Credit line adjusting method and device, electronic equipment and computer program product

Abstract

The invention discloses a credit line adjusting method and device, electronic equipment and a computer program product. Relates to the field of financial science and technology, and comprises the following steps: obtaining product data of a product produced by a target institution, and extracting financial data of M raw materials required for producing the product from the product data, M being a positive integer; the financial data of the product is calculated according to the financial data of the M raw materials, the demand change rate of the product is calculated based on the financial data of the product, and the demand change rate is obtained based on the combination of the sub-demand change rates of the M raw materials; and determining a risk adjustment strategy of the target institution based on the demand change rate of the product, and adjusting the credit line of the target institution according to the risk adjustment strategy. According to the method and the device, the technical problem of low adjustment accuracy when the credit line of the target mechanism is adjusted in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of financial technology, and more specifically, to a method, apparatus, electronic device, and computer program product for adjusting credit limits. Background Technology

[0002] In today's rapidly changing market environment, financial institutions face the challenge of effectively supporting the healthy development of SMEs while ensuring the safety of their own assets. Traditional methods, due to inherent limitations such as assessment lags and insufficient demand forecasting, result in financial institutions providing SMEs with relatively low financial parameters. This not only restricts the size of these businesses but also increases the risks faced by financial institutions during market fluctuations.

[0003] Small and medium-sized enterprises (SMEs), especially manufacturing companies, often rely on inventory or finished goods for financial transactions to meet their working capital needs. However, when valuing these inventories, financial institutions typically rely on historical prices or static valuation methods, failing to promptly assess changes in demand and ultimately failing to adjust relevant financial parameters in a timely manner, leading to increased risk. Furthermore, because the product information submitted by SMEs can cover a variety of different raw materials, and the demand for these raw materials varies, it is also difficult to effectively adjust financial parameters.

[0004] There is currently no effective solution to the technical problem of low accuracy in adjusting credit limits for target institutions in related technologies. Summary of the Invention

[0005] The main objective of this application is to provide a method, apparatus, electronic device, and computer program product for adjusting credit limits, in order to solve the technical problem of low accuracy in adjusting credit limits of target institutions in related technologies.

[0006] To achieve the above objectives, according to one aspect of this application, a method for adjusting credit limits is provided. The method includes: acquiring product data of a product manufactured by a target institution, and extracting financial data of M types of raw materials required for the production of the product from the product data, where M is a positive integer; calculating financial data of the product based on the financial data of the M types of raw materials, and calculating the demand change rate of the product based on the financial data of the product, wherein the demand change rate is obtained based on a combination of sub-demand change rates of the M types of raw materials; determining a risk adjustment strategy for the target institution based on the demand change rate of the product, and adjusting the credit limit of the target institution according to the risk adjustment strategy.

[0007] Furthermore, extracting financial data for the M types of raw materials required for product production from the product data includes: formatting the product data to obtain processed product data, and determining whether the M types of raw materials in the product belong to a preset type; if the M types of raw materials belong to the preset type, obtaining a component mapping table, and extracting financial data from the processed product data based on the component mapping table; if any raw material does not belong to the preset type, obtaining cost data for Y types of raw materials that do not belong to the preset type, and determining the Y cost data and MY cost data as the financial data of the raw materials, where Y is less than or equal to M and Y is a positive integer.

[0008] Furthermore, calculating the product's financial data based on the financial data of M raw materials includes: obtaining the cost data of the M raw materials over a historical period from the financial data of the M raw materials, obtaining a cost list, and obtaining the proportion of the M raw materials in the product; and calculating the product's financial data based on the M cost data in the cost list and the proportion of the M raw materials in the product.

[0009] Furthermore, calculating the product demand change rate based on the product's financial data includes: extracting product coefficients for M types of raw materials from the forecast parameter table to obtain M product coefficients, and obtaining the proportion of the M types of raw materials in the product; for a raw material, calculating the demand change rate of the raw material based on the raw material's product coefficient, the raw material's proportion, and the product's financial data to obtain the sub-demand change rate of the raw material; obtaining the product's preset demand growth rate, calculating the sum of the preset demand growth rate and the M sub-demand change rates to obtain the demand change rate.

[0010] Furthermore, calculating the demand change rate of raw materials based on the product coefficient of raw materials, the proportion of raw materials, and the financial data of products includes: obtaining the value threshold of raw materials and obtaining the initial value of raw materials; determining the change probability value based on the ratio of the initial value to the value threshold; and determining the sub-demand change rate of raw materials based on the product coefficient, the proportion of raw materials, and the change probability value.

[0011] Furthermore, determining the risk adjustment strategy for the target institution based on the product's demand change rate includes: obtaining a risk strategy matrix; extracting the adjustment ratio values ​​of the M raw materials from the risk strategy matrix based on the sub-demand change rates of the M raw materials in the demand change rate; calculating the product of the adjustment ratio values ​​of the M raw materials and the product's financial data to obtain the quota data of the M raw materials; calculating the adjustment amount of the M raw materials based on the adjustment ratio values ​​and quota data of the M raw materials; and constructing a risk adjustment strategy based on the adjustment amount of the M raw materials.

[0012] Furthermore, after determining the target institution's risk adjustment strategy based on the product's demand change rate, the method further includes: obtaining the adjustment ratio values ​​and adjustment amounts of M types of raw materials, and obtaining the financial transaction coefficient and initial transaction rate; calculating the product of the adjustment ratio values ​​and financial transaction coefficients of the M types of raw materials to obtain the financial product; calculating the sum of the financial product and the initial transaction rate to obtain financial transaction data; calculating the product of the financial transaction data and the adjustment amounts of the M types of raw materials to obtain transaction limit data; and sending a prompt message to the target institution when the transaction limit data is less than or equal to the target institution's historical limit data, wherein the prompt message is used to prompt the target institution to adjust the quantity of products.

[0013] To achieve the above objectives, according to another aspect of this application, a credit limit adjustment apparatus is provided. The apparatus includes: a first acquisition unit, configured to acquire product data of a product manufactured by a target institution, and extract financial data of M types of raw materials required for the production of the product from the product data, wherein M is a positive integer; a first calculation unit, configured to calculate the financial data of the product based on the financial data of the M types of raw materials, and calculate the demand change rate of the product based on the financial data of the product, wherein the demand change rate is obtained based on a combination of sub-demand change rates of the M types of raw materials; and a determination unit, configured to determine the risk adjustment strategy of the target institution based on the demand change rate of the product, and adjust the credit limit of the target institution according to the risk adjustment strategy.

[0014] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform any of the above-described credit limit adjustment methods.

[0015] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory storing an executable program, and the processor for running the program, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any of the above-described methods for adjusting the credit limit.

[0016] According to another aspect of the present invention, a computer program product is also provided, the computer program product including a computer program, wherein when the computer program is executed by a processor, it implements any of the above-described methods for adjusting the credit limit.

[0017] In this embodiment, a method for adjusting credit limits is adopted. This involves acquiring product data of the target institution's manufactured products and extracting financial data for M types of raw materials required for product production from the product data, where M is a positive integer. Financial data of the product is calculated based on the financial data of the M raw materials, and the demand change rate of the product is calculated based on this financial data. This demand change rate is obtained by combining the sub-demand change rates of the M raw materials. A risk adjustment strategy for the target institution is determined based on the product's demand change rate, and the credit limit of the target institution is adjusted accordingly. This solves the technical problem of low adjustment accuracy when adjusting credit limits for target institutions in related technologies. By acquiring financial data of the raw materials of the target institution's manufactured products, calculating the product's financial data based on the raw material financial data, calculating the product's demand change rate based on the product's financial data, and determining the risk adjustment strategy and credit limit of the target institution based on the product's demand change rate, the technical effect of improving the adjustment accuracy when adjusting the credit limit of the target institution is achieved. Attached Figure Description

[0018] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0019] Figure 1 This is a hardware structure block diagram of a computer terminal (or mobile device) used to implement a method for adjusting credit limits;

[0020] Figure 2 This is a flowchart of a method for adjusting credit limits according to an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of a credit limit adjustment system provided according to an embodiment of this application;

[0022] Figure 4 This is a schematic diagram of a credit limit adjustment device provided according to an embodiment of this application;

[0023] Figure 5 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] It should be noted that all information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this application are information and data authorized by the user or fully authorized by all parties. For example, this system has interfaces with relevant users or organizations to provide users with corresponding operation data for them to choose to agree to or refuse automated decision-making results. Before obtaining relevant information, a request for obtaining the information needs to be sent to the aforementioned user or organization through the interface, and the relevant information is obtained after receiving consent from the aforementioned user or organization; if the user chooses to refuse, the expert decision-making process is initiated. Users can view the purpose of data use in real time through authorization decoding and have the right to withdraw authorization or delete data at any time. After the authorization is withdrawn, the system will terminate the relevant data processing within 24 hours.

[0027] It should be noted that the information collected in this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation access points for users to choose to authorize use or refuse use.

[0028] Example 1

[0029] According to an embodiment of this application, a method embodiment for adjusting a credit limit is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 This is a hardware structure block diagram of a computer terminal (or mobile device) used to implement a method for adjusting credit limits, such as... Figure 1 As shown, computer terminal 10 (or mobile device) may include one or more ( Figure 1 The processor 102 (which may include, but is not limited to, a microprocessor MCU (Microcontroller Unit) or a programmable gate array (FPGA)) is shown as 102a, 102b, ..., 102n. It also includes a memory 104 for storing data and a transmission device 106 for communication functions. In addition, it may include: a display, an input / output interface, a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a keyboard, a cursor control device, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0031] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0032] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the credit limit adjustment method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned credit limit adjustment method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0033] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network interface controller (NIC) and a network interface, which can be connected to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a radio frequency (RF) module, used for wireless communication with the Internet.

[0034] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0035] Under the aforementioned operating environment, this application provides the following: Figure 2 The method for adjusting the credit limit is shown. Figure 2 This is a flowchart of the credit limit adjustment method provided in the embodiments of this application, such as... Figure 2 As shown, the method includes the following steps:

[0036] Step S201: Obtain product data of the products produced by the target institution, and extract financial data of M types of raw materials required for the production of the products from the product data, where M is a positive integer.

[0037] It should be noted that the target institution can refer to a company applying for a financial transaction, such as a manufacturing company. Product data refers to the detailed information submitted by the target institution to the financial institution regarding its manufactured products, which may include the product name, cost structure, and types of raw materials. After obtaining the product data, the different raw materials contained in the product can be extracted, and the corresponding financial data can be obtained through the material information of these raw materials. This financial data may include unit cost data and transaction volume of the raw materials, which can be used for subsequent value assessment and risk analysis.

[0038] It should be noted that when extracting raw materials for generating products, raw materials that are traded in the futures market can be extracted. The price fluctuations of these raw materials are more predictable and actionable, thereby allowing for the estimation of the future value of the product and helping financial institutions make more accurate risk management and decisions.

[0039] Step S202: Calculate the product's financial data based on the financial data of the M raw materials, and calculate the product's demand change rate based on the product's financial data, wherein the demand change rate is obtained based on the combination of sub-demand change rates of the M raw materials.

[0040] Specifically, after obtaining the financial data of various raw materials required for the product, the dynamic changes in the overall value of the product can be calculated based on the raw material financial data, that is, the product's financial data can be obtained. This data can reflect the dynamic changes in product costs, that is, the value changes affected by raw material price fluctuations, and can be calculated by the following formula: Financial data = Initial product valuation (initial financial data) × (∑(material benchmark value × material weight × current price index)) / (∑(material benchmark value × material weight)), where benchmark value = unit price of raw materials; price index = current futures price / benchmark futures price.

[0041] Furthermore, the degree of change in future demand relative to current demand can be calculated based on the product's financial data, i.e., the rate of change in product demand can be calculated. This rate of change in demand is based on changes in raw material prices and the product's price sensitivity, and can predict future fluctuations in the product. It can be obtained by combining the impact rate of each raw material's price change on product demand (i.e., sub-demand change rate). The sub-demand change rate of each raw material can be determined based on the price change rate ((current price / benchmark price) / benchmark price), the price demand sensitivity coefficient, and the material's weight in the product. It should be noted that when combining the sub-demand change rates, the weighted average of the sub-demand change rates of all raw materials can be taken, combined with the base growth rate, to obtain the overall product demand change rate, which can be calculated using the following formula: Demand Change Rate = Base Growth Rate + ∑(Material Price Change Rate × Price Sensitivity Coefficient × Material Weight).

[0042] Step S203: Determine the risk adjustment strategy for the target institution based on the product demand change rate, and adjust the credit limit of the target institution according to the risk adjustment strategy.

[0043] Specifically, after obtaining the product demand change rate, since the demand change rate reflects the percentage change in future demand relative to current demand, the market demand risk that the target institution's product may face can be assessed. Furthermore, based on the product demand change rate, the financial institution's risk adjustment strategy for the target institution can be assessed, such as how to adjust risk management measures, whether to hedge, the hedging ratio, and the specific hedging operation methods.

[0044] Furthermore, after obtaining the risk adjustment strategy, the credit line of the target institution can be adjusted according to the risk adjustment strategy. The credit line refers to the maximum amount that the financial institution is willing to provide. For example, if the rate of change in product demand indicates a decline in demand, the financial institution can assess it as a higher risk level and adopt a risk adjustment strategy with a lower credit line. Conversely, if product demand is stable or expected to rise, a risk level of lower risk can be achieved by choosing a risk adjustment strategy with a higher credit line. The credit line can be calculated using the following formula: Credit Line = Current Valuation × [Base Collateral Ratio + Additional Dynamic Collateral Coefficient × (1 - Hedging Ratio)].

[0045] The credit limit adjustment method provided in this application embodiment obtains product data of the products produced by the target institution and extracts financial data of M kinds of raw materials required for the production of the products from the product data, where M is a positive integer; calculates the financial data of the products based on the financial data of the M kinds of raw materials, and calculates the demand change rate of the products based on the financial data of the products, where the demand change rate is obtained based on the combination of sub-demand change rates of the M kinds of raw materials; determines the risk adjustment strategy of the target institution based on the demand change rate of the products, and adjusts the credit limit of the target institution according to the risk adjustment strategy. This solves the technical problem of low adjustment accuracy when adjusting the credit limit of the target institution in related technologies. By obtaining the financial data of the raw materials of the products produced by the target institution, calculating the financial data of the products based on the financial data of the raw materials, calculating the demand change rate of the products based on the financial data of the products, and determining the risk adjustment strategy and the credit limit of the target institution based on the demand change rate of the products, the method achieves the technical effect of improving the adjustment accuracy when adjusting the credit limit of the target institution.

[0046] Optionally, in the credit limit adjustment method provided in this application embodiment, extracting financial data of M types of raw materials required for product production from product data includes: formatting the product data to obtain processed product data, and determining whether the M types of raw materials in the product belong to a preset type; if the M types of raw materials belong to the preset type, obtaining a component mapping table, and extracting financial data from the processed product data based on the component mapping table; if any raw material does not belong to the preset type, obtaining cost data of Y types of raw materials that do not belong to the preset type, and determining the Y cost data and MY cost data as the financial data of the raw materials, where Y is less than or equal to M and Y is a positive integer.

[0047] Specifically, to improve the accuracy of credit limits, the product data should first be formatted after acquisition to ensure that information such as the material name, weight, and unit cost of each raw material is stored in a uniform format, facilitating subsequent analysis and mapping. Simultaneously, by determining whether the raw materials in the product are pre-defined types that can be traded on the futures market, the financial institution can identify which raw materials can effectively predict and hedge against price fluctuations, laying the foundation for subsequent dynamic valuation and risk management.

[0048] For multiple raw materials belonging to a preset type, a component mapping table can be invoked. Based on this table, corresponding futures market financial data, such as futures prices and price indices, can be accurately extracted from the processed product data for subsequent valuation and risk analysis. This component mapping table stores the mapping relationship between raw materials and futures contracts, and may include the benchmark price of the raw material and the current futures price index. For raw materials not belonging to a preset type, their cost data can be directly extracted from the provided product data. This means that subsequent valuation can be performed using unit costs and other market information, and these costs can be combined with the financial data of raw materials belonging to the preset type to form the raw material's financial data for further analysis.

[0049] This embodiment, by processing and utilizing product data, can not only analyze raw materials belonging to a preset type, but also properly handle raw materials that do not belong to the preset type, ensuring that the cost information of all raw materials is taken into account. This not only enhances flexibility and adaptability, but also effectively improves the accuracy of product valuation and the risk management capabilities of financial institutions, while ensuring the safety of financial institution assets.

[0050] Optionally, in the method for adjusting the credit limit provided in this application embodiment, calculating the product's financial data based on the financial data of M types of raw materials includes: obtaining the cost data of the M types of raw materials in a historical time period from the financial data of the M types of raw materials, obtaining a cost list, and obtaining the proportion of the M types of raw materials in the product; and calculating the product's financial data based on the M cost data in the cost list and the proportion of the M types of raw materials in the product.

[0051] Specifically, to calculate the financial data of a product, one can first obtain the latest price data of raw materials in the futures market and other financial indicators, that is, obtain the financial data of each raw material. Then, the cost data of each raw material over a historical period, such as past unit costs, can be obtained to form a cost list. At the same time, the proportion of each raw material in the product can be obtained through product data, that is, the weight of each raw material in the cost structure, which reflects its importance in the product value.

[0052] Furthermore, based on the cost data in the cost list and combined with the proportion of raw materials, the product's financial data is calculated using a dynamic valuation method. It can be obtained by the following formula: Product Financial Data = Initial Valuation × (∑(Material Benchmark Value × Material Weight × Current Futures Price Index)) / (∑(Material Benchmark Value × Material Weight)), where the material benchmark value is the historical cost data, the material weight is the proportion of raw materials, and the current futures price index is the latest price index obtained from the raw material financial data.

[0053] This embodiment calculates the product's financial data based on relevant raw material data, overcoming the lag of traditional static assessment. It can react to market changes more quickly, ensuring the rationality of the assessment results and avoiding the situation where changes in the price of a single raw material have an excessive impact on the product's value assessment.

[0054] Optionally, in the credit limit adjustment method provided in this application embodiment, calculating the product demand change rate based on the product's financial data includes: extracting product coefficients for M types of raw materials from the forecast parameter table to obtain M product coefficients, and obtaining the proportion of the M types of raw materials in the product; for a raw material, calculating the demand change rate of the raw material based on the product coefficient of the raw material, the proportion of the raw material, and the product's financial data to obtain the sub-demand change rate of the raw material; obtaining the product's preset demand growth rate, calculating the sum of the preset demand growth rate and the M sub-demand change rates to obtain the demand change rate.

[0055] Specifically, after obtaining the product's financial data, the demand change rate of each raw material can be calculated by combining the proportion information of various raw materials in the product with the product's financial data. This allows for the integration of the overall product demand change rate, providing accurate data support for subsequent risk assessment. First, a table of forecast parameters, including product coefficients and basic growth rates for various raw materials, can be obtained. Then, the specific product coefficients for each raw material can be extracted. These product coefficients reflect the degree to which changes in the price of that raw material affect product demand. Simultaneously, the proportion of each raw material in the product's composition needs to be obtained, thus determining the percentage of each raw material.

[0056] Furthermore, for each raw material, its sub-demand change rate can be calculated. Then, the product's preset demand growth rate is read from the forecast parameter table, and the preset demand growth rate is summed with the sub-demand change rates of all the above raw materials to determine the overall product demand change rate: Demand change rate = Preset demand growth rate + ∑ (sub-demand change rate).

[0057] This embodiment calculates the demand change rate based on product composition analysis and raw material price changes. It can not only capture the immediate impact of raw material price fluctuations on product demand, but also significantly enhance financial institutions' ability to predict and manage corporate risks by combining historical trends and industry averages.

[0058] Optionally, in the credit limit adjustment method provided in this application embodiment, calculating the demand change rate of raw materials based on the product coefficient of raw materials, the proportion of raw materials, and the financial data of the products includes: obtaining the value threshold of raw materials and obtaining the initial value of raw materials, determining the change probability value based on the ratio of the initial value to the value threshold; and determining the sub-demand change rate of raw materials based on the product coefficient, the proportion of raw materials, and the change probability value.

[0059] Specifically, when calculating the rate of change in demand for each raw material, we first obtain the value threshold and initial value of the raw material, where the initial value refers to the market price or cost at a certain benchmark time. Then, we can calculate the probability of a change in the value of the raw material, i.e., the rate of change in material price, using the following formula: (Initial Value - Value Threshold) / Value Threshold. Finally, based on the calculated probability of change, combined with the product coefficient and the proportion of raw materials, we determine the sub-demand change rate for each raw material using the following formula: Sub-demand change rate = Product coefficient × Raw material proportion × Probability of change, where the product coefficient reflects the direct impact of raw material price changes on product demand, and the raw material proportion reflects the proportion of that raw material in the total product cost.

[0060] This embodiment can assess the risk level of changes in the value of different raw materials by calculating the rate of change in demand for raw materials, thereby improving the risk control capabilities of financial institutions and optimizing risk management strategies.

[0061] Optionally, in the credit limit adjustment method provided in this application embodiment, determining the risk adjustment strategy of the target institution based on the product demand change rate includes: obtaining a risk strategy matrix; extracting the adjustment ratio values ​​of the M raw materials from the risk strategy matrix according to the sub-demand change rates of the M raw materials in the demand change rate; calculating the product of the adjustment ratio values ​​of the M raw materials and the financial data of the product to obtain the credit limit data of the M raw materials; calculating the adjustment amount of the M raw materials based on the adjustment ratio values ​​of the M raw materials and the credit limit data of the M raw materials; and constructing a risk adjustment strategy based on the adjustment amount of the M raw materials.

[0062] Specifically, after obtaining the product demand change rate, a risk strategy matrix containing elements such as demand change rate, risk level, adjustment ratio, and operational method can be obtained. This matrix can guide financial institutions to take corresponding risk management measures based on changes in product demand. Then, based on each sub-demand change rate, the corresponding adjustment ratio is extracted from the matrix. This adjustment ratio reflects the financial institution's assessment of the risk of future raw material price fluctuations and the degree of hedging required.

[0063] Furthermore, the adjustment ratio for each raw material can be multiplied by the product's financial data to obtain the quota data for each raw material. Then, based on the adjustment ratio and quota data, the adjustment amount for each raw material can be calculated: Adjustment Amount = Adjustment Ratio × Raw Material Quota Data. Finally, by integrating the adjustment amounts for all raw materials, a specific risk adjustment strategy can be constructed, including the total amount, direction (buy or sell), and timing of hedging operations on raw materials in the futures market.

[0064] This embodiment determines the risk adjustment strategy of the target institution based on dynamic changes in product demand. It not only quantifies the financial institution's risk management, but also ensures that risk management measures can respond to market changes in a timely manner, thereby improving the efficiency and accuracy of the financial institution's risk management.

[0065] Optionally, in the credit limit adjustment method provided in this application embodiment, after determining the risk adjustment strategy of the target institution based on the product demand change rate, the method further includes: obtaining the adjustment ratio value and adjustment amount of M types of raw materials, and obtaining the financial transaction coefficient and initial transaction rate; calculating the product of the adjustment ratio value and financial transaction coefficient of M types of raw materials to obtain the financial product, calculating the sum of the financial product and the initial transaction rate to obtain financial transaction data; calculating the product of the financial transaction data and the adjustment amount of M types of raw materials to obtain transaction limit data, and sending a prompt message to the target institution when the transaction limit data is less than or equal to the historical limit data of the target institution, wherein the prompt message is used to prompt the target institution to adjust the quantity of products.

[0066] Specifically, after obtaining the risk adjustment strategy of the financial institution for the target institution, the adjustment ratio and amount of raw materials calculated based on the risk strategy matrix and the sub-demand change rate can also be obtained. Simultaneously, the financial transaction coefficient and initial transaction rate are also obtained. The financial transaction coefficient reflects market transaction efficiency and is used to assess the cost and efficiency of hedging operations conducted by financial institutions in the futures market. The initial transaction rate is the default ratio pre-set by the financial institution for futures hedging transactions in the absence of additional market information, representing the conservative strategy of the financial institution under static conditions.

[0067] Further, the adjustment ratio for the product is determined based on the adjustment ratio for raw materials. This product adjustment ratio is then multiplied by the financial transaction coefficient to obtain a financial product. This financial product is then added to the initial transaction rate to generate financial transaction data, which represents the final decision ratio after the financial institution comprehensively considers market conditions and risk forecasts. Further still, the financial transaction data is multiplied by the adjustment amount for all raw materials to obtain transaction limit data, i.e., the specific hedging operation scale that the financial institution plans to execute. Finally, the transaction limit data is compared with the target institution's historical limit data. If the transaction limit data exceeds the historical limit data, a notification message needs to be sent to the target institution, instructing it to assess whether it needs to adjust the quantity of products to avoid increased risk or cost due to excessive hedging.

[0068] This embodiment assesses the actual transaction volume of financial institutions and establishes an early warning mechanism based on this to ensure that the transaction volume does not exceed the historical reference limit, maintain the safety and operational stability of financial institutions and target institutions, and improve the flexibility and response speed of financial transactions.

[0069] This application also provides a credit limit adjustment system. Figure 3 This is a schematic diagram of a credit limit adjustment system provided according to an embodiment of this application, such as... Figure 3As shown, the system includes: a component analysis and mapping module, a value assessment module, a product demand forecasting module, a risk decision-making module, and a credit decision-making and adjustment module. The component analysis and mapping module receives product data submitted by the target institution, analyzes it, and maps it to raw material contracts in the futures market, establishing a link between the product and futures. The value assessment module uses a dynamic algorithm to calculate the product's financial data based on futures market price changes and product component mapping. The product demand forecasting module analyzes the rate of change in future product demand based on raw material price trends and industry forecast parameters, i.e., calculating the product's demand change rate based on its financial data. The risk decision-making module determines the target institution's risk adjustment strategy based on the product's demand change rate. This strategy may include deciding whether to conduct hedging operations in the futures market, as well as the hedging ratio and method. The credit decision-making and adjustment module dynamically adjusts the credit limit for the target institution based on product value, demand forecasts, and risk adjustment strategies, ensuring asset security while meeting the enterprise's funding needs.

[0070] To adjust the credit limit, after the target institution submits product data including the name, weight ratio, and unit cost of raw materials through the system interface, the component analysis and mapping module queries the futures market to find corresponding contracts, obtains the latest prices, and establishes a mapping relationship between product components and futures contracts, thereby obtaining the financial data of the raw materials. For example, if a company submits product information containing four raw materials: aluminum, copper, silicon, and glass, the component analysis and mapping module queries the futures market to find corresponding contracts, obtains the latest prices, and establishes a mapping relationship between product components and futures contracts, thereby obtaining the financial data of the raw materials.

[0071] The valuation module reads the mapping results from the component analysis and mapping module, combines them with real-time price data from the futures market, and uses a dynamic valuation formula to calculate the latest valuation of the product. This means calculating the product's financial data based on the financial data of the raw materials. For example, if the futures price of aluminum rises while the futures price of copper falls, the valuation module recalculates the product's valuation according to the formula to reflect the impact of raw material price fluctuations on the value of the finished product. After the valuation module completes the valuation update, the product demand forecasting module calculates the future demand change rate of the product based on the base growth rate, material price change rate, and price sensitivity coefficient in the forecasting parameter table. The risk decision-making module queries the risk control strategy table based on the product's demand change rate to determine the target institution's risk adjustment strategy. For example, if a decline in demand is predicted, the module selects a higher proportion of the strategy to reduce potential risks. Finally, the credit decision and adjustment module comprehensively considers the product's latest financial data, risk adjustment strategies, and demand forecast results, using a dynamic collateral ratio formula to calculate a new credit line. If risk increases, the credit line is lowered; conversely, if risk decreases, the credit line is increased to adapt to market changes and risk dynamics.

[0072] This embodiment effectively predicts changes in market demand, reduces risk, and adjusts loan conditions through the interactive operation between the component analysis mapping module, value assessment module, product demand forecasting module, risk decision-making module, and credit decision-making and adjustment module. This meets the target institution's greater funding needs and protects financial institutions from losses caused by market fluctuations.

[0073] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0074] Example 2

[0075] This application also provides a credit limit adjustment device. It should be noted that the credit limit adjustment device of this application can be used to execute the credit limit adjustment method provided in this application. The following describes the credit limit adjustment device provided in this application.

[0076] According to an embodiment of this application, an apparatus for implementing the above-described method for adjusting credit limits is also provided. Figure 4 This is a schematic diagram of a credit limit adjustment device provided according to an embodiment of this application, such as... Figure 4 As shown, the device includes: a first acquisition unit 40, a first calculation unit 41, and a determination unit 42.

[0077] The first acquisition unit 40 is used to acquire product data of the products produced by the target institution, and extract financial data of M kinds of raw materials required for the production of the products from the product data, where M is a positive integer;

[0078] The first calculation unit 41 is used to calculate the financial data of the product based on the financial data of the M kinds of raw materials, and to calculate the demand change rate of the product based on the financial data of the product, wherein the demand change rate is obtained based on the combination of the sub-demand change rates of the M kinds of raw materials.

[0079] Unit 42 is used to determine the risk adjustment strategy of the target institution based on the product demand change rate, and adjust the credit limit of the target institution according to the risk adjustment strategy.

[0080] The credit limit adjustment device provided in this application embodiment acquires product data of the products produced by the target institution through a first acquisition unit 40, and extracts financial data of M kinds of raw materials required for the production of the products from the product data, where M is a positive integer; a first calculation unit 41 calculates the financial data of the products based on the financial data of the M kinds of raw materials, and calculates the demand change rate of the products based on the financial data of the products, wherein the demand change rate is obtained based on the combination of sub-demand change rates of the M kinds of raw materials; a determination unit 42 determines the risk adjustment strategy of the target institution based on the demand change rate of the products, and adjusts the credit limit of the target institution according to the risk adjustment strategy. This solves the technical problem of low adjustment accuracy when adjusting the credit limit of the target institution in related technologies. By acquiring the financial data of the raw materials of the products produced by the target institution, calculating the financial data of the products based on the financial data of the raw materials, calculating the demand change rate of the products based on the financial data of the products, and determining the risk adjustment strategy and the credit limit of the target institution based on the demand change rate of the products, the device achieves the technical effect of improving the adjustment accuracy when adjusting the credit limit of the target institution.

[0081] Optionally, in the credit limit adjustment device provided in this application embodiment, the first acquisition unit 40 includes: a processing module, used to format product data to obtain processed product data, and determine whether M kinds of raw materials in the product belong to a preset type; a first acquisition module, used to acquire a component mapping table when the M kinds of raw materials belong to the preset type, and extract financial data from the processed product data based on the component mapping table; and a second acquisition module, used to acquire cost data of Y kinds of raw materials that do not belong to the preset type when any one of the raw materials does not belong to the preset type, and determine the Y cost data and MY cost data as the financial data of the raw materials, wherein Y is less than or equal to M, and Y is a positive integer.

[0082] Optionally, in the credit limit adjustment device provided in this application embodiment, the first calculation unit 41 includes: a third acquisition module, used to acquire cost data of M raw materials in a historical time period from the financial data of M raw materials, obtain a cost list, and acquire the proportion of M raw materials in the product; and a first calculation module, used to calculate product financial data based on the M cost data in the cost list and the proportion of M raw materials in the product.

[0083] Optionally, in the credit limit adjustment device provided in this application embodiment, the first calculation unit 41 includes: an extraction module, used to extract product coefficients of M kinds of raw materials from the prediction parameter table to obtain M product coefficients, and obtain the proportion of M kinds of raw materials in the product; a second calculation module, used to calculate the demand change rate of a raw material based on the product coefficient of the raw material, the proportion of the raw material and the financial data of the product, to obtain the sub-demand change rate of the raw material; and a fourth acquisition module, used to acquire the preset demand growth rate of the product, calculate the sum of the preset demand growth rate and the M sub-demand change rates, to obtain the demand change rate.

[0084] Optionally, in the credit limit adjustment device provided in this application embodiment, the first calculation unit 41 includes: a fifth acquisition module, used to acquire the value threshold of raw materials and acquire the initial value of raw materials, and determine the change probability value according to the ratio of the initial value to the value threshold; and a determination module, used to determine the sub-demand change rate of raw materials according to the product coefficient, the proportion of raw materials and the product of the change probability value.

[0085] Optionally, in the credit limit adjustment device provided in this application embodiment, the determining unit 42 includes: a sixth acquisition module, used to acquire a risk strategy matrix and extract the adjustment ratio values ​​of the M raw materials from the risk strategy matrix according to the sub-demand change rates of the M raw materials in the demand change rate; a third calculation module, used to calculate the product of the adjustment ratio values ​​of the M raw materials and the financial data of the product to obtain the credit limit data of the M raw materials; and a fourth calculation module, used to calculate the adjustment amount of the M raw materials according to the adjustment ratio values ​​of the M raw materials and the credit limit data of the M raw materials, and construct a risk adjustment strategy based on the adjustment amount of the M raw materials.

[0086] Optionally, in the credit limit adjustment device provided in this application embodiment, the device further includes: a second acquisition unit, used to acquire the adjustment ratio value of M types of raw materials and the adjustment amount of M types of raw materials after determining the risk adjustment strategy of the target institution based on the product demand change rate, and to acquire the financial transaction coefficient and the initial transaction rate; a second calculation unit, used to calculate the product of the adjustment ratio value of M types of raw materials and the financial transaction coefficient to obtain the financial product, and to calculate the sum of the financial product and the initial transaction rate to obtain financial transaction data; a third calculation unit, used to calculate the product of the financial transaction data and the adjustment amount of M types of raw materials to obtain transaction limit data, and to send a prompt message to the target institution when the transaction limit data is less than or equal to the historical limit data of the target institution, wherein the prompt message is used to prompt the target institution to adjust the quantity of products.

[0087] It should be noted that the first acquisition unit 40, the first calculation unit 41, and the determination unit 42 mentioned above correspond to steps S201 to S203 in Embodiment 1. The instances and application scenarios implemented by the above units and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above units can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0088] Example 3

[0089] Embodiments of this application may provide a computer terminal, which may be any computer terminal device in a group of computer terminals. Optionally, in this embodiment, the aforementioned computer terminal may also be replaced with a mobile terminal or an electronic device, etc.

[0090] Optionally, in this embodiment, the computer terminal may be located in at least one of a plurality of network devices in a computer network.

[0091] In this embodiment, the computer terminal described above can execute the program code for the following steps in the credit limit adjustment method: obtaining product data of the products produced by the target institution, and extracting financial data of M kinds of raw materials required for the production of the products from the product data, where M is a positive integer; calculating the financial data of the products based on the financial data of the M kinds of raw materials, and calculating the demand change rate of the products based on the financial data of the products, wherein the demand change rate is obtained based on the combination of sub-demand change rates of the M kinds of raw materials; determining the risk adjustment strategy of the target institution based on the demand change rate of the products, and adjusting the credit limit of the target institution according to the risk adjustment strategy.

[0092] Optionally, the aforementioned computer terminal can execute the following steps in the credit limit adjustment method: format the product data to obtain processed product data, and determine whether M types of raw materials in the product belong to a preset type; if the M types of raw materials belong to the preset type, obtain a component mapping table, and extract financial data from the processed product data based on the component mapping table; if any raw material does not belong to the preset type, obtain the cost data of Y types of raw materials that do not belong to the preset type, and determine the Y cost data and MY cost data as the financial data of the raw materials, where Y is less than or equal to M and Y is a positive integer.

[0093] Optionally, the aforementioned computer terminal can execute the program code for the following steps in the credit limit adjustment method: obtain the cost data of the M raw materials in the historical time period from the financial data of the M raw materials, obtain a cost list, and obtain the proportion of the M raw materials in the product; calculate the product financial data based on the M cost data in the cost list and the proportion of the M raw materials in the product.

[0094] Optionally, the aforementioned computer terminal can execute the following steps in the credit limit adjustment method: extract the product coefficients of M types of raw materials from the prediction parameter table to obtain M product coefficients, and obtain the proportion of M types of raw materials in the product; for a raw material, calculate the demand change rate of the raw material based on the product coefficient of the raw material, the proportion of the raw material, and the financial data of the product to obtain the sub-demand change rate of the raw material; obtain the preset demand growth rate of the product, calculate the sum of the preset demand growth rate and the M sub-demand change rates to obtain the demand change rate.

[0095] Optionally, the aforementioned computer terminal can execute the program code for the following steps in the credit limit adjustment method: obtaining the value threshold of raw materials and obtaining the initial value of raw materials; determining the change probability value based on the ratio of the initial value to the value threshold; and determining the sub-demand change rate of raw materials based on the product coefficient, the proportion of raw materials, and the product of the change probability value.

[0096] Optionally, the aforementioned computer terminal can execute the following steps in the credit limit adjustment method: obtain the risk strategy matrix; extract the adjustment ratio values ​​of the M raw materials from the risk strategy matrix based on the sub-demand change rates of the M raw materials in the demand change rate; calculate the product of the adjustment ratio values ​​of the M raw materials and the financial data of the product to obtain the credit limit data of the M raw materials; calculate the adjustment amount of the M raw materials based on the adjustment ratio values ​​of the M raw materials and the credit limit data of the M raw materials; and construct a risk adjustment strategy based on the adjustment amount of the M raw materials.

[0097] Optionally, the aforementioned computer terminal can execute the following steps in the credit limit adjustment method: obtain the adjustment ratio value and adjustment amount of M types of raw materials, and obtain the financial transaction coefficient and initial transaction rate; calculate the product of the adjustment ratio value and financial transaction coefficient of M types of raw materials to obtain the financial product; calculate the sum of the financial product and the initial transaction rate to obtain financial transaction data; calculate the product of the financial transaction data and the adjustment amount of M types of raw materials to obtain transaction limit data; if the transaction limit data is less than or equal to the historical limit data of the target institution, send a prompt message to the target institution, wherein the prompt message is used to prompt the target institution to adjust the quantity of products.

[0098] Optionally, Figure 5This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 5 As shown, the electronic device may include: one or more ( Figure 5 (Only one is shown) processor 502, memory 504, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0099] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the credit limit adjustment method and apparatus in this application embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned credit limit adjustment method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0100] The processor can access the information and application programs stored in the memory via the transmission device to execute the steps described above in the credit limit adjustment method.

[0101] Those skilled in the art will understand that Figure 5 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 5 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 5 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 5 The different configurations shown.

[0102] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0103] Example 4

[0104] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the credit limit adjustment method provided in Embodiment 1.

[0105] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0106] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: acquiring product data of the products produced by the target institution, and extracting financial data of M kinds of raw materials required for producing the products from the product data, where M is a positive integer; calculating the financial data of the products based on the financial data of the M kinds of raw materials, and calculating the demand change rate of the products based on the financial data of the products, wherein the demand change rate is obtained based on the combination of sub-demand change rates of the M kinds of raw materials; determining the risk adjustment strategy of the target institution based on the demand change rate of the products, and adjusting the credit limit of the target institution according to the risk adjustment strategy.

[0107] This application also provides a computer program product, which, when executed on a data processing device, is suitable for performing the steps of a method for adjusting a credit limit.

[0108] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0109] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0110] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of units or modules may be electrical or other forms.

[0111] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0112] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0113] If the integrated unit is implemented as 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 this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0114] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for adjusting credit limits, characterized in that, include: Obtain product data of the products produced by the target institution, and extract financial data of M types of raw materials required for the production of the products from the product data, where M is a positive integer; The financial data of the product is calculated based on the financial data of the M raw materials, and the demand change rate of the product is calculated based on the financial data of the product, wherein the demand change rate is obtained based on the combination of the sub-demand change rates of the M raw materials. The risk adjustment strategy for the target institution is determined based on the rate of change in demand for the product, and the credit limit for the target institution is adjusted according to the risk adjustment strategy.

2. The method according to claim 1, characterized in that, The financial data extracted from the product data for the M types of raw materials required to produce the product includes: The product data is formatted to obtain processed product data, and it is determined whether the M types of raw materials in the product belong to a preset type. If the M raw materials belong to the preset type, obtain the component mapping table, and extract the financial data from the processed product data based on the component mapping table; If any raw material does not belong to the preset type, obtain the cost data of Y types of raw materials that do not belong to the preset type, and determine the Y cost data and MY cost data as the financial data of the raw material, where Y is less than or equal to M and Y is a positive integer.

3. The method according to claim 1, characterized in that, The financial data of the product calculated based on the financial data of the M raw materials includes: Obtain cost data for the M raw materials from the financial data of the M raw materials within a historical time period, obtain a cost list, and obtain the proportion of the M raw materials in the product; The financial data of the product is calculated based on the M cost data in the cost list and the proportion of the M raw materials in the product.

4. The method according to claim 1, characterized in that, The calculation of the demand change rate for the product based on the product's financial data includes: Extract the product coefficients of the M raw materials from the prediction parameter table to obtain M product coefficients, and obtain the proportion of the M raw materials in the product; For a raw material, the demand change rate of the raw material is calculated based on the product coefficient of the raw material, the proportion of the raw material, and the financial data of the product, to obtain the sub-demand change rate of the raw material. Obtain the preset demand growth rate of the product, calculate the sum of the preset demand growth rate and the change rates of M sub-demands, and obtain the demand change rate.

5. The method according to claim 4, characterized in that, The calculation of the demand change rate for the raw materials based on the product coefficient, the proportion of the raw materials, and the financial data of the products includes: Obtain the value threshold of the raw material and the initial value of the raw material, and determine the change probability value based on the ratio of the initial value to the value threshold; The sub-demand change rate of the raw materials is determined by multiplying the product coefficient, the proportion of the raw materials, and the change probability value.

6. The method according to claim 1, characterized in that, Determining the risk adjustment strategy for the target organization based on the rate of change in demand for the product includes: Obtain the risk strategy matrix, and extract the adjustment ratio values ​​of the M raw materials from the risk strategy matrix based on the sub-demand change rates of the M raw materials in the demand change rate; The adjustment ratio values ​​of the M types of raw materials are calculated and multiplied by the financial data of the product to obtain the quota data of the M types of raw materials. The adjustment amount for the M types of raw materials is calculated based on the adjustment ratio and quota data of the M types of raw materials, and the risk adjustment strategy is constructed based on the adjustment amount of the M types of raw materials.

7. The method according to claim 1, characterized in that, After determining the risk adjustment strategy for the target organization based on the rate of change in demand for the product, the method further includes: Obtain the adjustment ratio values ​​and adjustment amounts of the M types of raw materials, and obtain the financial transaction coefficient and initial transaction rate; Calculate the product of the adjustment ratio of the M types of raw materials and the financial transaction coefficient to obtain the financial product; calculate the sum of the financial product and the initial transaction rate to obtain the financial transaction data. The transaction amount data is obtained by multiplying the financial transaction data and the adjustment amount of the M types of raw materials. If the transaction amount data is less than or equal to the historical amount data of the target institution, a prompt message is sent to the target institution, wherein the prompt message is used to prompt the target institution to adjust the quantity of the product.

8. A device for adjusting credit limits, characterized in that, include: The first acquisition unit is used to acquire product data of the products produced by the target institution, and extract financial data of M kinds of raw materials required for the production of the products from the product data, where M is a positive integer; The first calculation unit is used to calculate the financial data of the product based on the financial data of the M raw materials, and to calculate the demand change rate of the product based on the financial data of the product, wherein the demand change rate is obtained based on the combination of the sub-demand change rates of the M raw materials. The determining unit is used to determine the risk adjustment strategy of the target institution based on the demand change rate of the product, and adjust the credit limit of the target institution according to the risk adjustment strategy.

9. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, executes the credit limit adjustment method according to any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the credit limit adjustment method according to any one of claims 1 to 7.

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