter-system data breakpoints between the processes. Waiting for a long time, it takes 2-3 working days to complete an account opening, resulting in a long waiting time for customers and affecting customer experience.
Using RPA robots to replace manual work in multiple links such as information query, effectively solves problems such as process breakpoints and cross-system data migration, and improves efficiency and relieves burdens for grass-roots branch tellers, freeing their hands.
Moreover, the whole process of opening an enterprise account can be completed within one hour, and customers only need to complete one on-site handling. Compared with the past 2-3 working days, the efficiency is significantly increased, and the customer handling experience is significantly improved.
3. Batch annual inspection of accounts
There is a time requirement for the annual inspection, there are many accounts that need the annual inspection, and there are many operation steps, and it is only one of the tasks of the account administrator. At the same time, some banking institutions still use manual methods for many verification and processing environments in the annual account inspection process. The multi-system coordination process is complicated, and there are problems such as time-consuming operations and easy omissions.
After the application of RPA robots, the operation and execution efficiency is high. It takes 10 minutes to complete a transaction manually. The number of hundreds of thousands of public accounts can increase the efficiency by more than 90%, effectively solving the problems of efficiency and timeliness, and strictly following the prescribed procedures for operation. , to avoid the risk of operational compliance, there is no longer any risk of late reporting, omission, or misstatement of account information, and timeliness and accuracy are guaranteed.
4. Supplementary notes on anti-money laundering low-risk rating
According to the requirements of the People's Bank of China for anti-money laundering work on customer information management, banks need to manually supplement the basic customer information and transaction details that are not automatically collected by the anti-money laundering system, and need to regularly update the due diligence report for supplementary recording. And after assisting the competent authority to complete the judicial inquiry and control of the person involved and the account involved, the person involved in the case who opened an account in the bank needs to be included in the supplementary record of anti-money laundering risk events.
The RPA robot can realize the unattended operation of the whole process, and the processing time has been reduced from the previous manual operation of 5-10 minutes per pen to 30 seconds per pen for automatic processing, and the overall processing efficiency has increased by 80%. And RPA reduces the incidence of errors by eliminating human errors (such as fatigue or lack of knowledge), thereby reducing the level of operational risk; the rate of return is high, and the error rate is zero.
5. Anti-money laundering information export
The customer anti-money laundering center needs to process more than 100 pieces of suspicious flow analysis work every day, and the monitoring work has been in a semi-manual state. The staff need a lot of working time every day to complete the extraction, statistics, sorting, etc. of relevant data, and then generate the analyzed data. Reporting, the workload is heavy and the efficiency is extremely low.
The RPA robot can realize the unattended operation of the whole process, and the processing time has been reduced from the previous manual operation of 5-10 minutes per pen to 30 seconds per pen for automatic processing, and the overall processing efficiency has increased by 80%. In addition, the robot simulates manual operations and non-invasively accesses internal and external systems, which not only ensures the timeliness and accuracy of business processing, but also effectively avoids business risks; the robot is flexible and expandable, not only supporting the flexible setting of risk rules, It also supports screening at any time, reverse investigation, timely early warning, etc.
6. PBOC data submission
According to the requirements of the People's Bank of China's interest rate reporting system for data submission, financial institutions need to complete the reporting of T days within T+3. The document data verification cycle is long (generally takes more than 3 to 4 hours), and manual submission is time-consuming and laborious; and when the situation of return and re-report occurs, the workload of submission will increase sharply.
After applying the RPA robot, it can automatically log in to the core to obtain the required data files, automatically log in to the pedestrian system and upload them, and the operation time is shortened by more than 90%.
When the business personnel find that there is an error in the historical data, the system supports the business personnel to manually type back the historical message in the PBOC system, and the interest rate submission robot can restart the submission according to the start date specified by the user, and the submission result will automatically notify the personnel to do it manually Check out.
7. Analysis of credit reports
The credit report is an important reference material for grasping the credit status of the credit recipient in the credit service, involving the pre-lending and post-lending links. After receiving the loan application, the lending institution can judge the user's repayment willingness according to the historical repayment situation in the report, and decide whether to provide a loan and how much amount to provide according to the number of loans already borrowed and the external guarantee situation; after providing the loan, the same Check your credit report to decide whether to increase your line of credit or call in the loan early.
Based on OCR identification and NLP intelligent analysis, IPA digital employees help customers efficiently obtain digital credit report information, thereby speeding up the credit review process and improving business service efficiency. Currently, in terms of recognition accuracy, the OCR field recognition accuracy rate exceeds 99.9%.
In addition, the average time for identifying and extracting a single page is 3 seconds, and the average time for identifying a single report is about 1 minute. Compared with the time-consuming manual work, the efficiency of information collection is significantly improved, and the transaction time of credit services will be greatly shortened, which is conducive to more efficient credit services. Reach users extensively, and then boost the development of inclusive finance.
8. Analysis of annual report and financial report
Among all aspects of bank management, financial management is the most important thing, and it is an effective way to ensure the safety, liquidity and efficiency of bank assets. As an important task in financial management, the level of financial statement analysis determines whether the decision-making of bank financial management can be based on correct financial information, thereby improving the scientificity and predictability of decision-making. Financial statements include balance sheet, income statement (or profit and loss statement), and cash flow statement, which are important considerations to reflect the operating conditions of enterprises.
Each piece of data in the financial statement will have its corresponding subject behind it, and based on this, the auxiliary accounting of the cross-check relationship between financial subjects will be carried out. If the accounting result does not conform to the financial formula, the business personnel will be prompted to perform manual verification to effectively ensure the data. accuracy. Under the huge data, the workload of people is greatly reduced, and the labor cost is reduced.
In addition, only a part of the annual report PDF file is useful financial report information, which needs to be intelligently screened to automatically distinguish whether the content is complete and whether there is any related content. If the content is incomplete, it will automatically identify the continuation page to ensure the integrity of the information.
9. Merchant information changes
Banks usually need to deal with a large number of customer service requests. RPA robots can help bank employees to automatically complete various tasks that need to be done manually, such as changing merchant information. In addition to saving human resources for banks, RPA can also ensure the timeliness of information, allowing merchants and customers to get timely and effective responses, thereby improving the service efficiency of banks.
10. Batch export of reports
Commercial banks are faced with a large number of report export work every day, involving more than 10 business systems, more than 30 reports and vouchers, which are used for business operations, account analysis, and reporting to regulatory agencies. Due to the many departments and systems involved, many "cousins" and "cousins" in the bank work overtime day and night to query, export, calculate, merge, split and other operations on reports. inefficient.
Nowadays, the use of robots to automatically export reports in batches has liberated business personnel, enabling them to devote more work with more enthusiasm and attitude, and provide customers with more satisfactory services
In addition to the above scenarios, there are also data analysis and supplementary recording, regular mail inspection, operation and maintenance monitoring platform inspection, unified report platform, loan risk warning, large loan installment approval, Hangzhou Bank through train inspection, foreign exchange price inspection, Various scenarios such as Guojie smart document review and smart credit review .
Customer Success Stories
The following are some successful cases of customers in the banking field.
1. Linhai Rural Commercial Bank
Project Background - Anti-Money Laundering Center : Automatically operate the anti-money laundering platform to intelligently manage user risk levels.
Project content - low-risk rating automation : automatically log in to the anti-money laundering platform, screen low-risk customers, automatically record customer information, and complete the rating
——Automation of suspicious transaction ledger generation : Summarize suspicious transactions and initiate approval in the system
Project achievements: Automated customer risk information maintenance of 100,000+
Processing efficiency increased by 100% , without manual participation
Processing data is 100% accurate
2. Beilun Rural Commercial Bank
Project Background——Digitalization of retail financial business: conduct intelligent and automated review of individual user business information to ensure high-quality and efficient completion of related businesses.
Project content - automation of large-amount credit approval: automatic entry of large-amount credit application information, query and completion of customer credit status, and initiation of credit entry process
Automated merchant information change: identification and review of key information in overseas customer contracts
Project results - fast and flexible adaptation to individual business needs : digital employees have low development and maintenance costs, and can be flexibly developed and deployed according to actual business needs
3. Postal Savings Bank of China
Project content: supply chain financial business IDP intelligent document review
· Automatically log in to the comprehensive information management platform to obtain credit review tasks, obtain review data sources through the big credit platform and image platform, compare them synchronously, and return the review results.
· High-precision OCR recognition of various types of documents such as photocopies and scans, and NLP intelligently extracts key information from documents for cross-comparison.
Project results: Efficiency improvement : 30 minutes reduced to 1 minute
Quality improvement : Human risk reduction
Cost reduction : Once put into permanent use
4. Hua Xia Bank
Press the "fast-forward button" of digital transformation: Through the nationally produced and self-developed AI technology and RPA products, Real Smart provides automated and intelligent solutions in various banking scenarios, covering data query, report making, work order processing, etc. Multiple processes have improved the overall business processing efficiency of the bank, helping Huaxia Bank Guangzhou Branch to press the "fast forward button" for digital transformation and innovative development.
5. Hengfeng Bank
Banking business scene automation: Real RPA assisted Hengfeng Bank in automating financial scenes, realizing automatic inspection and printing of value-added tax invoices and general invoices. Through real RPA, the financial management efficiency of financial institutions can be effectively improved, laying a good foundation for the digital construction of Hengfeng Bank.
6. Bank of Hangzhou
Use real RPA to make data processing more efficient: Banking personnel need to file information and export daily data in their daily work. Multi-platform operations are cumbersome, time-consuming, labor-intensive, and error-prone. Real RPA helps Bank of Hangzhou realize business process automation, rapid empowerment, effectively improve business processing speed, and avoid the risk of human error.
Real Intelligence has created a large number of typical digital scenarios. Currently, Real RPA·Digital Employees have served 1500+ top customers in various industries, covering e-commerce retail consumption, government and public services, communication operators, financial services, energy and manufacturing , Biomedical industry.
Major customers include: China Mobile, China Telecom, China Unicom, China Tobacco, China Post, State Grid, China Everbright Bank, Hua Xia Bank, China Merchants Bank, China Life Insurance, Ping An of China, China Shipbuilding Industry Corporation, Xugong Group, North Huachuang, Jingwei Textile Machine, Angang Lianzhong, Geely Automobile, Johnson Controls, Haier, Midea, Baicaowei, Proya, Jasper, Nice, Joyoung and many other corporate customers, as well as Zhejiang Provincial Bureau of Statistics, Jiangsu Provincial Taxation Bureau and other local government statistics, taxation , Judiciary and other departments have become the standard equipment for the digital upgrade of the entire industry and functions.