Hotspot loan customer screening and customer data storage device and method

Abstract

The invention relates to the field of financial data management, and discloses a hotspot loan customer screening and customer data storage device and method, and the key point of the technical scheme is that the device comprises a configuration module, a registration module, a calculation module, a customer screening layering module and a storage module; the configuration module is used for configuring an accessed external service system and business index parameters, configuring a thermal value calculation strategy, configuring a customer hierarchy division strategy and configuring a customer information storage strategy; the registration module is used for accessing an external service system and receiving service data thrown by the external service system according to the service index parameters; the calculation module is used for calculating the received business data according to a thermodynamic value calculation strategy to obtain a customer thermodynamic value; the customer screening and layering module is used for carrying out hierarchical division on the customers according to the customer thermodynamic values and a customer hierarchical division strategy to obtain the hierarchy of each customer; and the storage module is used for performing hierarchical storage on the customer information according to the customer hierarchy and the customer information storage strategy.

Description

Technical Field

[0001] The present invention relates to the field of financial data management, and more specifically, to a device and method for screening hotspot loan customers and storing customer data. Background Art

[0002] With the continuous improvement of the level of science and technology in modern society, the continuous enrichment of financial products, and the continuous integration of finance and technology. Financial products are a good application scenario of technology, and technology continues to support the development of finance. The two complement each other. Because of the combination of technology, the financial products around us are becoming more and more abundant. In the past, you might have to go to designated places to buy financial products, such as exchanges, banks, etc., which was very inconvenient and time-consuming and laborious. But now financial products are often around us, and we can buy financial products very well just by moving our fingers. Among them, loan products are an extremely important part of financial products. Therefore, in order to provide hot customers with a better user experience and better loan services, how to efficiently identify hot customers and store hot customer information has become a very important part of various financial institutions. Through existing surveys and research, it is found that the existing commonly used processing methods have the following problems and deficiencies:

[0003] Full storage method: All customer information is considered as hot customers and stored in a high-speed cache. This method is acceptable when the customer scale is small, but once the number of customers reaches millions, it will put huge pressure on cache storage resources and customers are not effectively screened.

[0004] Transaction access mechanism: When a customer has a real transaction, the customer is identified as a hot customer and stored in the cache so that the customer can have a better user experience the next time. Although this can screen some customers, it will fail to identify some potential customers or lead to the loss of potential customers. This will also mistakenly identify many customers with invalid transactions as hot customers, resulting in a high natural misidentification rate. When the amount of subsequent transaction data is large, there will also be great storage pressure.

[0005] Transaction access and cache expiration mechanism: Based on the transaction access mechanism, a fixed cache storage duration is set for customers. If no transaction occurs, customer information will be removed to reduce resource waste. However, there is uncertainty in the setting of storage duration. Too long or too short may lead to resource waste or loss of important customer information.

[0006] The data source is relatively single: only customers who have loan transactions are defined as hot customers, but the actual situation is that many other transaction behaviors of customers can also screen customers as hot customers. For example, large cash withdrawals by customers may be one of the potential factors indicating that customers need funds. For example, customers' purchase of financial products can also be considered as one of the potential factors indicating that customers need users. The number of times customers browse and the length of time they stay on the website can all be screened as factors that indicate hot customers of loan products. The screening of hot customers is multi-dimensional, not just a single aspect. Summary of the invention

[0007] The purpose of the present invention is to provide a hot loan customer screening and customer data storage device, which can accurately screen hot customers and calculate the customer's thermal value based on the big data streaming computing capability. According to the thermal value, the system divides customers into different levels and realizes dynamic storage management of customer information. This not only ensures the efficient use of storage resources, but also improves the accuracy and response speed of customer service.

[0008] The above technical objectives of the present invention are achieved through the following technical solutions: A hotspot loan customer screening and customer data storage device, comprising: a configuration module, a registration module, a calculation module, a customer screening and stratification module, and a storage module;

[0009] The configuration module is used to configure the connected external service system and the corresponding business indicator parameters, configure the thermal value calculation strategy, configure the customer level division strategy, and configure the customer information storage strategy;

[0010] The registration module is used to access the external service system and receive the business data sent by the external service system according to the business indicator parameters;

[0011] The calculation module is used to calculate the received business data according to the thermal value calculation strategy to obtain the customer thermal value;

[0012] The customer screening and stratification module is used to classify customers into different levels according to the customer heat value and the customer level classification strategy to obtain the level of each customer;

[0013] The storage module is used to store customer information in a hierarchical manner according to customer levels and customer information storage strategies.

[0014] As a preferred technical solution of the present invention, the thermal value calculation strategy includes:

[0015] An indicator weight list, which includes indicator items, indicator item weights, indicator item classification ranges, and classification values;

[0016] The calculation method of customer thermal value is:

[0017] Query the current customer's grading weight value for each indicator item: obtain the customer's business data, retrieve the indicator item grading range that the customer's business data meets through the indicator weight list, and obtain the current customer's grading value for each indicator item;

[0018] Calculate the weight value of the current customer in each indicator item: multiply the graded value of each indicator item by the indicator item weight of the current indicator item to obtain the weight value of the current customer in each indicator item;

[0019] Calculate the heat value of the current customer: add up the weight values ​​of the current customer in each indicator item to get the heat value of the current customer.

[0020] As a preferred technical solution of the present invention, the thermal value calculation strategy is also provided with a time interval calculation rule, and the time interval calculation rule includes: designing a number of time windows for the calculation action of the customer's thermal value, collecting and accepting the indicator data sent by the business system within a time window, and performing weighted calculation according to the configured indicator weight to update the customer's latest thermal value.

[0021] As a preferred technical solution of the present invention, a customer level division table is established in the customer level division strategy, and the customer level division table includes customer levels and corresponding customer thermal value intervals.

[0022] As a preferred technical solution of the present invention, the configuration module is used to provide a visual configuration interface; the computing module is provided with a big data computing platform for performing streaming computing on business data.

[0023] As a preferred technical solution of the present invention, the storage module uses the middleware Redis to store customer information in a hierarchical manner;

[0024] The customer information storage strategy: the customer information corresponding to the customer with a higher thermal value has a longer storage period, and the customer information corresponding to the customer with a lower thermal value has a shorter storage period;

[0025] The customer information storage policy is provided with a storage schedule, and the storage schedule includes customer levels and corresponding customer information storage validity periods.

[0026] As a preferred technical solution of the present invention, the registration module is provided with a data standard processing submodule, and the data standard processing submodule is used to perform standard processing on the received business data to obtain business data in a standard format that can be directly input into the calculation module for calculation.

[0027] As a preferred technical solution of the present invention, the registration module and the external service system are connected in a heartbeat detection manner. When the registration module detects that the external service system is unavailable, the external service system and the corresponding indicator parameters are removed from the registration list until the registration module detects that the external service system is available again, and then the external service system and the corresponding indicator parameters are restored in the registration list.

[0028] A method for screening hot loan customers and storing customer data comprises the following steps:

[0029] Pre-configure the external service system to be connected and the corresponding business indicator parameters, configure the thermal value calculation strategy, configure the customer tier division strategy, and configure the customer information storage strategy;

[0030] Access external service systems and receive business data sent by external service systems according to business indicator parameters;

[0031] Calculate the received business data according to the thermal value calculation strategy to obtain the customer thermal value;

[0032] According to the customer heat value and customer tier division strategy, customers are divided into tiers to obtain the tier of each customer;

[0033] Customer information is stored in a hierarchical manner according to customer levels and customer information storage strategies.

[0034] In summary, the present invention has the following beneficial effects: the device is standardized and independent of other external service information services, and the device allows the process of screening loan users without coding, and only requires flexible configuration through the visual interface of the configuration module. At the same time, a unified external open interface is provided through the registration module, and other external service systems only need to follow the standard interface specifications for access and data transmission.

[0035] The device of the present invention can complete the registration, discovery and validation process of new data sources. Business personnel can dynamically adjust the weights of different data sources. The device will automatically push the collected data to the big data Flink platform of the computing module for streaming calculation based on these weight information to calculate the customer's thermal value. Based on the calculation results, customers can be divided into levels, and a hierarchical storage strategy for customer information can be implemented through the middleware Redis of the storage module. Customer information with higher thermal values ​​has a longer storage time in Redis, while customer information with lower thermal values ​​has a shorter storage time. Such a design not only optimizes the utilization of storage resources, but also significantly improves the actual experience of customers under limited resource conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a connection diagram of the device modules of the present invention;

[0037] Figure 2 It is a registration module architecture diagram of the present invention;

[0038] Figure 3 It is a configuration module architecture diagram of the present invention;

[0039] Figure 4 It is a schematic diagram of the time window of the present invention. DETAILED DESCRIPTION

[0040] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0041] like Figure 1 As shown, the present invention provides a hotspot loan customer screening and customer data storage device, including: a configuration module, a registration module, a calculation module, a customer screening and stratification module, and a storage module;

[0042] like Figure 3 As shown, the configuration module is used to configure the external service system to be connected and the corresponding business indicator parameters, configure the thermal value calculation strategy, configure the customer level division strategy, and configure the customer information storage strategy; the configuration module is used to provide a visual configuration interface;

[0043] The configuration module of this device is a back-end configuration system developed based on the vue+iviewUI front-end development framework. It realizes the full visual configuration of access to external service systems and access indicator parameters. The accessed external service system sends data according to the standard interface, and this device will automatically collect the data. Business personnel configure the accessed external service system, the name of the accessed business indicator, the weight of the accessed business indicator, the validity period of the accessed business indicator, the threshold of the business indicator, the effective time of the indicator, the expiration time and other business indicator configurations in the back-end, and flexibly set them according to actual needs. Then the device of the present invention will calculate according to a certain algorithm formula based on the indicators of the business configuration to calculate the customer's thermal value.

[0044] like Figure 2 As shown, the registration module is used to access the external service system and receive the business data sent by the external service system according to the business indicator parameters;

[0045] The registration module is provided with a data standard processing submodule, which is used to perform standard processing on the received business data to obtain business data in a standard format that can be directly input into the calculation module for calculation;

[0046] The registration module and the external service system are connected in a heartbeat detection manner. When the registration module detects that the external service system is unavailable, the external service system and the corresponding indicator parameters are removed from the registration list until the registration module detects that the external service system is available again, then the external service system and the corresponding indicator parameters are restored in the registration list.

[0047] The registration module of the present invention is a registration center built based on zookeeper. The external service system that needs to be connected only needs to be simply configured to register with the registration center. The registration center can implement the health check of the external service system that is connected. The two are connected by a heartbeat detection connection, thereby realizing automatic and regular checks on the status of the registered external service system. When the external service system is unavailable, the external service system will be automatically offline and removed. At the same time, if the registered external service system resumes service, the service will be automatically discovered so that the configuration center can use and configure the business indicators thrown by this external service system.

[0048] Among them, the external service system includes a credit service system, a loan service system, a financial service system, and a deposit service, etc. The connected system only needs to send the business data to the agreed kafka middleware according to the standard interface, and the data standard processing submodule can receive the data. The device of the present invention can automatically collect data, summarize and calculate the collected data.

[0049] A calculation module is used to calculate the received business data according to the thermal value calculation strategy to obtain the customer's thermal value;

[0050] The computing module is equipped with a big data computing platform for performing streaming computing on business data.

[0051] Thermal value calculation strategies include:

[0052] Indicator weight list, which includes indicator items, indicator item weights, indicator item classification range, and classification values;

[0053] The calculation method of customer thermal value is:

[0054] Query the current customer's grading weight value for each indicator item: obtain the customer's business data, retrieve the indicator item grading range that the customer's business data meets through the indicator weight list, and obtain the current customer's grading value for each indicator item;

[0055] Calculate the weight value of the current customer in each indicator item: multiply the graded value of each indicator item by the indicator item weight of the current indicator item to obtain the weight value of the current customer in each indicator item;

[0056] Calculate the heat value of the current customer: add up the weight values ​​of the current customer in each indicator item to get the heat value of the current customer.

[0057] Specifically, the calculation module is the core functional module of this device. After the business personnel configure the relevant business parameters at the front desk, they will perform calculations based on the standard parameters thrown by each business system. Taking into account the sensitivity of the access data, the business system will not transmit precise values, but will send a data range to protect customer privacy. For example, when processing customer withdrawals, the system will connect with the deposit system to transmit the proportion of the customer's withdrawal amount to the total balance; in financial service access, what is transmitted is the range of the amount of the customer's purchase of financial products; and in the credit service, the customer's credit results are transmitted, etc.

[0058] These multi-dimensional indicators from different systems all follow a unified standard interface field for data transmission. All the parameters of these business systems will become the input parameters of the calculation module, and the corresponding result values ​​will be calculated by calculating these parameters. The following is a specific example to illustrate.

[0059] Taking the deposit and financial management system value indicators as an example, the following is a list of corresponding deposit system indicators and financial management system indicator weights.

[0060] Table 1-Deposit system indicator weight list:

[0061]

[0062] Table 2-Wealth Management System Index Weight List:

[0063]

[0064] After the business personnel have set the above indicators, they can calculate according to the thrown indicators. First, according to the configured total indicator weight, calculate the indicator value of each indicator, formula: f(x1) = a1 / (a1+a2+a3+…+an), and find the weight of the indicator in the total. Then calculate the weight value of the specific indicator in a single indicator, formula: f(x2) =

[0065] b1 / (b1+b2+b3+…+bn), to find the weight of the sub-index in the current index. After calculating the weight of the index and the corresponding sub-index, calculate the result again f(y)=f(x1)*f(x2), which is the weight of the customer in the current index project. After getting all the index results, perform weighted summary of all the indicators and apply the formula: F(z)=f(y1)+f(y2)+f(y3). After combining the above multiple indicators, the customer's thermal value can be calculated.

[0066] like Figure 4As shown, as an embodiment of the present invention, a time interval calculation rule is also provided in the thermal value calculation strategy, and the time interval calculation rule includes: designing a number of time windows for the calculation action of the customer's thermal value, collecting and accepting the indicator data thrown by the business system within a time window, and performing weighted calculation according to the configured indicator weights to update the customer's latest thermal value.

[0067] The calculation module relies on the message queue and the big data flink processing platform. Through the time interval calculation rules, that is, setting the size of the sliding statistical time window and using various aggregation operators, it calculates the customer's various indicator values ​​and sub-indicator values ​​within a certain period of time, and performs weighted calculation on each score according to the corresponding weight, and finally obtains the final thermal value representing the hot customer.

[0068] Specifically, when the calculated thermal value has an error or the weight of a certain indicator needs to be increased or decreased, the business personnel can adjust the parameters in the background to achieve the optimal result. After the business personnel complete the back-end adjustment, the latest rules will automatically take effect and apply the business rules to the calculation center, which can then calculate the latest value based on the latest rules. Business personnel can also see the customer's latest thermal value calculation results. As a result, the device realizes real-time tuning of parameters and ensures the real-time nature of business results, which can effectively provide technical and data support for subsequent business operations.

[0069] The customer screening and stratification module is used to classify customers according to their heat value and customer stratification strategy to obtain the stratification of each customer;

[0070] A customer tier division table is established in the customer tier division strategy, and the customer tier division table includes customer tiers and corresponding customer thermal value ranges.

[0071] The customer screening and stratification module screens customers based on the thermal value calculated in the previous step. For example, customers are temporarily divided into 6 levels. The following is the branch range of thermal value and the corresponding customer stratification.

[0072] Table 3-Customer Tier Classification Table:

[0073]

[0074] After customers are stratified, targeted marketing and customer experience optimization can be carried out. For example, more practical products can be introduced to hot customers, customer information can be cached for hot customers so that they have a good interactive experience, and different promotional activities can be carried out for hot customers at different levels.

[0075] The storage module is used to store customer information in a hierarchical manner according to customer levels and customer information storage strategies. The storage module uses the middleware Redis to store customer information in a hierarchical manner;

[0076] Customer information storage strategy: The customer information corresponding to the customer with a higher thermal value has a longer storage period, and the customer information corresponding to the customer with a lower thermal value has a shorter storage period;

[0077] A storage schedule is set in the customer information storage policy, and the storage schedule includes customer levels and corresponding customer information storage validity periods.

[0078] Specifically, after calculating the customer's thermal value and stratifying the customers according to the thermal value, the hot customers are stored based on the cache middleware redis. Customers at different levels can set different cache times so that customers can have a better user experience when they use the product later. A dynamic cache mechanism is organized according to different customer tier division schemes. This ensures that storage resources can be maximized when storage resources are limited. The following is a cache storage mechanism designed based on different levels of customers.

[0079] Table 4 - Storage schedule:

[0080]

[0081] After setting different thermal values ​​and levels for customers, a dynamic customer information storage mechanism can be implemented. This method effectively avoids the problem that a large amount of customer information may become invalid at a specific time point due to the traditional unified time mechanism, and also reduces the excessive consumption of resources by full storage. The customer's storage mechanism is not static, but is flexibly adjusted with the real-time changes of the customer's thermal value. Within a statistical period, the customer's different operating behaviors will be calculated in real time by the calculation module according to the thermal value calculation strategy, thereby giving the customer different thermal values ​​and realizing dynamic adjustment of the customer level. This mechanism ensures the dynamic and adaptable nature of the customer storage strategy.

[0082] From the initial access of data to the real-time processing in the middle, and then to the final storage strategy, this device ensures the continuity, real-time and data accuracy of the entire business process. Through this end-to-end dynamic management, it not only optimizes the efficiency of resource use, but also improves customer experience, ensuring the immediacy of business response and the accuracy of data processing.

[0083] Corresponding to the above-mentioned device, the present invention also provides a method for screening hot loan customers and storing customer data, comprising the following steps:

[0084] S1. Pre-configure the external service system to be connected and the corresponding business indicator parameters, configure the thermal value calculation strategy, configure the customer level division strategy, and configure the customer information storage strategy;

[0085] Business personnel perform independent business configuration in the back-end of the device, and configure parameter information of indicators of different systems, such as weight information, threshold information, parameter names, etc.

[0086] S2. Access the external service system and receive the business data sent by the external service system according to the business indicator parameters; after the external service system is connected, the data is sent according to the standard interface format, and the device can obtain the data and perform secondary processing on the data so that the data is converted into data that can be recognized by the device.

[0087] S3. Calculate the received business data according to the thermal value calculation strategy to obtain the customer thermal value;

[0088] The calculation module combines the received business data, business indicators configured by the backend, and other information, and uses the big data Flink calculation tool to perform comprehensive calculations on various indicators and calculate the final customer thermal value.

[0089] S4. According to the customer heat value and the customer level division strategy, the customers are divided into levels to obtain the level of each customer;

[0090] S5. According to the customer level and customer information storage strategy, the customer information is stored hierarchically. After obtaining the final result, the device can visualize the final result to the business personnel so that accurate parameter tuning can be performed.

[0091] The technical advantages of the hot loan customer screening and customer data storage device and method of the present invention are: the device is a standardized device that is independent of other external service information services, and the device allows the process of screening loan users without coding, and only requires flexible configuration through the visual interface of the configuration module. At the same time, a unified external open interface is provided through the registration module, and other external service systems only need to follow the standard interface specifications for access and data transmission.

[0092] The device of the present invention can complete the registration, discovery and validation process of new data sources. Business personnel can dynamically adjust the weights of different data sources. The device will automatically push the collected data to the big data Flink platform of the computing module for streaming calculation based on these weight information to calculate the customer's thermal value. Based on the calculation results, customers can be divided into levels, and a hierarchical storage strategy for customer information can be implemented through the middleware Redis of the storage module. Customer information with higher thermal values ​​has a longer storage time in Redis, while customer information with lower thermal values ​​has a shorter storage time. Such a design not only optimizes the utilization of storage resources, but also significantly improves the actual experience of customers under limited resource conditions.

[0093] The customer screening and dynamic storage solution of the present invention can perform multi-dimensional fine data evaluation, diversified data source integration, flexible configuration management and highly automated processing. Relying on the big data streaming computing capability, it can accurately screen hot customers and calculate the thermal value of customers. According to the thermal value, the system divides customers into different levels and realizes dynamic storage management of customer information. This not only ensures the efficient use of storage resources, but also improves the accuracy and response speed of customer service.

[0094] The device in the present invention is independent of the business process, but serves the business. Business personnel pay attention to the configuration of business weights and other related parameters, and continuously tune the parameters according to the final calculation results, so as to efficiently identify hot customers and store hot customers. The effective management of these data can, on the one hand, enable targeted system optimization of these hot customers and improve the customer experience, and on the other hand, it can also provide one of the reference bases for subsequent product operations and customer portrait analysis.

[0095] Specifically, the advantages of the device and method of the present invention include:

[0096] The device has the independence of business processes and achieves a high degree of decoupling from business processes. Business personnel can independently set business indicators, and the device automatically calculates the customer's thermal value based on these indicators, thereby effectively identifying hot customers and improving the flexibility of operations and the adaptability of the system.

[0097] The device has standardized service access capabilities. The external service system that is connected only needs to follow the established standard process for registration and access, and transmit data through the standard interface. This enables the device to respond quickly to business data, providing excellent scalability and convenient integration experience.

[0098] The registration module of this device has a built-in automatic heartbeat detection mechanism, which can monitor the availability of the registration service in real time. Once the service is found to be unavailable, the system will automatically exclude the relevant business indicators, ensuring the authenticity and accuracy of the data indicators.

[0099] This device can make a comprehensive score based on the diverse indicators provided by different external service systems, such as pass rate, withdrawal rate, purchase rate, etc., so as to fully calculate the customer's thermal value and ensure the accuracy and comprehensiveness of the evaluation results.

[0100] In terms of customer information storage, this device not only draws on the experience of traditional storage solutions, but also specifically solves problems such as excessive resource usage and information "avalanche". With limited storage resources, it achieves efficient resource utilization and optimizes storage efficiency.

[0101] This device concretizes the customer's operation behavior and presents it intuitively in the form of thermal values, providing business personnel with a clear data view. This intuitive display facilitates business personnel to conduct subsequent operation analysis and work decision-making.

[0102] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A device for screening hotspot loan customers and storing customer data, characterized in that: include: Configuration module, registration module, calculation module, customer screening and stratification module, storage module; The configuration module is used to configure the connected external service system and the corresponding business indicator parameters, configure the thermal value calculation strategy, configure the customer level division strategy, and configure the customer information storage strategy; The registration module is used to access the external service system and receive the business data sent by the external service system according to the business indicator parameters; The calculation module is used to calculate the received business data according to the thermal value calculation strategy to obtain the customer thermal value; The customer screening and stratification module is used to classify customers into different levels according to the customer heat value and the customer level classification strategy to obtain the level of each customer; The storage module is used to store customer information in a hierarchical manner according to customer levels and customer information storage strategies.

2. A hotspot loan customer screening and customer data storage device according to claim 1, characterized in that: The thermal value calculation strategy includes: An indicator weight list, which includes indicator items, indicator item weights, indicator item classification ranges, and classification values; The calculation method of customer thermal value is: Query the current customer's grading weight value for each indicator item: obtain the customer's business data, retrieve the indicator item grading range that the customer's business data meets through the indicator weight list, and obtain the current customer's grading value for each indicator item; Calculate the weight of each indicator item for the current customer: multiply the graded value of each indicator item by the indicator item weight of the current indicator item to obtain the weight of each indicator item for the current customer; Calculate the heat value of the current customer: add up the weight values ​​of the current customer in each indicator item to get the heat value of the current customer.

3. A hotspot loan customer screening and customer data storage device according to claim 2, characterized in that: The thermal value calculation strategy is also provided with time interval calculation rules, and the time interval calculation rules include: designing several time windows for the calculation action of the customer's thermal value, collecting and accepting the indicator data sent by the business system in each time window, and performing weighted calculation according to the configured indicator weight to update the customer's thermal value.

4. A hotspot loan customer screening and customer data storage device according to claim 3, characterized in that: A customer level division table is established in the customer level division strategy, and the customer level division table includes customer levels and corresponding customer thermal value intervals.

5. A hotspot loan customer screening and customer data storage device according to claim 4, characterized in that: The configuration module is used to provide a visual configuration interface; the computing module is provided with a big data computing platform for performing streaming computing on business data.

6. A hotspot loan customer screening and customer data storage device according to claim 5, characterized in that: The storage module uses the middleware Redis to store customer information in a hierarchical manner; The customer information storage strategy: the customer information corresponding to the customer with a higher thermal value has a longer storage period, and the customer information corresponding to the customer with a lower thermal value has a shorter storage period; The customer information storage policy is provided with a storage schedule, and the storage schedule includes customer levels and corresponding customer information storage validity periods.

7. A hotspot loan customer screening and customer data storage device according to claim 6, characterized in that: The registration module is provided with a data standard processing submodule, and the data standard processing submodule is used to perform standard processing on the received business data to obtain business data in a standard format that can be directly input into the calculation module for calculation.

8. A hotspot loan customer screening and customer data storage device according to claim 7, characterized in that: The registration module and the external service system are connected in a heartbeat detection manner. When the registration module detects that the external service system is unavailable, the external service system and the corresponding indicator parameters are removed from the registration list until the registration module detects that the external service system is available again, then the external service system and the corresponding indicator parameters are restored in the registration list.

9. A method for screening hot loan customers and storing customer data, characterized in that: The steps include: Pre-configure the external service system to be connected and the corresponding business indicator parameters, configure the thermal value calculation strategy, configure the customer tier division strategy, and configure the customer information storage strategy; Access external service systems and receive business data sent by external service systems according to business indicator parameters; Calculate the received business data according to the thermal value calculation strategy to obtain the customer thermal value; According to the customer heat value and customer tier division strategy, customers are divided into tiers to obtain the tier of each customer; Customer information is stored in a hierarchical manner according to customer levels and customer information storage strategies.

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