Personalized pricing method and device and computer readable storage medium

Abstract

The invention discloses a personalized pricing method and device and a computer readable storage medium. The method comprises the following steps: under the condition that a pricing request is received, analyzing the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request; determining a pricing parameter required in the pricing formula as a target pricing parameter; performing data matching in a database according to a parameter matching strategy to determine a parameter value of the target pricing parameter; and the parameter value and the adjustment value are substituted into a pricing formula for calculation, a pricing result of pricing the pricing product is obtained, the pricing of the pricing product is adjusted in real time according to the pricing result, and the adjustment value is a value for determining the pricing result by adjusting the parameter value based on the pricing request. The technical problem that the pricing mode is difficult to adjust flexibly due to the fact that most of traditional product pricing models in the prior art adopt a single pricing formula and a parameter matching rule is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of information processing, and in particular, to a personalized pricing method, device, and computer-readable storage medium. Background Art

[0002] In traditional product pricing models, fixed pricing formulas, parameter matching rules, etc. are configured, which cannot meet the real-time and high flexibility requirements of product pricing in transactions. There are the following problems in the current transaction pricing models of traditional enterprises: 1) In traditional transaction pricing models, pricing formulas, parameter matching rules, etc. are set in the models, lacking flexibility in calculation and parameter matching; 2) In traditional transaction pricing models, formulas and rules are accurately set in the models, and it is impossible to modify the configuration according to real-time changes and specific situations, increasing the amount of model modification for system upgrade.

[0003] Most existing pricing methods accurately set pricing formulas and specific parameters in the models, and perform pricing calculations by obtaining information from transactions to achieve the effect of real-time pricing. According to research and analysis, there are some disadvantages in the current pricing methods: 1) The parameters in existing product pricing models are set in the models, and it is impossible to configure the parameters required for pricing according to real-time changes and specific situations, lacking real-time nature; 2) The pricing formulas and parameter matching rules in existing product pricing models are single, and each pricing model has only a fixed pricing formula and parameter matching rule. When modification is required, the change in the model is large, and it cannot be changed in time, increasing the lag of pricing results, and at the same time making the workload of developers large, lacking flexibility.

[0004] Aiming at the problem that most traditional product pricing models in the above-mentioned related technologies adopt single pricing formulas and parameter matching rules, resulting in difficult flexible adjustment of pricing methods, no effective solution has been proposed yet. Summary of the Invention

[0005] Embodiments of the present invention provide a personalized pricing method, device, and computer-readable storage medium to at least solve the technical problem that most traditional product pricing models in the related technologies adopt single pricing formulas and parameter matching rules, resulting in difficult flexible adjustment of pricing methods.

[0006] According to one aspect of an embodiment of the present invention, a personalized pricing method is provided, including: when receiving a pricing request, parsing the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the pricing of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula; determining the pricing parameters required in the pricing formula as target pricing parameters; performing data matching in a database according to the parameter matching strategy to determine the parameter values of the target pricing parameters; substituting the parameter values and adjustment values into the pricing formula for calculation to obtain a pricing result for pricing the pricing product, so as to adjust the pricing of the pricing product in real time according to the pricing result, where the adjustment value is a value determined by adjusting the parameter values based on the pricing request to determine the pricing result.

[0007] Optionally, when receiving a pricing request, parsing the pricing request to obtain a pricing formula corresponding to the pricing request includes: when receiving the pricing request, parsing the pricing request to obtain the type of pricing product requested in the pricing request; when the type of pricing product is a loan product, determining a first formula as the pricing formula, where the first formula is: P = G + A, P represents the pricing result, G represents the break-even interest rate, and A represents the adjustment value; when the type of pricing product is a deposit product, determining a second formula as the pricing formula, where the second formula is: P = B + A, B represents the base interest rate; when the pricing request includes customized request information, determining a configuration formula configured based on the customized request information as the pricing formula, where the customized request information is information for requesting customization of the pricing formula.

[0008] Optionally, when receiving a pricing request, parsing the pricing request to obtain a parameter matching strategy corresponding to the pricing request includes: when receiving the pricing request, parsing the pricing request to obtain the type of pricing product and pricing product information requested in the pricing request, where the pricing product information at least includes: the currency of the pricing product, the term of the pricing product, and the pricing platform, and the pricing platform is a platform for pricing the pricing product; determining a preset matching strategy in the database that has a corresponding relationship with the type of pricing product and the pricing product information as the parameter matching strategy, where the corresponding relationship means that the relevance of the parameter matching strategy to the type of pricing product or at least one of the pricing product information is higher than the correlation threshold.

[0009] Optionally, data matching is performed in the database according to the parameter matching strategy to determine the parameter value of the target pricing parameter, including: determining the data table that needs to be queried by the parameter matching strategy as the target data table; generating a data query statement for querying the target data table according to the parameter matching strategy; performing data query in the target data table according to the data query statement to obtain the parameter value of the target pricing parameter.

[0010] Optionally, before substituting the parameter value and the adjustment value into the pricing formula for calculation to obtain the pricing result of the priced product, the method further includes: generating a decision tree according to a preset label, where the decision tree includes multiple matching paths, each matching path corresponds to an adjustment item, each matching path includes multiple preset labels, and the preset label is a preset pricing restriction condition; sequentially matching the priced product information in the pricing request with the preset labels on each matching path to obtain a matching result; determining the adjustment item of the matching path with the matching result being successful as the target adjustment item; calculating according to the item value of the target adjustment item to obtain the adjustment value.

[0011] Optionally, determining the adjustment item of the matching path with the matching result being successful as the target adjustment item includes: when the priced product information satisfies all the preset labels on the matching path, determining the matching result as successful; determining the matching path with the matching result being successful as the target matching path; when the target matching path only includes local preset labels, determining the adjustment item of the target matching path as the target adjustment item; when the target matching path includes external preset labels, numerically adjusting the adjustment item of the target matching path according to the external preset label, and determining the adjusted adjustment item as the target adjustment item.

[0012] Optionally, calculating according to the item value of the target adjustment item to obtain the adjustment value includes: determining the upper limit value of the adjustment value as the adjustment upper limit value according to the preset value range of the adjustment value, and determining the lower limit value of the adjustment value as the adjustment lower limit value; when there is only one target adjustment item, determining the item value of the target adjustment item as the total adjustment item value; when there are multiple target adjustment items, determining the sum of the item values of the multiple target adjustment items as the total adjustment item value; calculating according to the adjustment upper limit value, the adjustment lower limit value, and the total adjustment item value using a third formula to obtain the adjustment value, where the third formula is: A = min[max(AS, AD), AU], AS represents the total adjustment item value, AD represents the adjustment lower limit value, and AU represents the adjustment upper limit value.

[0013] According to another aspect of the embodiments of the present invention, a personalized pricing device is further provided, including: a first acquisition unit, configured to, when receiving a pricing request, parse the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the pricing of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula; a first determination unit, configured to determine the pricing parameters required in the pricing formula as target pricing parameters; a second determination unit, configured to perform data matching in a database according to the parameter matching strategy to determine the parameter values of the target pricing parameters; a second acquisition unit, configured to substitute the parameter values and adjustment values into the pricing formula for calculation to obtain a pricing result for pricing the pricing product, so as to adjust the pricing of the pricing product in real time according to the pricing result, where the adjustment value is a value obtained by adjusting the parameter values based on the pricing request to determine the pricing result.

[0014] Optionally, the first acquisition unit includes: a first acquisition module, configured to, when receiving the pricing request, parse the pricing request to obtain the type of pricing product requested in the pricing request; a first determination module, configured to, when the type of pricing product is a loan product, determine a first formula as the pricing formula, where the first formula is: P = G + A, P represents the pricing result, G represents the break-even interest rate, and A represents the adjustment value; a second determination module, configured to, when the type of pricing product is a deposit product, determine a second formula as the pricing formula, where the second formula is: P = B + A, and B represents the base interest rate; a third determination module, configured to, when the pricing request includes customization request information, determine a configuration formula configured based on the customization request information as the pricing formula, where the customization request information is information for requesting to customize the pricing formula.

[0015] Optionally, the first acquisition unit includes: a second acquisition module, configured to, when receiving the pricing request, parse the pricing request to obtain the type of pricing product and the pricing product information requested in the pricing request, where the pricing product information at least includes: the currency of the pricing product, the term of the pricing product, and the pricing platform, and the pricing platform is a platform for pricing the pricing product; a fourth determination module, configured to determine a preset matching strategy having a corresponding relationship with the type of pricing product and the pricing product information in the database as the parameter matching strategy, where the corresponding relationship means that the correlation degree of the parameter matching strategy with the type of pricing product or at least one piece of the pricing product information is higher than a correlation threshold.

[0016] Optionally, the second determination unit includes: a fifth determination module, configured to determine that the data table to be queried by the parameter matching policy is a target data table; a generation module, configured to generate a data query statement for querying the target data table according to the parameter matching policy; and a third acquisition module, configured to perform data query in the target data table according to the data query statement to obtain the parameter value of the target pricing parameter.

[0017] Optionally, the personalized pricing device further includes: a generation unit, configured to generate a decision tree according to a preset label before substituting the parameter value and the adjustment value into the pricing formula for calculation to obtain a pricing result of the priced product, where the decision tree includes multiple matching paths, each matching path corresponds to an adjustment item, each matching path includes a plurality of the preset labels, and the preset label is a preset pricing restriction condition; a third acquisition unit, configured to sequentially match the priced product information in the pricing request with the preset labels on each matching path to obtain a matching result; a third determination unit, configured to determine that the adjustment item of the matching path with the matching result being successful is a target adjustment item; and a fourth acquisition unit, configured to calculate according to the item value of the target adjustment item to obtain the adjustment value.

[0018] Optionally, the third determination unit includes: a sixth determination module, configured to determine that the matching result is successful when the priced product information satisfies all the preset labels on the matching path; a seventh determination module, configured to determine that the matching path with the matching result being successful is a target matching path; an eighth determination module, configured to determine that the adjustment item of the target matching path is the target adjustment item when the target matching path only includes local preset labels; and a ninth determination module, configured to numerically adjust the adjustment item of the target matching path according to the external preset label and determine the adjusted adjustment item as the target adjustment item when the target matching path includes an external preset label.

[0019] Optionally, the third determination unit includes: a tenth determination module, configured to determine, according to a preset value range of the adjustment value, an upper limit value of the adjustment value as an adjustment upper limit value, and determine a lower limit value of the adjustment value as an adjustment lower limit value; an eleventh determination module, configured to determine, when there is only one target adjustment item, a value of the target adjustment item as an adjustment item total value; a twelfth determination module, configured to determine, when there are multiple target adjustment items, a sum of values of the multiple target adjustment items as the adjustment item total value; a fourth acquisition module, configured to calculate the adjustment value according to the adjustment upper limit value, the adjustment lower limit value, and the adjustment item total value by using a third formula, where the third formula is: A = min[max(AS, AD), AU], AS represents the adjustment item total value, AD represents the adjustment lower limit value, and AU represents the adjustment upper limit value.

[0020] On the other hand, according to an embodiment of the present invention, there is also provided a personalized pricing system, and the personalized pricing system uses any one of the above-mentioned personalized pricing methods.

[0021] On the other hand, according to an embodiment of the present invention, there is also provided a computer-readable storage medium, and the computer-readable storage medium includes a stored program, where the program executes any one of the above-mentioned personalized pricing methods.

[0022] On the other hand, according to an embodiment of the present invention, there is also provided a processor, and the processor is configured to run a program, where the program, when running, executes any one of the above-mentioned personalized pricing methods.

[0023] On the other hand, according to an embodiment of the present invention, there is also provided a computer program product, including computer instructions, and the computer instructions, when executed by a processor, execute any one of the above-mentioned personalized pricing methods.

[0024] In an embodiment of the present invention, when a pricing request is received, the pricing request is parsed to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request. Herein, the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the price of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula. Determine the pricing parameters required in the pricing formula as target pricing parameters. Perform data matching in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters. Substitute the parameter values and adjustment values into the pricing formula for calculation to obtain a pricing result for pricing the pricing product, so as to adjust the price of the pricing product in real time according to the pricing result. Herein, the adjustment value is a value obtained by adjusting the parameter values based on the pricing request to determine the pricing result. Through the above technical solution, the purpose of selecting a pricing formula and matching the parameter values of the required pricing parameters based on the user's pricing request is achieved, so as to perform personalized configuration on the pricing formula by using the parameter values, thereby obtaining a pricing result more suitable for the pricing request. The technical effect of flexibly and adaptively adjusting the pricing formula and parameters according to the user request is realized, the flexibility and real-time performance of pricing are improved, the pricing efficiency is increased, and furthermore, the technical problem in the related art that most traditional product pricing models adopt a single pricing formula and parameter matching rule, resulting in difficult flexible adjustment of the pricing method, is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0026] Figure 1 is a hardware structure block diagram of a mobile terminal for a personalized pricing method according to an embodiment of the present invention;

[0027] Figure 2 is a flowchart of a personalized pricing method according to an embodiment of the present invention;

[0028] Figure 3 is a flowchart of an optional personalized pricing method according to an embodiment of the present invention;

[0029] Figure 4 is a flowchart of determining an adjustment item according to an embodiment of the present invention;

[0030] Figure 5 is a schematic diagram of a personalized pricing device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0033] For the convenience of description, some nouns or terms involved in the embodiments of the present invention are explained below:

[0034] Product pricing: Using the "pricing formula", through cost parameters, extensible pricing tags, and highly flexible pricing adjustment item configurations, the interest rate calculation result for a certain product is obtained.

[0035] Pricing formula: The function required for the product pricing service.

[0036] Parameter matching: Using input parameters, the cost parameters corresponding to the matching rules are obtained.

[0037] Cost parameters: The calculation parameters required in the pricing process are divided into seven major cost parameters: capital cost rate, capital cost rate, operating cost rate, risk cost rate, income tax, surtax, and value-added tax.

[0038] Parameter matching rule: The matching mechanism for obtaining the corresponding cost parameters using input parameters.

[0039] Business system: The users of this model.

[0040] Adjustment item: The adjustment item is an important part of achieving differential pricing in this model. The adjustment item is essentially a series of decision trees composed of local tags and external tags.

[0041] As introduced in the background art, most of the traditional product pricing models in the related art adopt a single pricing formula and parameter matching rule, resulting in difficult flexible adjustment of the pricing method. To address the above deficiencies, an embodiment of the present invention provides a personalized pricing method, apparatus, and computer-readable storage medium.

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention.

[0043] The method embodiments provided in the embodiments of the present invention can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking the operation on a mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal of a personalized pricing method according to an embodiment of the present invention. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in Figure 1 a processor 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Among them, the above mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only illustrative and does not limit the structure of the above mobile terminal. For example, the mobile terminal may further include more or fewer components than Figure 1 shown in

[0044] The memory 104 can be used to store computer programs, such as software programs and modules of application software, for example, the computer program corresponding to the personalized pricing method in the embodiments of the present invention. The processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, that is, the above-mentioned method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories may be connected to the mobile terminal through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The transmission device 106 is used to receive or send data via a network. A specific example of the above-mentioned network may include a wireless network provided by a communication provider of the mobile terminal. In one instance, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 may be a radio frequency (Radio Frequency, abbreviated as RF) module, which is used to communicate with the Internet wirelessly.

[0045] According to an embodiment of the present invention, a method embodiment of a personalized pricing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0046] Figure 2 is a flowchart of the personalized pricing method according to an embodiment of the present invention, as Figure 2 shown, the method includes the following steps:

[0047] Step S202, when a pricing request is received, parse the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the price of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula.

[0048] Optionally, the above-mentioned pricing products may include, but are not limited to: loan products, deposit products.

[0049] In this embodiment, when a pricing request is received, it can be parsed to obtain a pricing formula and a parameter matching strategy (also referred to as a parameter matching rule) that conform to the pricing request, facilitating subsequent flexible adjustment of the pricing method based on the pricing request to obtain a pricing result more suitable for the pricing request.

[0050] In an alternative embodiment of the present invention, a product pricing model can be used to implement product pricing. This model can use a database to configure the pricing formula and parameter matching rules. Among them, the pricing formula involves formulas for loan products and deposit products, and the parameter matching rules involve seven major parameters including the cost of capital rate, cost of funds rate, cost of risk rate, operating cost rate, income tax, value-added tax, and surtax, as well as information such as product type, term, institution, and currency. Moreover, the parameter values are extracted to the page and configured through information such as product, term, institution, and currency. Here, the pricing formula, parameter matching strategy, and parameters stored in the database can be configured in two ways: through the front-end page configuration and the database configuration. That is, developers can control the matching mechanism and pricing mechanism of the model by modifying and adding pricing formulas and parameter matching rules in the database, and business personnel can control the matched parameter values by modifying and adding parameter values through page configuration, realizing the separation of the pricing formula, parameter matching rules, and parameter result matching.

[0051] The following combines Figure 3 to elaborate on the above embodiments of the present invention in detail. Figure 3 is a flowchart of an alternative personalized pricing method according to an embodiment of the present invention; as Figure 3 shown, when a pricing request is received, the corresponding pricing formula and parameter matching strategy can be obtained from the database by entering the system interface.

[0052] According to the above embodiments of the present invention, in step S202 above, when a pricing request is received, the pricing request is parsed to obtain a pricing formula corresponding to the pricing request, including: when a pricing request is received, the pricing request is parsed to obtain the pricing product type requested in the pricing request; when the pricing product type is a loan product, it is determined that the first formula is the pricing formula, where the first formula is: P = G + A, P represents the pricing result, G represents the break-even interest rate, and A represents the adjustment value; when the pricing product type is a deposit product, it is determined that the second formula is the pricing formula, where the second formula is: P = B + A, B represents the base interest rate; when the pricing request contains customization request information, it is determined that the configuration formula configured based on the customization request information is the pricing formula, where the customization request information is information for requesting a customized pricing formula.

[0053] In this embodiment, depending on the type of pricing product requested in the pricing request, different pricing formulas are used for pricing. Specifically, when the pricing product type is a loan product, the formula P = G + A (i.e., loan pricing result = break-even interest rate + adjustment value) can be used as the pricing formula, where the break-even interest rate G = (cost of funds rate * (1 - cost of capital rate / 10%) + operating cost rate + risk cost rate + cost of capital rate / (1 - income tax rate)) / (1 - value-added tax rate × surcharge rate) × (1 + value-added tax rate); when the pricing product type is a deposit product, the formula P = B + A (i.e., deposit pricing result = base interest rate + adjustment value) can be used as the pricing formula.

[0054] In addition to selecting the corresponding pricing formula according to the pricing product type, it is also possible to configure a pricing formula that meets the current requirements according to the actual needs of the user or the current actual situation. Similarly, corresponding configurations can be made according to the actual situation through two methods: front-end page configuration and database configuration.

[0055] According to the above embodiment of the present invention, in step S202 above, when a pricing request is received, the pricing request is parsed to obtain a parameter matching strategy corresponding to the pricing request, including: when a pricing request is received, the pricing request is parsed to obtain the type of pricing product and pricing product information requested in the pricing request, where the pricing product information includes at least: the currency of the pricing product, the term of the pricing product, and the pricing platform, and the pricing platform is the platform for pricing the pricing product; it is determined that the preset matching strategy in the database that has a corresponding relationship with the pricing product type and pricing product information is the parameter matching strategy, where the corresponding relationship means that the relevance of the parameter matching strategy to the pricing product type or at least one piece of pricing product information is higher than the correlation threshold.

[0056] In this embodiment, the selection of the parameter matching strategy is usually related to seven major parameters: cost of capital rate, cost of funds rate, risk cost rate, operating cost rate, income tax, value-added tax, and surcharge, as well as information such as product type, term, institution, and currency. When selecting the parameter matching strategy, it can be selected according to the correlation between this information carried in the pricing request and some pre-stored parameter matching strategies in the database.

[0057] Some possible parameter matching strategies are illustrated below:

[0058] 1) Maturity / Currency Matching Rule: For example, for loans with different maturities, the parameter matching rule may be set as follows: if the maturity is less than one year, select parameters from the short-term funding cost rate table; if the maturity is greater than one year, select from the long-term funding cost rate table. For loans in different currencies, the parameter matching rule may be set as: for RMB loans, use the domestic funding cost rate; for USD loans, use the international funding cost rate, to ensure that the impact of funding costs varying with maturity and currency is considered when pricing loans.

[0059] 2) Customer Credit Rating Matching Rule: For different customer credit ratings, the parameter matching rule may be: for customers with a high credit rating, select a lower risk cost rate; for customers with a low credit rating, select a higher risk cost rate. This rule reflects the bank's assessment of the loan risks of different customers and enables additional pricing for high-risk customers by adjusting the risk cost rate.

[0060] 3) Market Condition Matching Rule: In some cases, fluctuations in market interest rates affect the bank's loan costs. The parameter matching rule may be set as: when the market interest rate rises, select a higher capital cost rate and funding cost rate; when the market interest rate falls, select a lower capital cost rate and funding cost rate. This rule enables loan pricing to be adjusted in real time according to market conditions and stay in sync with the market.

[0061] 4) Product Type Matching Rule: For different loan product types, the parameter matching rule may vary. For example, for real estate mortgage loans, parameters may need to be selected from the real estate loan cost table; for small and micro enterprise loans, parameters may be selected from the small and micro enterprise cost table. This differential matching rule reflects the specific costs and risks of different types of loans and ensures the pertinence and reasonableness of pricing.

[0062] Step S204, determine the pricing parameters required in the pricing formula as target pricing parameters.

[0063] As Figure 3 shown, in this embodiment, it is possible to determine which parameter is specifically needed for pricing the pricing product according to the pricing parameters required in the pricing formula, so as to obtain the corresponding parameter value according to the corresponding parameter matching strategy.

[0064] Step S206, perform data matching in the database according to the parameter matching strategy to determine the parameter value of the target pricing parameter.

[0065] As Figure 3As shown, in this embodiment, after determining the target pricing parameters required for pricing a pricing product according to the pricing formula, a parameter matching strategy can be used to perform data matching in the database to obtain the specific parameter values of the target pricing parameters. These specific parameter values selected using the parameter matching strategy are generally the optimal choices that meet the pricing request, so as to ensure that the final pricing can meet customer needs as much as possible.

[0066] According to the above embodiment of the present invention, in step S206, data matching is performed in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters, including: determining the data table that the parameter matching strategy needs to query as the target data table; generating a data query statement for querying the target data table according to the parameter matching strategy; performing data query in the target data table according to the data query statement to obtain the parameter values of the target pricing parameters.

[0067] As Figure 3 shown, the database stores a mapping table of seven major parameters and the corresponding data storage tables, and a mapping table of parameter matching rules and SQL statements. Corresponding data query statements (i.e., parameter query SQL) can be generated according to the parameter matching strategy to query the corresponding parameter values in the data table storing the target pricing parameters.

[0068] Step S208, substituting the parameter values and adjustment values into the pricing formula for calculation to obtain the pricing result for pricing the pricing product, so as to adjust the pricing of the pricing product in real time according to the pricing result, where the adjustment value is the value determined by adjusting the parameter values based on the pricing request to determine the pricing result.

[0069] As Figure 3 shown, in this embodiment, the parameter values obtained in the above steps and the adjustment values obtained based on the pricing request can be substituted into the pricing formula for calculation to obtain the corresponding pricing result, and the pricing product can be priced according to the pricing result.

[0070] Next, in conjunction with Figure 4 the process of determining the adjustment value in the above embodiment of the present invention will be described in detail. Figure 4 is a flowchart of determining adjustment items according to an embodiment of the present invention.

[0071] According to the above embodiments of the present invention, before the above step S208, that is, before substituting the parameter value and the adjustment value into the pricing formula for calculation to obtain the pricing result of the priced product, the method further includes: generating a decision tree according to preset tags, where the decision tree includes multiple matching paths, each matching path corresponds to an adjustment item, each matching path includes multiple preset tags, and the preset tags are preset pricing restriction conditions; sequentially matching the priced product information in the pricing request with the preset tags on each matching path to obtain a matching result; determining the adjustment item of the matching path with the matching result being successful as the target adjustment item; calculating according to the item value of the target adjustment item to obtain an adjustment value.

[0072] Optionally, the above preset tags may include, but are not limited to: local tags (i.e., local preset tags in the embodiments of the present invention), external tags (i.e., external preset tags in the embodiments of the present invention).

[0073] As Figure 4 shown, the local tag here is the tag inside the product pricing model, which is a series of rules defined inside the product pricing model. Based on the pricing dictionary, it includes pricing fields, operators, and field values, and is used for internal decision-making and rule matching. These tags reflect the bank's business rules, strategies, and preset conditions for market conditions. For example, the local tag may include conditions such as "loan amount greater than 1 million" or "deposit term exceeding 1 year". The local tag is set by the bank internally and is used to automatically match the parameters and adjustment items in the database to ensure that the pricing model prices according to the bank's specific strategies; the external tag (also called the customer tag) is generally customer- or product-specific information provided by an external system and is directly used without internal decision-making in the model. The external tag may include customer credit ratings, market interest rates, customer historical transaction data, etc. These information provide a real-time view of the external environment or customer conditions, enabling the pricing model to make more personalized and accurate pricing calculations based on specific transactions or customer situations. For example, the external tag may include "customer credit rating is AAA level"; the local tag and the external tag can jointly participate in the matching of the decision tree to determine the value of a specific adjustment item.

[0074] Specifically, each path in the decision tree is determined by a combination of multiple tags, including any combination of local tags and external tags; each internal node of the decision tree represents a judgment condition for a tag or a combination of tags, and each leaf node represents a decision result, that is, the value of the adjustment item; during the construction of the tree, the tags and combinations of tags are placed on different nodes, forming a series of logical judgment paths that ultimately point to one or more leaf nodes, representing different decision results; when a pricing request enters the system, the system dynamically searches for a matching path in the decision tree based on the local tags and external tags carried in the request. If the request information meets all the tag conditions on a certain path, that path is considered to be successfully matched, and the corresponding adjustment item value will be used for pricing calculation; finally, the adjustment item values corresponding to all successfully matched paths can be calculated to obtain the parameter value for adjusting the parameter value to determine the pricing result.

[0075] In a specific embodiment of the present invention, the adjustment item of the matching path with the matching result determined to be successfully matched is the target adjustment item, including: when the pricing product information meets all the preset tags on the matching path, determining that the matching result is successfully matched; determining the matching path with the matching result determined to be successfully matched as the target matching path; when the target matching path only contains local preset tags, determining the adjustment item of the target matching path as the target adjustment item; when the target matching path contains external preset tags, adjusting the value of the adjustment item of the target matching path according to the external preset tags, and determining the adjusted adjustment item as the target adjustment item.

[0076] Specifically, each path in the decision tree can either contain only external tags, or only local tags, or both external tags and local tags; if a successfully matched path only contains local tags, the adjustment item value corresponding to that path can be directly used as the adjustment item value obtained on that path; if a successfully matched path contains external tags, the adjustment item value corresponding to that path can be adjusted according to its external tags, and the adjusted value is used as the adjustment item value obtained on that path; for example, if the credit rating is AAA, the adjustment of the adjustment item value is -0.5%. If the credit rating is AA, the adjustment item value is not adjusted. If the credit rating is A, the adjustment of the adjustment item value is +0.25%. If the credit rating is B, the adjustment of the adjustment item value is +0.5%. If the credit rating is C, the adjustment of the adjustment item value is +1%, and the adjusted value is used as the adjustment item value obtained on that path.

[0077] In another specific embodiment of the present invention, calculating an adjustment value according to the item value of the target adjustment item includes: determining the upper limit value of the adjustment value as the adjustment upper limit value according to the preset value range of the adjustment value, and determining the lower limit value of the adjustment value as the adjustment lower limit value; when there is only one target adjustment item, determining the item value of the target adjustment item as the total adjustment item value; when there are multiple target adjustment items, determining the sum of the item values of the multiple target adjustment items as the total adjustment item value; calculating an adjustment value according to the adjustment upper limit value, the adjustment lower limit value and the total adjustment item value by using a third formula, where the third formula is: A = min[max(AS, AD), AU], AS represents the total adjustment item value, AD represents the adjustment lower limit value, and AU represents the adjustment upper limit value.

[0078] Specifically, in order to avoid the impact on customer service caused by an overly high final pricing result and the revenue risk caused by an overly low pricing result, a range can be set for the adjustment value. If the sum of the adjustment item values on all paths (i.e., the total adjustment item value) is lower than the adjustment lower limit value of this range, then select the adjustment lower limit value as the parameter value for adjusting the parameter value to determine the pricing result; if the total adjustment item value is higher than the adjustment upper limit value of this range, then select the adjustment upper limit value as the parameter value for adjusting the parameter value to determine the pricing result; if the total adjustment item value is within this range, then the total adjustment item value can be selected as the parameter value for adjusting the parameter value to determine the pricing result. Specifically, the formula A = min[max(AS, AD), AU] can be used to implement this process, where AS represents the total adjustment item value, AD represents the adjustment lower limit value, and AU represents the adjustment upper limit value.

[0079] As can be seen from the above, through the technical solution provided by the above embodiment of the present invention, when a pricing request is received, the pricing request can be parsed to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the pricing of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula; determining the pricing parameters required in the pricing formula as the target pricing parameters; performing data matching in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters; substituting the parameter values and the adjustment value into the pricing formula for calculation to obtain the pricing result for pricing the pricing product, so as to adjust the pricing of the pricing product in real time according to the pricing result, where the adjustment value is the value for adjusting the parameter value based on the pricing request to determine the pricing result, achieving the purpose of selecting a pricing formula and matching the parameter values of the required pricing parameters based on the user's pricing request, so as to perform personalized configuration on the pricing formula by using the parameter values, thereby obtaining a pricing result more suitable for the pricing request, realizing the technical effect of flexibly and adaptively adjusting the pricing formula and parameters according to the user request, improving the flexibility and real-time performance of pricing, and enhancing the pricing efficiency.

[0080] Therefore, through the technical solution provided by the above embodiments of the present invention, the technical problem in the related art that most traditional product pricing models adopt a single pricing formula and parameter matching rule, resulting in difficult flexible adjustment of the pricing method, is solved.

[0081] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0082] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to enable a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of this application.

[0083] According to an embodiment of the present invention, there is also provided a personalized pricing device for implementing the above personalized pricing method. Figure 5 It is a schematic diagram of the personalized pricing device according to an embodiment of the present invention, as Figure 5 shown. The device includes: a first acquisition unit 51, a first determination unit 53, a second determination unit 55, and a second acquisition unit 57. The following is a detailed description of the personalized pricing device.

[0084] The first acquisition unit 51 is configured to, when receiving a pricing request, parse the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the price of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula.

[0085] The first determination unit 53 is configured to determine the pricing parameters required in the pricing formula as target pricing parameters.

[0086] The second determination unit 55 is configured to perform data matching in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters.

[0087] A second acquisition unit 57 is configured to substitute parameter values and adjustment values into a pricing formula for calculation to obtain a pricing result for pricing a priced product, so as to adjust the price of the priced product in real time according to the pricing result, where the adjustment value is a value determined by adjusting the parameter values based on a pricing request for determining the pricing result.

[0088] It should be noted here that the above-mentioned first acquisition unit 51, first determination unit 53, second determination unit 55, and second acquisition unit 57 correspond to steps S202 to S208 in the above-mentioned embodiment. The instances and application scenarios implemented by the four units and the corresponding steps are the same, but are not limited to the content disclosed in the above-mentioned embodiment.

[0089] As can be seen from the above, in the solution described in the above embodiment of the present invention, the first acquisition unit can, when receiving a pricing request, parse the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a priced product, the pricing formula is a formula for calculating the price of the priced product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula; then use the first determination unit to determine the pricing parameters required in the pricing formula as target pricing parameters; then use the second determination unit to perform data matching in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters; finally, use the second acquisition unit to substitute the parameter values and adjustment values into the pricing formula for calculation to obtain a pricing result for pricing the priced product, so as to adjust the price of the priced product in real time according to the pricing result, where the adjustment value is a value determined by adjusting the parameter values based on the pricing request for determining the pricing result, achieving the purpose of selecting a pricing formula and matching the parameter values of the required pricing parameters based on the user's pricing request, so as to perform personalized configuration on the pricing formula using the parameter values, thereby obtaining a pricing result more suitable for the pricing request, realizing the technical effect of flexibly adapting and adjusting the pricing formula and parameters according to the user's request, improving the flexibility and real-time performance of pricing, and improving the pricing efficiency.

[0090] Therefore, through the technical solution provided by the above embodiment of the present invention, the technical problem in the related art that most traditional product pricing models use a single pricing formula and parameter matching rule, resulting in difficult flexible adjustment of the pricing method, is solved.

[0091] In an alternative embodiment of the present invention, the first acquisition unit includes: a first acquisition module, configured to parse a pricing request to obtain the type of pricing product requested in the pricing request when receiving the pricing request; a first determination module, configured to determine the first formula as the pricing formula when the pricing product type is a loan product, where the first formula is: P = G + A, P represents the pricing result, G represents the break-even interest rate, and A represents the adjustment value; a second determination module, configured to determine the second formula as the pricing formula when the pricing product type is a deposit product, where the second formula is: P = B + A, and B represents the base interest rate; a third determination module, configured to determine the configuration formula configured based on the customization request information as the pricing formula when the pricing request includes customization request information, where the customization request information is information for requesting a customized pricing formula.

[0092] In an alternative embodiment of the present invention, the first acquisition unit includes: a second acquisition module, configured to parse a pricing request to obtain the type of pricing product requested in the pricing request and the pricing product information when receiving the pricing request, where the pricing product information at least includes: the currency of the pricing product, the term of the pricing product, and the pricing platform, and the pricing platform is the platform for pricing the pricing product; a fourth determination module, configured to determine the preset matching policy having a corresponding relationship with the pricing product type and the pricing product information in the database as the parameter matching policy, where the corresponding relationship means that the correlation between the parameter matching policy and the pricing product type or at least one piece of pricing product information is higher than the correlation threshold.

[0093] In an alternative embodiment of the present invention, the second determination unit includes: a fifth determination module, configured to determine the data table that the parameter matching policy needs to query as the target data table; a generation module, configured to generate a data query statement for querying the target data table according to the parameter matching policy; a third acquisition module, configured to perform a data query in the target data table according to the data query statement to obtain the parameter value of the target pricing parameter.

[0094] In an alternative embodiment of the present invention, the personalized pricing device further includes: a generation unit, configured to generate a decision tree according to preset tags before substituting the parameter value and the adjustment value into the pricing formula for calculation to obtain the pricing result of the pricing product, where the decision tree includes multiple matching paths, each matching path corresponds to an adjustment item, and each matching path includes multiple preset tags, and the preset tags are preset pricing restriction conditions; a third acquisition unit, configured to sequentially match the pricing product information in the pricing request with the preset tags on each matching path to obtain a matching result; a third determination unit, configured to determine the adjustment item of the matching path with a successful matching result as the target adjustment item; a fourth acquisition unit, configured to calculate according to the item value of the target adjustment item to obtain the adjustment value.

[0095] In an alternative embodiment of the present invention, the third determination unit includes: a sixth determination module, configured to determine that the matching result is a successful match when the pricing product information meets all the preset tags on the matching path; a seventh determination module, configured to determine the matching path with the matching result being a successful match as the target matching path; an eighth determination module, configured to determine the adjustment item of the target matching path as the target adjustment item when the target matching path only includes local preset tags; a ninth determination module, configured to, when the target matching path includes external preset tags, perform numerical adjustment on the adjustment item of the target matching path according to the external preset tags, and determine the adjusted adjustment item as the target adjustment item.

[0096] In an alternative embodiment of the present invention, the third determination unit includes: a tenth determination module, configured to determine the upper limit value of the adjustment value as the adjustment upper limit value according to the preset value range of the adjustment value, and determine the lower limit value of the adjustment value as the adjustment lower limit value; an eleventh determination module, configured to determine the item value of the target adjustment item as the total adjustment item value when there is only one target adjustment item; a twelfth determination module, configured to determine the sum of the item values of multiple target adjustment items as the total adjustment item value when there are multiple target adjustment items; a fourth acquisition module, configured to calculate the adjustment value according to the adjustment upper limit value, the adjustment lower limit value, and the total adjustment item value using the third formula, where the third formula is: A = min[max(AS, AD), AU], AS represents the total adjustment item value, AD represents the adjustment lower limit value, and AU represents the adjustment upper limit value.

[0097] On the other hand, according to an embodiment of the present invention, a personalized pricing system is further provided, and the personalized pricing system uses any one of the above personalized pricing methods.

[0098] On the other hand, according to an embodiment of the present invention, a computer-readable storage medium is further provided, and the computer-readable storage medium includes a stored program, where the program executes any one of the above personalized pricing methods.

[0099] Optionally, in this embodiment, the above computer-readable storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the communication devices in the communication device group.

[0100] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: when a pricing request is received, parse the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the price of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula; determine the pricing parameters required in the pricing formula as target pricing parameters; perform data matching in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters; substitute the parameter values and adjustment values into the pricing formula for calculation to obtain a pricing result for pricing the pricing product, so as to adjust the price of the pricing product in real time according to the pricing result, where the adjustment value is a value obtained by adjusting the parameter values based on the pricing request to determine the pricing result.

[0101] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: when a pricing request is received, parse the pricing request to obtain the type of the pricing product requested in the pricing request; when the type of the pricing product is a loan product, determine the first formula as the pricing formula, where the first formula is: P = G + A, P represents the pricing result, G represents the break-even interest rate, and A represents the adjustment value; when the type of the pricing product is a deposit product, determine the second formula as the pricing formula, where the second formula is: P = B + A, and B represents the base interest rate; when the pricing request includes customized request information, determine the configuration formula configured based on the customized request information as the pricing formula, where the customized request information is information for requesting a customized pricing formula.

[0102] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: when a pricing request is received, parse the pricing request to obtain the type of the pricing product and the pricing product information requested in the pricing request, where the pricing product information at least includes: the currency of the pricing product, the term of the pricing product, and the pricing platform, and the pricing platform is the platform for pricing the pricing product; determine the preset matching strategy in the database that has a corresponding relationship with the type of the pricing product and the pricing product information as the parameter matching strategy, where the corresponding relationship means that the correlation degree between the parameter matching strategy and the type of the pricing product or at least one piece of pricing product information is higher than the correlation threshold.

[0103] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determine the data table that the parameter matching strategy needs to query as the target data table; generate a data query statement for querying the target data table according to the parameter matching strategy; perform data query in the target data table according to the data query statement to obtain the parameter values of the target pricing parameters.

[0104] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: generating a decision tree according to preset tags, where the decision tree includes multiple matching paths, each matching path corresponds to an adjustment item, each matching path includes multiple preset tags, and the preset tags are preset pricing limit conditions; sequentially matching the pricing product information in the pricing request with the preset tags on each matching path to obtain a matching result; determining the adjustment item of the matching path with the matching result being successful as the target adjustment item; and calculating according to the item value of the target adjustment item to obtain an adjustment value.

[0105] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining that the matching result is successful when the pricing product information meets all the preset tags on the matching path; determining the matching path with the matching result being successful as the target matching path; determining the adjustment item of the target matching path as the target adjustment item when the target matching path only includes local preset tags; and when the target matching path includes external preset tags, numerically adjusting the adjustment item of the target matching path according to the external preset tags and determining the adjusted adjustment item as the target adjustment item.

[0106] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining the upper limit value of the adjustment value as the adjustment upper limit value and the lower limit value of the adjustment value as the adjustment lower limit value according to the preset value range of the adjustment value; determining the item value of the target adjustment item as the total adjustment item value when there is only one target adjustment item; determining the sum of the item values of multiple target adjustment items as the total adjustment item value when there are multiple target adjustment items; and calculating according to the adjustment upper limit value, the adjustment lower limit value, and the total adjustment item value using the third formula to obtain the adjustment value, where the third formula is: A = min[max(AS, AD), AU], AS represents the total adjustment item value, AD represents the adjustment lower limit value, and AU represents the adjustment upper limit value.

[0107] According to another aspect of the embodiments of the present invention, a processor is further provided, and the processor is used to run a program, where the program executes the personalized pricing method of any one of the above when running.

[0108] According to another aspect of the embodiments of the present invention, a computer program product is further provided, including computer instructions, and the computer instructions execute the personalized pricing method of any one of the above when executed by a processor.

[0109] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

[0110] In the above embodiments of the present invention, the descriptions of the various embodiments each have their own emphasis. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0111] In several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the units or modules can be in electrical or other forms.

[0112] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0113] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0114] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, 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. The computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. And the aforementioned storage medium includes: USB flash drives, read-only memory (ROM), random access memory (RAM), mobile hard disks, magnetic disks or optical discs and other various media that can store program codes.

[0115] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A personalized pricing method, characterized in that, including: When receiving a pricing request, parsing the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, where the pricing request is a request for pricing a pricing product, the pricing formula is a formula for calculating the pricing of the pricing product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula; Determining the pricing parameters required in the pricing formula as target pricing parameters; Performing data matching in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters; Substituting the parameter values and adjustment values into the pricing formula for calculation to obtain a pricing result for pricing the pricing product, so as to adjust the pricing of the pricing product in real time according to the pricing result, where the adjustment value is a value determined by adjusting the parameter values based on the pricing request to determine the pricing result.

2. The personalized pricing method according to claim 1, wherein When receiving a pricing request, parsing the pricing request to obtain a pricing formula corresponding to the pricing request, including: When receiving the pricing request, parsing the pricing request to obtain the pricing product type requested in the pricing request; When the pricing product type is a loan product, determining the first formula as the pricing formula, where the first formula is: P = G + A, P represents the pricing result, G represents the break-even interest rate, and A represents the adjustment value; When the pricing product type is a deposit product, determining the second formula as the pricing formula, where the second formula is: P = B + A, and B represents the base interest rate; When the pricing request includes customization request information, determining the configuration formula configured based on the customization request information as the pricing formula, where the customization request information is information for requesting to customize the pricing formula.

3. The personalized pricing method according to claim 1, wherein When receiving a pricing request, parsing the pricing request to obtain a parameter matching strategy corresponding to the pricing request, including: When receiving the pricing request, parsing the pricing request to obtain the pricing product type and pricing product information requested in the pricing request, where the pricing product information at least includes: pricing product currency, pricing product term, pricing platform, and the pricing platform is a platform for pricing the pricing product; Determining the preset matching strategy having a corresponding relationship with the pricing product type and the pricing product information in the database as the parameter matching strategy, where the corresponding relationship means that the relevance of the parameter matching strategy to the pricing product type or at least one of the pricing product information is higher than the correlation threshold.

4. The personalized pricing method according to claim 1, wherein, Performing data matching in the database according to the parameter matching strategy to determine the parameter values of the target pricing parameters, including: Determining the data table that the parameter matching strategy needs to query as the target data table; Generating a data query statement for querying the target data table according to the parameter matching strategy; Performing data query in the target data table according to the data query statement to obtain the parameter values of the target pricing parameters.

5. The personalized pricing method according to claim 1, wherein Before substituting the parameter value and the adjustment value into the pricing formula for calculation to obtain the pricing result of the priced product, the method further includes: Generating a decision tree according to preset tags, wherein the decision tree includes multiple matching paths, each matching path corresponds to an adjustment item, each matching path includes multiple preset tags, and the preset tags are preset pricing restriction conditions; Sequentially matching the priced product information in the pricing request with the preset tags on each matching path to obtain a matching result; Determining the adjustment item of the matching path with the matching result being successful as the target adjustment item; Calculating according to the item value of the target adjustment item to obtain the adjustment value.

6. The personalized pricing method according to claim 5, characterized in that, Determining the adjustment item of the matching path with the matching result being successful as the target adjustment item includes: When the priced product information meets all the preset tags on the matching path, determining the matching result as successful; Determining the matching path with the matching result being successful as the target matching path; When only local preset tags are included in the target matching path, determining the adjustment item of the target matching path as the target adjustment item; When external preset tags are included in the target matching path, numerically adjusting the adjustment item of the target matching path according to the external preset tags, and determining the adjusted adjustment item as the target adjustment item.

7. The personalized pricing method according to claim 5, wherein Calculating according to the item value of the target adjustment item to obtain the adjustment value includes: Determining the upper limit value of the adjustment value as the adjustment upper limit value according to the preset value range of the adjustment value, and determining the lower limit value of the adjustment value as the adjustment lower limit value; When there is only one target adjustment item, determining the item value of the target adjustment item as the total adjustment item value; When there are multiple target adjustment items, determining the sum of the item values of the multiple target adjustment items as the total adjustment item value; Calculating according to the adjustment upper limit value, the adjustment lower limit value and the total adjustment item value using a third formula to obtain the adjustment value, wherein the third formula is: A = min[max(AS, AD), AU], AS represents the total adjustment item value, AD represents the adjustment lower limit value, and AU represents the adjustment upper limit value.

8. A personalized pricing device, characterized in that, Including: A first obtaining unit, configured to, when receiving a pricing request, parse the pricing request to obtain a pricing formula and a parameter matching strategy corresponding to the pricing request, wherein the pricing request is a request for pricing a priced product, the pricing formula is a formula for calculating the pricing of the priced product, and the parameter matching strategy is a strategy for matching the parameters required by the pricing formula; A first determining unit, configured to determine the pricing parameters required in the pricing formula as target pricing parameters; A second determining unit, configured to perform data matching in a database according to the parameter matching strategy to determine the parameter values of the target pricing parameters; A second acquisition unit, configured to substitute the parameter value and the adjustment value into the pricing formula for calculation, so as to obtain a pricing result for pricing the pricing product, and to adjust the pricing of the pricing product in real time according to the pricing result, where the adjustment value is a value obtained by adjusting the parameter value based on the pricing request to determine the pricing result.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, where the program executes the personalized pricing 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 a processor, the personalized pricing method according to any one of claims 1 to 7 is executed.

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