Bulk commodity transaction service center management background system

Abstract

The invention relates to the technical field of transaction management, and discloses a bulk commodity transaction service center management background system, which comprises a transaction data management module used for collecting order data, transaction data and market data in a bulk commodity transaction process in real time, carrying out format standardization processing on the data and then storing the data to a distributed database, multi-condition query and data export according to transaction varieties, transaction time periods and transaction subject dimensions are supported; order data, transaction data and market information data in an order can be visually known and searched in a later period through the transaction data management module, data integration can be carried out inside, the burden of the system is reduced, the operation of a background system is enhanced, real-time transaction control and transaction data processing are carried out through the risk control module, and the risk management efficiency is improved. According to the intelligent logistics supervision system, the problems of later transaction are reduced, the market loss is reduced, transportation path optimization, multi-warehouse collaborative management and real-time inventory monitoring are realized through the intelligent logistics supervision system, and the logistics cost and resource waste are reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of transaction management, in particular to a bulk commodity transaction service center management background system. BACKGROUND

[0002] As the basic material of the national economy, the transaction scale of bulk commodities is huge, the participating subjects are diverse (covering production enterprises, traders, financial institutions, etc.), and the transaction process involves order negotiation, fund settlement, warehouse management, logistics transportation and other links, which requires high professionalism, safety and efficiency of transaction management; The particularity of the current bulk commodity transaction (such as large transaction amount, long delivery period, frequent price fluctuation, and multiple related links) makes the dependence of the transaction service center on the background management system far exceed that of the ordinary commodity transaction platform. The background management system not only needs to realize the centralized management of transaction data, but also needs to link up fund settlement, warehouse logistics, risk control and other multi-dimensional businesses to form a whole-process closed-loop management. Therefore, the existing background management system needs to solve the problems of multi-system collaboration and risk control, and in order to ensure the accuracy of personnel work at each stage, the control of authority is required to avoid the problem of finding no one responsible when the staff makes a mistake.

[0003] In view of the above problems, a bulk commodity transaction service center management background system is proposed. SUMMARY

[0004] The purpose of the present application is to provide a bulk commodity transaction service center management background system, which solves the problems mentioned in the background art.

[0005] To achieve the above object, the present application provides the following technical solutions: the bulk commodity transaction service center management background system, comprising: a transaction data management module, used for real-time collection of order data, transaction data and market data in the bulk commodity transaction process, storage of the data to a distributed database after format standardization processing, and support of multi-condition query and data export according to transaction varieties, transaction time periods and transaction subjects; a risk control module, used for user registration information auditing, account state management, transaction permission configuration and user credit level evaluation, dynamic risk monitoring of transaction orders based on preset risk thresholds and real-time transaction data; a settlement management module, connected with a bank settlement system, used for automatic calculation of payable / receivable amounts of transaction parties according to transaction data, generation of a settlement list and completion of fund transfer instruction issuing, and recording of settlement process logs for audit tracing; a warehousing and logistics docking module, used for data intercommunication with third-party warehousing systems and logistics transportation systems through API interfaces, acquisition of bulk commodity inventory state data and logistics transportation track data, association of the data with transaction orders, and realization of collaborative management of transaction, warehousing and logistics data; and a system permission management module, used for configuration of differentiated function access permissions and data viewing permissions for system users of different roles based on an RBAC (Role-Based Access Control) model, and support of real-time recording of operation logs and abnormal operation tracing, realization of function permission and data field level isolation of roles such as traders, risk controllers and auditors.

[0006] As a further description of the above technical solutions: the transaction data management module comprises a multi-source data collection unit, a data cleaning unit, a data verification unit and a data synchronization unit, the multi-source data collection unit collects negotiation communication data, order modification log data and abnormal transaction marking data in addition to order data, transaction data and market data, the negotiation communication data comprises online message records and voice communication transcribed texts of both parties, the order modification log data records fields, content before and after modification and modification operators of each modification after order creation, the data cleaning unit processes missing values by using a sliding window algorithm, identifies abnormal quotation data by using K-means clustering for elimination of redundant data and abnormal data in transaction data, and completes missing data, then the transaction data passing the verification of the data verification unit and the data synchronization unit are synchronized to the distributed database, and real-time data synchronization with the transaction front-end system is realized.

[0007] As a further description of the above technical solution: The risk control module adopts an intelligent risk control engine, which automatically triggers risk warnings and generates disposal suggestions based on a preset rule base (such as price fluctuation thresholds and transaction frequency limits) and machine learning models (such as abnormal transaction detection algorithms). Through risk threshold configuration units, real-time monitoring units, risk warning units, and risk disposal units, it can customize risk monitoring indicators and corresponding thresholds according to different commodity varieties, trading modes, and credit ratings of trading entities. Then, it continuously monitors real-time transaction data through a streaming computing framework, compares the transaction data with preset risk thresholds in real time, and automatically generates different types of warning information according to the risk level when the transaction data triggers the risk threshold. The warning information includes SMS warnings, system pop-up warnings, and email warnings. In conjunction with the system permission management module, it provides disposal functions such as risk transaction freezing, transaction limit adjustment, and forced liquidation. All risk disposal operations must record the operator, operation time, and operation reason.

[0008] As a further description of the above technical solution: the intelligent risk control engine of the risk control module adopts the following process structure: A [Data Access] --> B{Rule Set 1} B -->|Pass| C [Decision Matrix] B -->|Reject| E [Final Review Interception] C --> D{Model Scoring} D -->|High Risk| ED -->|Low Risk| F [Manual Review].

[0009] As a further description of the above technical solution: the warehousing and logistics docking module includes a warehousing data interface unit, a logistics data interface unit, and a data association unit; it uses a standardized API interface to interface with a third-party warehousing system to obtain real-time data on bulk commodity inbound, outbound, inventory counts, GPS positioning data, and logistics platform data, and obtain real-time location, transport vehicle information, and estimated arrival time during the transportation of bulk commodities; then, through the data association unit, the obtained warehousing data and logistics data are associated and bound with the corresponding transaction orders through order numbers, realizing full-process data visualization and tracking from transaction orders to warehousing delivery and logistics transportation.

[0010] As a further description of the above technical solution: The system permission management module is equipped with an operation audit unit, which records all user operation logs and uses blockchain technology to achieve tamper-proof evidence storage. The operation logs include operation time, operator, operation module, operation content and operation result, and the operation logs are tamper-proof and support querying and exporting by time range, operator and operation module.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The bulk commodity trading service center management backend system provided by this invention allows for intuitive understanding and subsequent retrieval of order data, transaction data, and market data through the transaction data management module. It also enables internal data integration, reducing the system's burden and enhancing the operation of the backend system.

[0012] 2. The bulk commodity trading service center management back-end system provided by this invention can control transactions in real time and process transaction data through a risk control module, thereby reducing the occurrence of problems in later transactions and reducing market losses. Through an intelligent logistics supervision system, it can optimize transportation routes, manage multiple warehouses collaboratively, and monitor inventory in real time, thereby reducing logistics costs and resource waste. Attached Figure Description

[0013] Figure 1 This is a system module diagram of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0015] To further understand the content of this invention, a detailed description of the invention will be provided in conjunction with the accompanying drawings.

[0016] Combination Figure 1The bulk commodity trading service center management backend system includes: a transaction data management module, used to collect order data, transaction data, and market data in real time during the bulk commodity trading process, standardize the data format, and store it in a distributed database, supporting multi-condition queries and data export by trading variety, trading time period, and trading entity; a risk control module, which reviews user registration information, manages account status, configures trading permissions, and assesses user credit ratings, and dynamically monitors trading orders based on preset risk thresholds and real-time transaction data; a settlement management module, which interfaces with the bank settlement system, automatically calculates the payable / receivable amounts of all parties involved in the transaction based on transaction data, generates settlement lists, and issues fund transfer instructions, while recording settlement process logs for audit traceability; and a warehousing and logistics integration module, which connects via API. The interface enables data exchange with third-party warehousing and logistics systems to obtain inventory status data and logistics trajectory data of bulk commodities, and associates the data with transaction orders to achieve collaborative management of transaction, warehousing, and logistics data. The system permission management module, based on the RBAC (role-based access control) model, configures differentiated function access permissions and data viewing permissions for system users with different roles, and supports real-time recording of operation logs and traceability of abnormal operations, realizing functional permissions and data field-level isolation for roles such as traders, risk controllers, and auditors.

[0017] Combination Figure 1 The transaction data management module includes a multi-source data acquisition unit, a data cleaning unit, a data verification unit, and a data synchronization unit. The multi-source data acquisition unit collects order data, transaction data, and market data, as well as negotiation and communication data, order modification log data, and abnormal transaction marker data during the transaction process. The negotiation and communication data includes online message records and transcripts of voice communications between the transacting parties. The order modification log data records the fields modified each time an order is created, the content before and after the modification, and the person who performed the modification. The data cleaning unit uses a sliding window algorithm to process missing values ​​and uses K-means clustering to identify abnormal price data to remove redundant and abnormal data from the transaction data, and completes missing data. Then, the transaction data that passes verification through the data verification unit and the data synchronization unit is synchronized to the distributed database, simultaneously achieving real-time data synchronization with the transaction front-end system.

[0018] Combination Figure 1The risk control module employs an intelligent risk control engine, based on a preset rule base (such as price fluctuation thresholds and transaction frequency limits) and machine learning models (such as abnormal transaction detection algorithms). It automatically triggers risk warnings and generates handling suggestions. Through risk threshold configuration units, real-time monitoring units, risk warning units, and risk handling units, it allows for customized setting of risk monitoring indicators and corresponding thresholds based on different commodity types, trading models, and the credit rating of trading entities. Then, a streaming computing framework continuously monitors real-time transaction data, comparing it in real-time with preset risk thresholds. When transaction data triggers a risk threshold, it automatically generates different types of warning information based on the risk level. These warnings include SMS warnings, system pop-up warnings, and email warnings. In conjunction with the system permission management module, it provides functions such as freezing risky transactions, adjusting transaction limits, and forced liquidation. All risk handling operations must record the operator, operation time, and reason for the operation. A[Data Access] --> B{Rule Set 1} B -->|Pass| C[Decision Matrix] B -->|Reject| E[Final Review Interception] C --> D{Model Score} D -->|High Risk| ED -->|Low Risk| F [Manual Review].

[0019] Combination Figure 1 The warehousing and logistics integration module includes a warehousing data interface unit, a logistics data interface unit, and a data association unit. It uses a standardized API interface to connect with third-party warehousing systems, obtaining real-time data on bulk commodity inbound and outbound shipments, inventory counts, GPS positioning data, and logistics platform data. It also obtains real-time location, vehicle information, and estimated arrival time of bulk commodities during transportation. Then, through the data association unit, the obtained warehousing and logistics data are linked and bound to the corresponding transaction orders using order numbers, realizing full-process data visualization and tracking from transaction orders to warehousing delivery and logistics transportation.

[0020] The working principle involves a multi-source data acquisition unit collecting order data, transaction data, and market data. It also transcribes online messages and voice communications into text. The order modification log records every modified field, the content before and after modification, and the operator of the modification after order creation. This log is used to remove redundant and abnormal data from the transaction data and to complete missing data. The transaction data, verified by the data verification and synchronization units, is then synchronized to a distributed database. Simultaneously, it achieves real-time data synchronization with the transaction front-end system before transactions are initiated. During the transaction process, the risk control module pre-sets risk thresholds, monitors the transaction data, and provides feedback to staff within the system's access control module. Staff then perform operations, log the operations, and proceed with shipment. After shipment, the system interfaces with a third-party warehousing system to obtain real-time data on bulk commodity inbound and outbound shipments, inventory counts, and logistics tracking, and completes the backend records.

[0021] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A commodity trading service center management back office system, characterized by: Comprise: A transaction data management module for real-time collection of order data, transaction data and market data during commodity trading, standardization of the data, storage in a distributed database, and support for multi-condition queries and data export by transaction type, transaction period, and transaction subject; A risk control module for user registration information review, account status management, transaction permission configuration, and user credit level assessment, dynamic risk monitoring of transaction orders based on preset risk thresholds and real-time transaction data; A settlement management module for interfacing with a bank settlement system, automatic calculation of payable / receivable amounts for each party based on transaction data, generation of a settlement list and completion of fund transfer instructions, and recording of settlement process logs for audit and traceability; A warehouse logistics interface module for data exchange with third-party warehouse systems and logistics transportation systems through API interfaces, acquisition of commodity inventory data and logistics transportation trajectory data, association of the data with transaction orders, and collaborative management of transaction, warehouse, and logistics data; A system permission management module based on the RBAC (Role-Based Access Control) model for configuring differentiated function access permissions and data viewing permissions for different roles, real-time recording of operation logs, and abnormal operation traceability, and function permission and data field level isolation for roles such as traders, risk control personnel, and auditors.

2. The commodity trading service center management back office system of claim 1, wherein: The transaction data management module includes a multi-source data collection unit, a data cleaning unit, a data verification unit, and a data synchronization unit. The multi-source data collection unit collects negotiation and communication data, order modification log data, and abnormal transaction marker data in addition to order data, transaction data, and market data. The negotiation and communication data includes online message records and voice communication transcripts between the two parties. The order modification log data records the fields modified, the content before and after modification, and the modification operator after the order is created. The data cleaning unit uses a sliding window algorithm to handle missing values and identifies abnormal bid data through K-means clustering to remove redundant and abnormal data in the transaction data and complete the missing data. The transaction data that passes the verification of the data verification unit and the data synchronization unit is synchronized to the distributed database, and real-time data synchronization with the transaction front-end system is realized.

3. The commodity trading service center management back office system of claim 1, wherein: The risk control module adopts an intelligent risk control engine, based on a preset rule base (such as a price fluctuation threshold, a transaction frequency limit) and a machine learning model (such as an abnormal transaction detection algorithm), to automatically trigger risk early warning and generate disposal suggestions, through a risk threshold configuration unit, a real-time monitoring unit, a risk early warning unit and a risk disposal unit, to realize self-defined setting of risk monitoring indicators and corresponding thresholds according to different bulk commodity varieties, transaction modes and transaction subject credit levels, and then to perform uninterrupted monitoring on real-time transaction data through a stream computing framework, to compare transaction data with preset risk thresholds in real time, to automatically generate different types of early warning information according to risk levels when transaction data triggers risk thresholds, the early warning information including SMS early warning, system pop-up window early warning and email early warning, to provide risk transaction freezing, transaction limit adjustment, forced liquidation and other disposal functions in cooperation with the system permission management module, and all risk disposal operations need to record the operator, operation time and operation reason.

4. The commodity trading service center management back office system of claim 3, wherein: The intelligent risk control engine of the risk control module adopts the following process structure: A [data access] --> B {rule set 1} B -->| through | C [decision matrix] B -->| reject | E [final review interception] C --> D {model score} D -->| high risk | E D -->| low risk | F [manual review].

5. The commodity trading service center management back office system of claim 1, wherein: The warehouse logistics docking module includes a warehouse data interface unit, a logistics data interface unit and a data association unit; it adopts a standardized API interface to dock with a third-party warehouse system, to obtain real-time warehouse data, warehouse-out data, inventory data and GPS positioning data interfaces and logistics platform interfaces of bulk commodities, to obtain real-time positions, transportation vehicle information and expected arrival time of bulk commodities during transportation; Then through the data association unit, the obtained warehouse data, logistics data and corresponding transaction orders are associated and bound through order numbers, to realize full-process data visual tracking from transaction orders to warehouse delivery and logistics transportation.

6. The commodity trading service center management back office system of claim 1, wherein: The system permission management module is internally provided with an operation audit unit to record all user operation logs, and to realize tamper-proof storage through blockchain technology, the operation logs including operation time, operator, operation module, operation content and operation result, and the operation logs being unalterable, supporting query and export according to time range, operator and operation module.

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