A method and device for intelligent fund deduction applicable to multiple scenarios

Abstract

The present invention proposes a method and device for intelligent fund deduction applicable to multiple scenarios. The method includes: configuring and maintaining core variables, including product parameter A, bank parameter B, and decision-making parameter C; initiating a batch task to query a list of IOUs participating in the deduction based on product parameter A; calling a loan core module to query the outstanding amount of each IOU on the IOU list; determining whether the IOU supports splitting based on decision-making parameter C, and if so, proceeding to the next step; if not, directly generating a deduction request message A; calling a deposit core module to query the account balance, calculate the deduction amount based on the outstanding amount and the account balance, and split the deduction amount based on the bank limit information in bank parameter B, generating a deduction request message B; and calling a payment module to execute the deduction operation based on deduction request messages A / B. The present invention solves the problem of customers who are unable to recharge and repay their loans in a timely manner due to work circumstances and are unconsciously overdue.

Description

Technical Field

[0001] The present invention relates to the field of computer information technology, and in particular to a method and device for intelligent fund deduction applicable to multiple scenarios. Background Art

[0002] At present, for most cooperative platforms, credit card repayments are to guide customers to actively initiate recharges through the basic recharge function before the repayment date, and transfer funds from the bound cards of other banks to the second-class account of the bank to be repaid.

[0003] However, with the promotion and development of banking business scenarios, the scope of service customers continues to expand, and some customers of the connected scenario platforms do not have the time and energy to recharge and repay in time before the repayment date. As a result, the customer's overdue rate increases, affecting credit reports and causing many troubles to customers. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and device for intelligent fund deduction applicable to multiple scenarios, which solves the problem of unconscious overdue payments by customers who cannot recharge and repay in time due to work conditions.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for intelligent fund deduction applicable to multiple scenarios, which runs between the enterprise online loan module, the loan core module, the deposit core module and the payment module, and includes the following steps: configuring and maintaining core variables, the core variables including product parameter A, bank parameter B and decision call parameter C; starting a batch task, and querying the list of IOUs participating in the deduction according to the product parameter A; calling the loan core module, and querying the amount to be repaid of each IOU on the IOU list; judging whether the IOU supports splitting according to the decision call parameter C, if so, proceeding to the next step, if not, directly generating a deduction request message A; calling the deposit core module to query the account balance, calculating the deduction amount according to the amount to be repaid and the account balance, and splitting the deduction amount according to the bank limit information in the bank parameter B, and generating a deduction request message B; calling the payment module, and performing the deduction operation according to the deduction request message A / B.

[0006] As a preferred solution, it also includes synchronizing the bank limit information, specifically: regularly starting the bank limit synchronization task, the enterprise online loan module notifies the payment module through the interface to obtain the bank limit information, and uploads it to the agreed directory; clearing the temporary table data, the enterprise online loan module downloads the bank limit information, and stores it in the temporary table after parsing; using SpringBatch to read the temporary table, perform logical cleaning of the data, and then save the valid data to the limit table.

[0007] As a preferred solution, it also includes synchronizing the bank limit information. Specifically, when the bank limit information is monitored to change, the payment module sends a message in real time through the Kafka module; the enterprise online loan module builds a consumption module, pulls messages from the topic of the Kafka module, and refreshes the local bank limit information in real time.

[0008] As a preferred solution, it also includes: after the deduction operation fails, it is repeated N times on the same day. After exceeding N times, the deduction is stopped and the batch task fails.

[0009] As a preferred solution, it also includes: obtaining the bank's daily limit based on the bank parameter B. If the customer's deduction amount on that day exceeds the bank's daily limit, a grace period is triggered, and the deduction operation will continue during the grace period. No interest or penalty interest will be calculated during the grace period, and the amount will not be reported to the credit bureau.

[0010] As a preferred solution, the deduction amount is the difference between the amount to be repaid and the account balance.

[0011] As a preferred solution, the deduction amount is split according to the bank limit information in the bank parameter B to generate a deduction request message B, including: assuming the bank limit information is m and the deduction amount is n, the result after splitting the order is: mod(n, m) amount m and 1 amount rem(n, m); saving the mod(n, m)+1 amount to the deduction preparation table; generating a deduction request message B according to the deduction preparation table.

[0012] As a preferred solution, the message body of the deduction request message includes a name, type, description and instructions for use.

[0013] The present invention also discloses an intelligent fund deduction device suitable for multiple scenarios, including: a configuration and maintenance module, used to configure and maintain core variables, the core variables including product parameter A, bank parameter B and decision call parameter C; a list query module, used to start a batch task, and query the list of IOUs participating in the deduction according to the product parameter A; a pending repayment query module, used to call the loan core module, and query the pending repayment amount of each IOU on the IOU list; a splitting judgment module, used to judge whether the IOU supports splitting according to the decision call parameter C, and if so, proceed to the next step; if not, directly generate a deduction request message A; a splitting module, used to call the deposit core module to query the account balance, calculate the deduction amount according to the pending repayment amount and the account balance, and split the deduction amount according to the bank limit information in the bank parameter B to generate a deduction request message B; a deduction execution module, used to call the payment module, and execute the deduction operation according to the deduction request message A / B.

[0014] Compared with the existing technology, the beneficial effects of the present invention include: effectively splitting the bill based on the single limit and daily limit of the customer's card-binding bank, as well as the customer's current outstanding amount at the bank to be repaid, and the program automatically executes the deduction step after the bill splitting is completed. The present invention has a full set of functions that can be fully automated, without the need for manual intervention, reducing manual operation and maintenance costs; it can meet the requirements of different products and different scenarios through multi-dimensional parameterized configuration, improve customer experience, solve customer pain points, and provide customers with better services; it covers various scenarios, and a one-time design and development can meet the sharing of multiple products, reducing human development costs; it automatically updates bank limit information in real time to avoid deduction failures due to bank limit updates. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The disclosure of the present invention is illustrated with reference to the accompanying drawings. It should be understood that the drawings are for illustrative purposes only and are not intended to limit the scope of protection of the present invention. In the accompanying drawings, the same reference numerals are used to refer to the same components. Among them:

[0016] Figure 1 This is a flow chart of a smart funds deduction method applicable to multiple scenarios according to an embodiment of the present invention;

[0017] Figure 2 This is a schematic diagram of the process of synchronizing bank limit information according to an embodiment of the present invention;

[0018] Figure 3 Another schematic diagram of a process for synchronizing the bank limit information according to an embodiment of the present invention;

[0019] Figure 4 This is a schematic diagram of the process of data interaction of the Kafka module according to an embodiment of the present invention;

[0020] Figure 5 This is a structural diagram of an intelligent funds deduction device applicable to multiple scenarios according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] It is easy to understand that according to the technical solution of the present invention, without changing the essential spirit of the present invention, a person skilled in the art can propose a variety of interchangeable structural modes and implementation modes. Therefore, the following specific embodiments and drawings are only exemplary descriptions of the technical solution of the present invention and should not be regarded as the entire invention or as a limitation or restriction of the technical solution of the present invention.

[0022] According to one embodiment of the present invention, Figure 1 A smart deduction method for funds applicable to multiple scenarios runs between the enterprise online loan module, loan core module, deposit core module and payment module of the credit business system, including:

[0023] Step 1: Configure and maintain core variables. Core variables include product parameter A, bank parameter B, and decision-making parameter C, which are used to determine whether the credit business system starts smart deductions and the deduction method.

[0024] (1) Product Parameter A: When connecting to a new platform, if there is a need for deduction based on the characteristics of the product, maintain the product list to ensure that the products to be processed are retrieved during batch processing.

[0025] (2) Bank abbreviation parameter B: To support different bank lists for different products, different debit channels for the same bank, and different single-transaction and daily limits for each bank, a set of configuration pages has been developed for back-end management to support the addition, modification, and deletion of products, banks, single-transaction limits, and other dimensions.

[0026] (3) Decision calling parameter C: Set the decision calling parameter C to distinguish whether to split the order and deduct it. It can support configuration of products, banks, and maintenance.

[0027] Step 2: Start a batch task to query the list of IOUs that are subject to deduction based on product parameter A. The IOU list is determined by the number of IOUs with outstanding balances greater than zero on that day.

[0028] Step 3: Call the loan core module to query the outstanding amount for each IOU on the IOU list. The customer account information corresponding to the debit account includes the account number, account name, bank name, bank number, card type, and the phone number reserved with the other bank.

[0029] Step 4: Based on the decision-making parameter C, determine whether the IOU supports splitting. If so, proceed to the next step. If not, directly generate the deduction request message A.

[0030] Step 5: Call the deposit core module to query the account balance, calculate the deduction amount based on the outstanding amount and the account balance, split the deduction amount according to the bank limit information in the bank parameter B, and generate the deduction request message B.

[0031] The message body of the deduction request message includes name, type, description, and usage instructions, as shown in the following table:

[0032]

[0033]

[0034] The deduction amount is the difference between the outstanding amount and the account balance. The deduction amount is split based on the bank limit information in bank parameter B, generating a deduction request message B. This message includes: Assuming the bank limit information is m and the deduction amount is n, the split result is: mod(n, m) transactions with m amounts and 1 transaction with rem(n, m) amounts. mod(n, m) represents rounding the result of n / m, and rem(n, m) represents the remainder of the result of n / m. The mod(n, m) + 1 transaction amount is saved to the deduction preparation table; then, a deduction request message B is generated based on the deduction preparation table.

[0035] The Deduction Preparation Table is used to store data and historical records for pending deductions. The interface fields are defined according to the payment deduction interface fields to facilitate subsequent deduction operations. Transaction statuses include: Success, Failure, Timeout, Waiting, and Running. The transaction status identifies the node in the lifecycle of the data.

[0036] Step 6: Call the payment module and execute the deduction operation based on the deduction request message A / B. Automatic deduction is performed immediately after the order is split. The deduction records found are polled and the deduction interface provided by the bank's unified payment system is called to finally collect the funds.

[0037] Furthermore, the method also includes: if the deduction operation fails, repeat it N times that day. If N times are exceeded, the deduction is stopped and the batch task fails. For example, deductions are divided into three batches each day (9:00, 14:00, and 20:00). This method can help customers deduct funds in a timely manner. For customers whose deductions fail due to insufficient balances, real-time text messages are sent to remind them to recharge promptly, reducing customer overdue rates. It also alleviates the pressure on the system for deductions, avoiding situations where timely deductions cannot be completed during the day and evening.

[0038] Furthermore, the method also includes obtaining the bank's daily limit based on bank parameter B. If the customer's daily debit amount exceeds the bank's daily limit, a grace period is triggered, during which the debit operation can continue. During this grace period, no interest or penalty interest will be accrued, and no credit report will be submitted. This approach improves the customer experience and avoids overdue credit reports due to special circumstances.

[0039] See also Figure 2 The method also includes synchronizing bank limit information, specifically:

[0040] 1) The bank limit synchronization task is started regularly. The enterprise online loan module notifies the payment module through the interface to obtain the bank limit information and upload it to the agreed directory.

[0041] 2) Clear the temporary table data. The enterprise online loan module downloads the bank limit information and stores it in the temporary table after analysis.

[0042] 3) Use Spring Batch to read the temporary table, perform logical cleansing, and save valid data to the limit table. Finally, retrieve data appropriate for the scenario based on factors such as bank and channel, and complete the limit refresh. This limit table stores information on products, banks, and bank limits, serving as the basis for intelligent order splitting.

[0043] Use Spring Batch to read temporary tables, including: Spring Batch comes with a centralized reader. Since it reads the content in the file, there is no need to customize the reader implementation. You can directly use FlatFileItemReader and configure it in the Batch config.

[0044] See also Figure 3 The method also includes synchronizing bank limit information. Specifically, when a change in bank limit information is detected, the payment module (i.e., the production module) sends a real-time message via the Kafka module. The enterprise online loan module builds a consumption module, pulls messages from the Kafka module's topic, and refreshes the local bank limit information in real time.

[0045] See also Figure 4 The producer module is connected to the Kafka module's input, the Kafka module's output is connected to the consumer module, and the consumer module's output is connected to the Kafka module via the Zookeeper module. During runtime, each piece of data is assigned an offset (sequence number) in order. The consumer module submits the offset to inform the Kafka module of the number of data items it has consumed. The Zookeeper module records the current consumption sequence number.

[0046] When the production module loses messages, use the producer.send(msg, callback) API to avoid message loss. Based on the callback, if a message submission fails, it can be handled in a targeted manner. If it is due to transient errors, the production module can simply retry.

[0047] When the consumer module loses data, it starts a single-threaded asynchronous consumption process. The consumer module uses an "offset" to indicate the current position in the topic partition. The Kafka module consumes messages first and then updates the offset to ensure that messages are not lost.

[0048] In a highly concurrent system, a sudden burst of high traffic often places significant pressure on the system. Kafka can help mitigate this peak traffic. For example, if 10,000 queries per second enter the system, these requests can be written to Kafka, and the backend can process the requests based on the load. Therefore, for an integrated project, decoupling is essential, and Kafka provides this functionality. For example, if System A and System B both need the latest quota information, they can simply call the Kafka producer and push the information into Kafka, ensuring the update is successful by default.

[0049] In order to clearly describe the technical solution of the present invention, the following is further explained with reference to specific cases:

[0050] 1. Real-time synchronization of bank single transaction limit data maintained by the payment system, and updating of local data in the enterprise online loan module for order splitting;

[0051] 2. On the due date, the system calculates that customer A needs to pay off the principal and interest for the period totaling 8,600 yuan. The system checks the balance in the customer's Type 2 account repayment account, which is 200 yuan. The system calculates that 8,400 yuan needs to be debited from the customer's card at another bank.

[0052] 3. The system checks and finds that the customer's debit card belongs to Industrial and Commercial Bank of China. The current single transaction limit for ICBC is 2,500 yuan. Therefore, the system splits the transaction into four transactions awaiting debit data, with the debit amounts being 2,500 yuan, 2,500 yuan, 2,500 yuan, and 900 yuan respectively.

[0053] 4. At 9:00 AM, customer A successfully deducts 2,500 yuan, but the remaining three transactions fail. This triggers a text message reminder, informing the customer to top up 5,900 yuan. At 2:00 PM, the deduction continues. If only 2,500 yuan is deducted, the remaining 3,400 yuan will fail due to bank limits. The deduction will continue the next day.

[0054] 5. At the end of the core day, the customer's partial repayment (5,000 yuan) is automatically deducted;

[0055] 6. The next day, continue with steps 1-3 to split the orders of 2,500 yuan and 900 yuan. Since no interest is accrued during the 3-day grace period, the deduction amount will not change. If the customer's loan note is overdue for more than 3 days, the daily deduction amount will change.

[0056] See also Figure 5 The present invention also discloses a smart fund deduction device applicable to multiple scenarios, including:

[0057] The configuration and maintenance module is used to configure and maintain core variables, including product parameters A, bank parameters B, and decision-making call parameters C.

[0058] The list query module is used to start batch tasks and query the list of IOUs involved in the deduction based on product parameter A.

[0059] The outstanding repayment query module is used to call the loan core module to query the outstanding repayment amount of each IOU on the IOU list.

[0060] The split order judgment module is used to determine whether the IOU supports splitting based on the decision calling parameter C. If so, it proceeds to the next step. If not, it directly generates the deduction request message A.

[0061] The order splitting module is used to call the deposit core module to query the account balance, calculate the deduction amount based on the outstanding amount and the account balance, split the deduction amount according to the bank limit information in the bank parameter B, and generate the deduction request message B.

[0062] The deduction execution module is used to call the payment module and perform the deduction operation according to the deduction request message A / B.

[0063] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0064] In summary, the beneficial effects of the present invention include: effectively splitting the bill based on the single transaction limit and daily limit of the bank to which the customer binds the card, as well as the current amount to be repaid by the customer at the bank to be repaid, and the program automatically executes the deduction step after the bill splitting is completed. The present invention has a full set of functions that can be fully automated, and does not require manual intervention to reduce manual operation and maintenance costs. It can meet the requirements of different scenarios for different products through multi-dimensional parameterized configuration, improve customer experience, solve customer pain points, and provide customers with better services. It covers various scenarios, and one-time design and development can meet the sharing of multiple products, reducing human development costs. Bank limit information is automatically updated in real time to avoid deduction failures due to bank limit updates.

[0065] It should be understood that if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0066] The technical scope of the present invention is not limited to the contents of the above description. Those skilled in the art can make various deformations and modifications to the above embodiments without departing from the technical idea of ​​the present invention, and these deformations and modifications should all fall within the protection scope of the present invention.

Claims

1. A smart fund deduction method applicable to multiple scenarios, running between the enterprise online loan module, loan core module, deposit core module and payment module, characterized in that: The steps include: Configure and maintain core variables, including product parameter A, bank parameter B, and decision-making parameter C; Start a batch task and query the list of IOUs involved in the deduction based on the product parameter A; Calling the loan core module to query the outstanding amount of each IOU on the IOU list; Based on the decision call parameter C, determine whether the IOU supports splitting. If so, proceed to the next step. If not, directly generate a deduction request message 1; Call the deposit core module to query the account balance, calculate the deduction amount based on the outstanding amount and the account balance, split the deduction amount into orders based on the bank limit information in the bank parameter B, and generate a deduction request message 2; Call the payment module and perform the deduction operation according to the deduction request message 1 / 2; It also includes the scheduled synchronization of the bank limit information, specifically: the bank limit synchronization task is started regularly, the enterprise online loan module notifies the payment module through the interface to obtain the bank limit information, and uploads it to the agreed directory; the temporary table data is cleared, the enterprise online loan module downloads the bank limit information, and stores it in the temporary table after parsing; Spring Batch is used to read the temporary table, perform data cleaning logic, and save the valid data to the limit table; It also includes real-time synchronization of the bank limit information. Specifically, when the bank limit information is detected to have changed, the payment module sends a message in real time through the Kafka module; the enterprise online loan module builds a consumption module, pulls messages from the topic of the Kafka module, and refreshes the local bank limit information in real time.

2. The intelligent fund deduction method applicable to multiple scenarios according to claim 1 is characterized in that: Also includes: After the deduction operation fails, it will be repeated N times on the same day. After exceeding N times, the deduction will be stopped and the batch task will fail.

3. The intelligent fund deduction method applicable to multiple scenarios according to claim 1 is characterized in that: Also includes: According to the bank parameter B, the bank's daily limit is obtained. If the customer's deduction amount on that day exceeds the bank's daily limit, a grace period is triggered. The deduction operation will continue during the grace period. No interest or penalty interest will be calculated during the grace period, and the amount will not be reported to the credit bureau.

4. The intelligent fund deduction method applicable to multiple scenarios according to claim 1 is characterized in that: The deduction amount is the difference between the amount to be repaid and the account balance.

5. The intelligent fund deduction method applicable to multiple scenarios according to claim 1 is characterized in that: The deduction amount is split according to the bank limit information in the bank parameter B, and a deduction request message 2 is generated, including: Assume the bank limit information is m, and the deduction amount is n. The result after splitting the order is: mod(n, m) transactions with m amount and 1 transaction with rem(n, m) amount. Save the amount mod(n, m)+1 to the withholding preparation table; Generate a deduction request message 2 according to the deduction preparation table.

6. The intelligent fund deduction method applicable to multiple scenarios according to claim 1 is characterized in that: The message body of the deduction request message includes a name, type, description and instructions for use.

7. A smart fund deduction device applicable to multiple scenarios, characterized by: include: A configuration and maintenance module is used to configure and maintain core variables, including product parameter A, bank parameter B, and decision-making call parameter C; A list query module is used to start a batch task and query the list of IOUs involved in the deduction based on the product parameter A; The outstanding repayment query module is used to call the loan core module to query the outstanding repayment amount of each IOU on the IOU list; A splitting judgment module is used to judge whether the IOU supports splitting based on the decision calling parameter C. If so, it proceeds to the next step; if not, it directly generates a deduction request message 1; A splitting module is used to call the deposit core module to query the account balance, calculate the deduction amount based on the outstanding amount and the account balance, split the deduction amount based on the bank limit information in the bank parameter B, and generate a deduction request message 2; A deduction execution module is used to call the payment module and perform a deduction operation according to the deduction request message 1 / 2; It also includes the scheduled synchronization of the bank limit information, specifically: the bank limit synchronization task is started regularly, the enterprise online loan module notifies the payment module through the interface to obtain the bank limit information, and uploads it to the agreed directory; the temporary table data is cleared, the enterprise online loan module downloads the bank limit information, and stores it in the temporary table after parsing; Spring Batch is used to read the temporary table, perform data cleaning logic, and save the valid data to the limit table; It also includes real-time synchronization of the bank limit information. Specifically, when the bank limit information is detected to have changed, the payment module sends a message in real time through the Kafka module; the enterprise online loan module builds a consumption module, pulls messages from the topic of the Kafka module, and refreshes the local bank limit information in real time.

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