Custom rule risk indicator early warning method and system based on data mining

Abstract

The invention belongs to the technical field of rule monitoring and early warning, and discloses a custom rule risk indicator early warning method and system based on data mining. The method comprises the following steps: customizing monitoring data grades on a monitoring rule definition page according to business requirements and policy requirements of a current area, wherein the custom monitoring data grades comprise a public accumulation fund personal loan rate grade, a mobility guarantee multiple grade and a business fund net flow grade; key data of a public accumulation fund center are collected, wherein the key data comprise public accumulation fund loan balance, public accumulation fund payment balance, non-business fund expenditure of the current month, public accumulation fund extraction amount of the current month, public accumulation fund payment amount of the current month, public accumulation fund loan amount of the current month and public accumulation fund loan recovery capital of the current month; according to the invention, the management personnel can flexibly customize the monitoring rule according to the business requirements and the policy change, so that the management personnel can quickly adapt to the policy change and adjust the monitoring strategy in time.

Description

Technical Field

[0001] The present invention relates to the technical field of rule monitoring and early warning, and more specifically, to a custom rule risk indicator early warning method and system based on data mining. Background Art

[0002] The existing Chinese patent with publication number CN115564564A proposes a housing fund credit loan risk monitoring system, which includes five functional modules: housing fund unit whitelist management module, log management module, early warning management module, parameter setting module and unit statistics module. The system effectively prevents risks arising in the credit process and promptly warns of risks. Relevant personnel can identify risks and check risks at the first time, take effective measures to reduce credit risks to the greatest extent, and achieve the purpose of controlling risks to a certain extent; the system provides daily management functions for credit business, such as uploading unit whitelists, counting loan information of unit employees, etc., which provides a strong guarantee for business management;

[0003] Although the above method can meet most scenarios, research and practical application of the above method and the prior art have found that the above method and the prior art have at least the following defects.

[0004] When monitoring the risks of provident fund credit loans, the income and expenditure of the provident fund center's funds are not taken into consideration; this may result in insufficient inflow of business funds to meet the business needs of housing provident fund withdrawals, loans, etc., or when there are sufficient funds, the funds cannot be fully utilized, resulting in idle funds and low returns.

[0005] When the system detects provident fund credit loan risks, it cannot customize the measures and rules for the risks, and the system cannot automatically make decisions and execute them based on the measures and rules.

[0006] In view of this, the present invention proposes a risk indicator early warning method and system based on customized rules for data mining to solve the above problems. Summary of the invention

[0007] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solution: a risk indicator early warning method based on customized rules of data mining, comprising:

[0008] Customize the monitoring data level on the monitoring rule definition page according to the business needs and policy requirements of the current region. The customized monitoring data level includes the provident fund individual loan rate level, the liquidity guarantee multiple level and the business fund net flow level;

[0009] Collect key data from the Provident Fund Center, including the Provident Fund loan balance, Provident Fund deposit balance, non-business fund expenditures for the month, Provident Fund withdrawal amount for the month, Provident Fund deposit amount for the month, Provident Fund loan amount for the month, and Provident Fund loan principal and interest collected for the month;

[0010] Process key data to obtain the individual housing provident fund loan rate, net business fund flow and liquidity guarantee multiple for the month;

[0011] According to the individual housing provident fund loan rate, the net business fund flow and the liquidity guarantee multiple of the month, it is judged whether to trigger the preset rule engine; if the rule engine is triggered, an early warning message is automatically generated and reported; the early warning message includes the rules of the rule engine and the early warning level; the early warning level includes the first-level early warning, the second-level early warning and the third-level early warning;

[0012] When generating warning information, customize the action rules on the action rule definition page according to the business needs and policy requirements of the current region;

[0013] The measure rules defined on the measure rule definition page will automatically generate policy change notifications on the provident fund center's official website.

[0014] Furthermore, the definition method of the provident fund individual loan rate level is:

[0015] On the monitoring rule definition page, customize the four provident fund individual loan rates of α1, α2, α3 and α4, α1<α2<α3<α4; if the provident fund individual loan rate is less than α1, the corresponding provident fund individual loan rate is too low; if the provident fund individual loan rate is greater than or equal to α1 and less than or equal to α2, the corresponding provident fund individual loan rate is low; if the provident fund individual loan rate is greater than α2 and less than α3, the corresponding provident fund individual loan rate is normal; if the provident fund individual loan rate is greater than or equal to α3 and less than or equal to α4, the corresponding provident fund individual loan rate is high; if the provident fund individual loan rate is greater than α4, the corresponding provident fund individual loan rate is too high.

[0016] Furthermore, the definition method of liquidity guarantee multiple levels is as follows:

[0017] On the monitoring rule definition page, you can customize three liquidity protection multiples, β1, β2 and β3, where β1<β2<β3; if the liquidity protection multiple is less than β1, it corresponds to insufficient liquidity; if the liquidity protection multiple is greater than or equal to β1 and less than or equal to β2, it corresponds to tight liquidity; if the provident fund individual loan rate is greater than β2 and less than β3, it corresponds to normal liquidity; if the liquidity protection multiple is greater than or equal to β3, it corresponds to excess liquidity.

[0018] Furthermore, the definition method of the business capital net flow level is:

[0019] On the monitoring rule definition page, customize the two business net capital flows γ1 and γ2, γ1<γ2; if the business net capital flow is less than γ1, the corresponding business net capital flow will be reduced; if the business net capital flow is greater than or equal to γ1 and less than or equal to γ2, the corresponding business net capital flow will be balanced; if the business net capital flow is greater than γ2, the corresponding business net capital flow will be enlarged.

[0020] Furthermore, the calculation formula of the provident fund individual loan rate is:

[0021]

[0022] The provident fund loan balance refers to the total amount of all provident fund loans that have been issued but not yet repaid; the provident fund deposit balance refers to the total balance of all provident fund accounts, that is, all provident fund deposits held by the provident fund center;

[0023] The calculation formula for the net flow of business funds is:

[0024] Net business capital flow = (the amount of provident fund deposits in the current month + the principal and interest of provident fund loans collected in the current month) -

[0025] (Amount of provident fund withdrawal in that month + amount of provident fund loan in that month);

[0026] The calculation formula of the liquidity protection multiple is:

[0027]

[0028] Furthermore, the method for generating the warning information includes:

[0029] Step 1: Match the individual housing fund loan rate of the current month with the individual housing fund loan rate level in the custom monitoring data level to obtain the individual housing fund loan rate level of the current month; match the net business fund flow of the current month with the net business fund flow level in the custom monitoring data level to obtain the net business fund flow level of the current month; match the liquidity guarantee multiple of the current month with the liquidity guarantee multiple level in the custom monitoring data level to obtain the liquidity guarantee multiple level of the current month;

[0030] Step 2: Generate warning levels based on the rules of the rule engine;

[0031] The method for generating the warning level is:

[0032] When the provident fund individual loan rate is too high, liquidity is insufficient or tight, and the net flow of business funds decreases, the rule engine is triggered, and the warning level is level three;

[0033] When the individual housing provident fund loan rate is too low, liquidity is excessive, and the net flow of business funds is enlarged, the rule engine is triggered, and the warning level is level three;

[0034] When the provident fund individual loan rate is high, liquidity is normal or excess liquidity and the net flow of business funds is enlarged, the rule engine is triggered and the warning level is level 2 warning;

[0035] When the individual housing provident fund loan rate is low, liquidity is tight, and the net flow of business funds decreases, the rule engine is triggered and the warning level is level 2.

[0036] When the individual housing provident fund loan rate is low, liquidity is normal, and the net flow of business funds is balanced, the rule engine is triggered and the warning level is level one;

[0037] When the individual housing provident fund loan rate is high, liquidity is normal, and the net flow of business funds is balanced, the rule engine is triggered and the warning level is level one;

[0038] Step 3: Match the provident fund individual loan rate level, the business fund net flow level and the liquidity guarantee multiple level of the current month with the rules of the rule engine. If the match is successful, the rule engine is triggered and step 4 is executed; if the match is unsuccessful, the rule engine is not triggered and the process ends;

[0039] Step 4: Generate warning information and report the warning information.

[0040] Furthermore, the method for customizing the measure rule includes:

[0041] When the triggered rule is that the provident fund individual loan rate is too high, liquidity is insufficient or liquidity is tight, and the net flow of business funds is reduced:

[0042] Modify the provident fund loan multiple: adjust the current A1 times to A2 times, where A1 is greater than A2; add the provident fund loan multiple A2 defined on the measure rule definition page to the request message, call the provident fund loan multiple modification interface, and modify the provident fund loan multiple;

[0043] Suspend the "commercial to public" loan business: the system automatically calls the "commercial to public" loan business interface and closes the "commercial to public" application interface;

[0044] Carry out the "public-to-private" loan business: call the "public-to-private" loan business modification interface and open the "public-to-private" application interface;

[0045] Add restrictions on provident fund loan applications: add the application restrictions defined on the measure rule definition page to the request message, and call the provident fund loan application restriction modification interface; the application restrictions include that the provident fund loan applicant has paid social security in full for more than two years in the area where he is located, that the provident fund loan applicant has paid provident fund in full for more than one year in the area where he is located, the down payment ratio for the second set of housing must not be less than 50%, and the purchase area must not exceed the upper limit of the purchase area specified in the area.

[0046] Furthermore, when the triggered rules are that the provident fund individual loan rate is too low, liquidity is excessive, and the net flow of business funds is enlarged:

[0047] Modify the provident fund loan multiple: adjust the current B1 times to B2 times, B1 is less than B2; add the provident fund loan multiple B2 defined on the measure rule definition page to the request message, call the provident fund loan multiple modification interface, and modify the provident fund loan multiple;

[0048] Carry out "commercial to public" loan business: the system automatically calls the "commercial to public" loan business interface and opens the "commercial to public" application interface;

[0049] Suspend the "public-to-private" loan business: call the "public-to-private" loan business modification interface and close the "public-to-private" application interface;

[0050] Reduce the restrictions on provident fund loan applications; add the application restrictions defined on the measure rule definition page to the request message, and call the provident fund loan application restriction modification interface; the application restrictions include reducing the restrictions on provident fund loan applications, including that the provident fund loan applicant has paid social security in full for more than half a year in the area where he is located, that the provident fund loan applicant has paid provident fund in full for more than half a year in the area where he is located, the down payment ratio for the second house shall not be less than 30%, and the purchase area shall not exceed the upper or lower limit of the purchase area specified in the area.

[0051] Furthermore, the method of automatically generating a policy change notification on the provident fund center official website includes:

[0052] Step 1: Get the action rules defined on the action rule definition page;

[0053] Step 2: Replace the measure rules in the policy change notification template with the measure rules defined this time, and replace the effective date in the policy change notification template with the effective date of the measure rules defined this time, to obtain a policy change notification;

[0054] Step 3: Add the policy change notification to the request message, call the policy change notification publishing interface, and publish the policy change notification.

[0055] A custom rule risk indicator early warning system based on data mining, implementing the custom rule risk indicator early warning method based on data mining, including:

[0056] A monitoring rule definition module is used to customize the monitoring data level on the monitoring rule definition page according to the business needs and policy requirements of the current region. The customized monitoring data level includes the provident fund individual loan rate level, the liquidity guarantee multiple level and the business fund net flow level;

[0057] The first data collection module is used to collect key data of the provident fund center, the key data including the provident fund loan balance, the provident fund deposit balance, the non-business fund expenditure of the month, the provident fund withdrawal amount of the month, the provident fund deposit amount of the month, the provident fund loan amount of the month and the principal and interest of the provident fund loan recovered in the month;

[0058] The first data processing module is used to process key data to obtain the monthly housing provident fund individual loan rate, the monthly business fund net flow and the monthly liquidity guarantee multiple;

[0059] The rule engine warning module is used to determine whether to trigger the preset rule engine according to the provident fund individual loan rate, the net flow of business funds and the liquidity guarantee multiple of the month; if the rule engine is triggered, the warning information is automatically generated and reported; the warning information includes the rules of the rule engine and the warning level; the warning level includes the first-level warning, the second-level warning and the third-level warning;

[0060] The action rule definition module customizes action rules on the action rule definition page according to the business needs and policy requirements of the current region when generating warning information;

[0061] The publishing module is used to automatically generate policy change notifications on the provident fund center's official website based on the measures and rules defined on the measures and rules definition page.

[0062] The technical effects and advantages of the risk indicator early warning method and system based on customized rules of data mining of the present invention are as follows:

[0063] Managers can flexibly customize monitoring rules based on business needs and policy changes, so that managers can quickly adapt to policy changes and adjust monitoring strategies in a timely manner; the Provident Fund Center scientifically, accurately and proactively regulates the income and expenditure of funds to avoid situations where business funds cannot meet business needs such as housing provident fund withdrawals and loans when there is insufficient inflow of business funds, or when there are sufficient funds, the funds cannot be fully utilized, resulting in idle funds and low returns.

[0064] The system can also generate early warnings in a timely manner based on user-defined rules, and automatically make decisions and execute them based on user-defined action rules, thereby reducing manual intervention and improving efficiency and accuracy. The system automatically generates policy change notifications on the Provident Fund Center's official website to ensure that all relevant parties (including Provident Fund contributors, loan applicants and other stakeholders) are able to keep abreast of the latest policies and changes; this improves information transparency, ensures the safety and efficient use of Provident Funds, reduces the lag in information transmission, and enhances users' trust and satisfaction with Provident Fund management. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1This is a schematic diagram of a risk indicator early warning system based on customized rules of data mining according to Embodiment 1 of the present invention;

[0066] Figure 2 It is a flow chart of the method for generating early warning information of the present invention;

[0067] Figure 3 It is a flow chart of the risk indicator early warning method based on customized rules of data mining of the present invention;

[0068] Figure 4 is a schematic diagram of an electronic device of the present invention;

[0069] Figure 5 Schematic diagram of the storage medium of the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] Example 1

[0072] See also Figure 1 As shown, the custom rule risk indicator warning system based on data mining described in this embodiment includes a monitoring rule definition module, a first data acquisition module, a first data processing module, a rule engine warning module, a measure rule definition module and a publishing module. The above modules are electrically connected to realize data transmission between modules.

[0073] The monitoring rule definition module customizes the monitoring data level on the monitoring rule definition page according to the business needs and policy requirements of the current region. The customized monitoring data level includes the provident fund individual loan rate level, the liquidity guarantee multiple level and the business capital net flow level.

[0074] The definition method of provident fund individual loan rate level is:

[0075] Customize four individual housing fund loan rates of α1, α2, α3 and α4 on the monitoring rule definition page, and divide the individual housing fund loan rate into five levels; the individual housing fund loan rate levels include individual housing fund loan rate too low, individual housing fund loan rate is low, individual housing fund loan rate is normal, individual housing fund loan rate is high and individual housing fund loan rate is too high;

[0076] It should be noted that α1<α2<α3<α4; if the Provident Fund individual loan rate is less than α1, the corresponding Provident Fund individual loan rate is too low; if the Provident Fund individual loan rate is greater than or equal to α1 and less than or equal to α2, the corresponding Provident Fund individual loan rate is low; if the Provident Fund individual loan rate is greater than α2 and less than α3, the corresponding Provident Fund individual loan rate is normal; if the Provident Fund individual loan rate is greater than or equal to α3 and less than or equal to α4, the corresponding Provident Fund individual loan rate is high; if the Provident Fund individual loan rate is greater than α4, the corresponding Provident Fund individual loan rate is too high;

[0077] The Provident Fund Individual Loan Rate is an important indicator to measure the Provident Fund's ability to support loans. A too low Provident Fund Individual Loan Rate indicates that Provident Fund loans are not fully utilized, and there is a large amount of Provident Fund funds deposited in the account that have not been effectively utilized; a normal Provident Fund Individual Loan Rate indicates that housing Provident Fund loans are fully utilized and the Provident Fund's ability to support loans is excellent; an excessively high Provident Fund Individual Loan Rate may bring liquidity risks.

[0078] The definition method of liquidity protection multiple levels is as follows:

[0079] On the monitoring rule definition page, you can customize three liquidity protection multiples, β1, β2 and β3, and divide the liquidity protection multiples into four levels; the liquidity protection multiples levels include insufficient liquidity, tight liquidity, normal liquidity and excess liquidity.

[0080] It should be noted that β1<β2<β3; if the liquidity protection ratio is less than β1, it corresponds to insufficient liquidity; if the liquidity protection ratio is greater than or equal to β1 and less than or equal to β2, it corresponds to tight liquidity; if the provident fund individual loan rate is greater than β2 and less than β3, it corresponds to normal liquidity; if the liquidity protection ratio is greater than or equal to β3, it corresponds to excess liquidity.

[0081] Insufficient liquidity indicates that there is liquidity risk, and the Provident Fund Center needs to significantly reduce the issuance of Provident Fund loans; tight liquidity indicates that the Provident Fund Center needs to appropriately increase the restrictions on Provident Fund loan applications; normal liquidity indicates that the Provident Fund Center's business is operating stably; excess liquidity indicates that housing Provident Fund loans are not fully utilized, and the Provident Fund Center can relax the restrictions on Provident Fund loan applications.

[0082] The definition method of business capital net flow level is:

[0083] On the monitoring rule definition page, customize the two business net capital flows γ1 and γ2, and divide the business net capital flow into three levels; the business net capital flow levels include business net capital flow reduction, business net capital flow balance and business net capital flow amplification.

[0084] It should be noted that γ1<γ2; if the net business capital flow is less than γ1, the corresponding net business capital flow will be reduced; if the net business capital flow is greater than or equal to γ1 and less than or equal to γ2, the corresponding net business capital flow will be balanced; if the net business capital flow is greater than γ2, the corresponding net business capital flow will be enlarged.

[0085] The net business fund flow reflects the business fund status of the provident fund center; a net business fund flow greater than 0 indicates that the net business fund flow is positive, otherwise it is negative; a decrease in the net business fund flow indicates that the provident fund business expenditure has increased significantly, far higher than the provident fund business income, and it is necessary to be vigilant against the risk of excessive expenditure; a balanced net business fund flow indicates that the business funds of the provident fund center are stable; an increase in the net business fund flow indicates that the provident fund business income has increased significantly, far higher than the provident fund business expenditure, and it is necessary to warn of the risk of excess funds.

[0086] The first data collection module is used to collect key data of the provident fund center, which includes the provident fund loan balance, provident fund payment balance, non-business fund expenditure of the month, provident fund withdrawal amount of the month, provident fund payment amount of the month, provident fund loan amount of the month and principal and interest of provident fund loan recovered in the month; the key data is obtained from the backend database of the provident fund center.

[0087] The first data processing module is used to process key data to obtain the provident fund individual loan rate, the net flow of business funds and the liquidity guarantee multiple of the month.

[0088] The calculation formula of provident fund individual loan rate is:

[0089]

[0090] It should be noted that the Provident Fund loan balance refers to the total amount of all Provident Fund loans that have been issued but not yet repaid; the Provident Fund deposit balance refers to the total balance of all Provident Fund accounts, that is, all Provident Fund deposits held by the Provident Fund Center.

[0091] The calculation formula for net operating funds flow is:

[0092] Net business capital flow = (the amount of provident fund deposits in the current month + the principal and interest of provident fund loans collected in the current month) -

[0093] (Amount of provident fund withdrawal in that month + amount of provident fund loan in that month).

[0094] The calculation formula for liquidity protection ratio is:

[0095]

[0096] The rule engine warning module is used to determine whether to trigger the preset rule engine based on the provident fund individual loan rate, the net business fund flow and the liquidity guarantee multiple of the month; if the rule engine is triggered, the warning information is automatically generated and reported; the warning information includes the rules of the rule engine and the warning level; the warning level includes level one warning, level two warning and level three warning.

[0097] Please refer to Figure 2 As shown, the method for generating the warning information includes:

[0098] Step 1: Match the individual housing fund loan rate of the current month with the individual housing fund loan rate level in the custom monitoring data level to obtain the individual housing fund loan rate level of the current month; match the net business fund flow of the current month with the net business fund flow level in the custom monitoring data level to obtain the net business fund flow level of the current month; match the liquidity guarantee multiple of the current month with the liquidity guarantee multiple level in the custom monitoring data level to obtain the liquidity guarantee multiple level of the current month;

[0099] Step 2: Generate warning levels based on the rules of the rule engine;

[0100] The method for generating the warning level is:

[0101] When the provident fund individual loan rate is too high, liquidity is insufficient or tight, and the net flow of business funds decreases, the rule engine is triggered, and the warning level is level three;

[0102] When the individual housing provident fund loan rate is too low, liquidity is excessive, and the net flow of business funds is enlarged, the rule engine is triggered, and the warning level is level three;

[0103] When the provident fund individual loan rate is high, liquidity is normal or excess liquidity and the net flow of business funds is enlarged, the rule engine is triggered and the warning level is level 2 warning;

[0104] When the individual housing provident fund loan rate is low, liquidity is tight, and the net flow of business funds decreases, the rule engine is triggered and the warning level is level 2.

[0105] When the individual housing provident fund loan rate is low, liquidity is normal, and the net flow of business funds is balanced, the rule engine is triggered and the warning level is level one;

[0106] When the provident fund individual loan rate is high, liquidity is normal and the net flow of business funds is balanced, the rule engine is triggered and the warning level is level one.

[0107] Step 3: Match the provident fund individual loan rate level, the net business fund flow level and the liquidity guarantee multiple level of the current month with the rules of the rule engine. If the match is successful, the rule engine is triggered and step 4 is executed; if the match is unsuccessful, the rule engine is not triggered and the process ends.

[0108] Step 4: Generate warning information and report the warning information.

[0109] The measure rule definition module customizes the measure rules on the measure rule definition page according to the business needs and policy requirements of the current area when generating warning information.

[0110] Methods for defining action rules include:

[0111] When the triggered rule is that the provident fund individual loan rate is too high, liquidity is insufficient or liquidity is tight, and the net flow of business funds is reduced:

[0112] Modify the provident fund loan multiple: adjust the current A1 times to A2 times, where A1 is greater than A2; add the provident fund loan multiple A2 defined on the measure rule definition page to the request message, and the system automatically calls the provident fund loan multiple modification interface to modify the provident fund loan multiple.

[0113] Suspend the "commercial to public" loan business: the system automatically calls the "commercial to public" loan business interface and closes the "commercial to public" application interface. When the "commercial to public" application interface is closed, the "commercial to public" loan business cannot be processed;

[0114] Carry out "public-to-private" loan business: the system automatically calls the "public-to-private" loan business modification interface and opens the "public-to-private" application interface. When the "public-to-private" application interface is opened, the "public-to-private" loan business is processed.

[0115] Add restrictions on provident fund loan applications: Add the application restrictions defined on the measure rule definition page to the request message. The system automatically calls the provident fund loan application restriction modification interface to add restrictions on provident fund loan applications. The application restrictions include that the provident fund loan applicant has paid social security in full for more than two years in the area where he is located, that the provident fund loan applicant has paid provident fund in full for more than one year in the area where he is located, the down payment ratio for the second set of housing must not be less than 50%, and the purchase area must not exceed the upper limit of the purchase area specified in the area.

[0116] When the triggered rules are that the provident fund individual loan rate is too low, liquidity is excessive, and the net flow of business funds is enlarged:

[0117] Modify the provident fund loan multiple: adjust the current B1 times to B2 times, B1 is less than B2; add the provident fund loan multiple B2 defined on the measure rule definition page to the request message, and the system automatically calls the provident fund loan multiple modification interface to modify the provident fund loan multiple;

[0118] Carry out "commercial to public" loan business: the system automatically calls the "commercial to public" loan business interface and opens the "commercial to public" application interface. When the "commercial to public" application interface is opened, the "commercial to public" loan business is processed;

[0119] Suspend the "public-to-private" loan business: This system automatically calls the "public-to-private" loan business modification interface and closes the "public-to-private" application interface. When the "public-to-private" application interface is closed, the "public-to-private" loan business cannot be processed.

[0120] Reduce the restrictions on provident fund loan applications; add the application restrictions defined on the measure rule definition page to the request message, and the system automatically calls the provident fund loan application restriction modification interface to reduce the provident fund loan application restrictions; the application restrictions include reducing the provident fund loan application restrictions, including that the provident fund loan applicant has paid social security in full in the area for more than half a year, that the provident fund loan applicant has paid provident fund in full in the area for more than half a year, the down payment ratio for the second house shall not be less than 30%, and the purchase area shall not exceed the upper or lower limit of the purchase area specified in the area.

[0121] The publishing module is used to automatically generate policy change notifications on the Provident Fund Center's official website based on the measure rules defined on the measure rule definition page.

[0122] The methods for automatically generating policy change notifications on the Provident Fund Center official website include:

[0123] Step 1: Get the action rules defined on the action rule definition page;

[0124] Step 2: Replace the measure rules in the policy change notification template with the measure rules defined this time, and replace the effective date in the policy change notification template with the effective date of the measure rules defined this time, to obtain a policy change notification;

[0125] Step 3: Add the policy change notification to the request message, and the system calls the policy change notification publishing interface to publish the policy change notification.

[0126] Managers can flexibly customize monitoring rules based on business needs and policy changes, so that managers can quickly adapt to policy changes and adjust monitoring strategies in a timely manner; the Provident Fund Center scientifically, accurately and proactively regulates the income and expenditure of funds to avoid situations where business funds cannot meet business needs such as housing provident fund withdrawals and loans when there is insufficient inflow of business funds, or when there are sufficient funds, the funds cannot be fully utilized, resulting in idle funds and low returns.

[0127] The system can also generate early warnings in a timely manner based on user-defined rules, and automatically make decisions and execute them based on user-defined action rules, thereby reducing manual intervention and improving efficiency and accuracy. The system automatically generates policy change notifications on the Provident Fund Center's official website to ensure that all relevant parties (including Provident Fund contributors, loan applicants and other stakeholders) are able to keep abreast of the latest policies and changes; this improves information transparency, ensures the safety and efficient use of Provident Funds, reduces the lag in information transmission, and enhances users' trust and satisfaction with Provident Fund management.

[0128] Example 2

[0129] See also Figure 3 As shown, this embodiment provides a custom rule risk indicator early warning method based on data mining, including:

[0130] Customize the monitoring data level on the monitoring rule definition page according to the business needs and policy requirements of the current region. The customized monitoring data level includes the provident fund individual loan rate level, the liquidity guarantee multiple level and the business fund net flow level;

[0131] Collect key data from the Provident Fund Center, including the Provident Fund loan balance, Provident Fund deposit balance, non-business fund expenditures for the month, Provident Fund withdrawal amount for the month, Provident Fund deposit amount for the month, Provident Fund loan amount for the month, and Provident Fund loan principal and interest collected for the month;

[0132] Process key data to obtain the individual housing provident fund loan rate, net business fund flow and liquidity guarantee multiple for the month;

[0133] According to the individual housing provident fund loan rate, the net business fund flow and the liquidity guarantee multiple of the month, it is judged whether to trigger the preset rule engine; if the rule engine is triggered, an early warning message is automatically generated and reported; the early warning message includes the rules of the rule engine and the early warning level; the early warning level includes the first-level early warning, the second-level early warning and the third-level early warning;

[0134] When generating warning information, customize the action rules on the action rule definition page according to the business needs and policy requirements of the current region;

[0135] The measure rules defined on the measure rule definition page will automatically generate policy change notifications on the provident fund center's official website.

[0136] Example 3

[0137] See also Figure 4As shown, according to another aspect of the present application, an electronic device 500 is also provided. The electronic device 500 may include one or more processors and one or more memories. The memories store computer readable codes, and when the computer readable codes are executed by one or more processors, the custom rule risk indicator early warning method based on data mining as described above may be executed.

[0138] The method or system according to the embodiment of the present application can also be used by Figure 4 The electronic device architecture shown in FIG. Figure 4 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, ROM 503, RAM 504, a communication port 505 connected to a network, an input / output 506, a hard disk 507, etc. The storage device in the electronic device 500, such as ROM 503 or hard disk 507, may store the customized rule risk indicator early warning method based on data mining provided by the present application. Furthermore, the electronic device 500 may also include a user interface 508. Of course, Figure 4 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 4 One or more components of an electronic device are shown.

[0139] Example 4

[0140] See also Figure 5 As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, the customized rule-based risk indicator early warning method based on data mining according to the embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0141] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0142] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A risk indicator early warning method based on customized rules of data mining, characterized in that: include: Customize the monitoring data level on the monitoring rule definition page according to the business needs and policy requirements of the current region. The customized monitoring data level includes the provident fund individual loan rate level, the liquidity guarantee multiple level and the business fund net flow level; Collect key data from the Provident Fund Center, including the Provident Fund loan balance, Provident Fund deposit balance, non-business fund expenditures for the month, Provident Fund withdrawal amount for the month, Provident Fund deposit amount for the month, Provident Fund loan amount for the month, and Provident Fund loan principal and interest collected for the month; Process key data to obtain the individual housing provident fund loan rate, net business fund flow and liquidity guarantee multiple for the month; Determine whether to trigger the pre-set rule engine based on the monthly provident fund individual loan rate, the monthly business fund net flow and the monthly liquidity guarantee multiple; If the rule engine is triggered, warning information is automatically generated and reported; the warning information includes the rules of the rule engine and the warning level; The warning levels include level one warning, level two warning and level three warning; When generating warning information, customize the action rules on the action rule definition page according to the business needs and policy requirements of the current region; The measure rules defined on the measure rule definition page will automatically generate policy change notifications on the provident fund center's official website.

2. The risk indicator early warning method based on customized rules of data mining according to claim 1 is characterized in that: The definition method of the provident fund individual loan rate level is as follows: Customize four individual housing fund loan rates of α1, α2, α3 and α4 on the monitoring rule definition page, α1<α2<α3<α4; if the individual housing fund loan rate is less than α1, the corresponding individual housing fund loan rate is too low; if the individual housing fund loan rate is greater than or equal to α1 and less than or equal to α2, the corresponding individual housing fund loan rate is low; if the individual housing fund loan rate is greater than α2 and less than α3, the corresponding individual housing fund loan rate is normal; If the Provident Fund individual loan rate is greater than or equal to α3 and less than or equal to α4, the corresponding Provident Fund individual loan rate is relatively high; if the Provident Fund individual loan rate is greater than α4, the corresponding Provident Fund individual loan rate is too high.

3. The risk indicator early warning method based on customized rules of data mining according to claim 2 is characterized in that: The definition method of liquidity protection multiple levels is as follows: On the monitoring rule definition page, you can customize three liquidity protection multiples, β1, β2 and β3, where β1<β2<β3; if the liquidity protection multiple is less than β1, it corresponds to insufficient liquidity; if the liquidity protection multiple is greater than or equal to β1 and less than or equal to β2, it corresponds to tight liquidity; if the provident fund individual loan rate is greater than β2 and less than β3, it corresponds to normal liquidity; if the liquidity protection multiple is greater than or equal to β3, it corresponds to excess liquidity.

4. The risk indicator early warning method based on customized rules of data mining according to claim 3 is characterized in that: The definition method of the business capital net flow level is as follows: On the monitoring rule definition page, customize the two business net capital flows γ1 and γ2, γ1<γ2; if the business net capital flow is less than γ1, the corresponding business net capital flow will be reduced; if the business net capital flow is greater than or equal to γ1 and less than or equal to γ2, the corresponding business net capital flow will be balanced; if the business net capital flow is greater than γ2, the corresponding business net capital flow will be enlarged.

5. The risk indicator early warning method based on customized rules of data mining according to claim 4 is characterized in that: The calculation formula of the provident fund individual loan rate is: The provident fund loan balance refers to the total amount of all provident fund loans that have been issued but not yet repaid; the provident fund deposit balance refers to the total balance of all provident fund accounts, that is, all provident fund deposits held by the provident fund center; The calculation formula for the net flow of business funds is: Net business capital flow = (amount of provident fund deposits in the current month + principal and interest collected from provident fund loans in the current month) - (amount of provident fund withdrawals in the current month + amount of provident fund loans in the current month); The calculation formula of the liquidity protection multiple is:

6. The risk indicator early warning method based on customized rules of data mining according to claim 5 is characterized in that: The method for generating the early warning information comprises: Step 1: Match the individual housing fund loan rate of the current month with the individual housing fund loan rate level in the custom monitoring data level to obtain the individual housing fund loan rate level of the current month; match the net business fund flow of the current month with the net business fund flow level in the custom monitoring data level to obtain the net business fund flow level of the current month; match the liquidity guarantee multiple of the current month with the liquidity guarantee multiple level in the custom monitoring data level to obtain the liquidity guarantee multiple level of the current month; Step 2: Generate warning levels based on the rules of the rule engine; The method for generating the warning level is: When the provident fund individual loan rate is too high, liquidity is insufficient or tight, and the net flow of business funds decreases, the rule engine is triggered, and the warning level is level three; When the individual housing provident fund loan rate is too low, liquidity is excessive, and the net flow of business funds is enlarged, the rule engine is triggered, and the warning level is level three; When the individual housing fund loan rate is high, liquidity is normal or excess, and the net flow of business funds is enlarged, the rule engine is triggered and the warning level is level 2. When the individual housing provident fund loan rate is low, liquidity is tight, and the net flow of business funds decreases, the rule engine is triggered and the warning level is level 2. When the individual housing provident fund loan rate is low, liquidity is normal, and the net flow of business funds is balanced, the rule engine is triggered and the warning level is level one; When the individual housing provident fund loan rate is high, liquidity is normal, and the net flow of business funds is balanced, the rule engine is triggered and the warning level is level one; Step 3: Match the provident fund individual loan rate level, the business fund net flow level and the liquidity guarantee multiple level of the current month with the rules of the rule engine. If the match is successful, the rule engine is triggered and step 4 is executed; if the match is unsuccessful, the rule engine is not triggered and the process ends; Step 4: Generate warning information and report the warning information.

7. The risk indicator early warning method based on customized rules of data mining according to claim 6 is characterized in that: The method for customizing the action rule includes: When the triggered rule is that the provident fund individual loan rate is too high, liquidity is insufficient or liquidity is tight, and the net flow of business funds is reduced: Modify the provident fund loan multiple: adjust the current A1 times to A2 times, where A1 is greater than A2; add the provident fund loan multiple A2 defined on the measure rule definition page to the request message, call the provident fund loan multiple modification interface, and modify the provident fund loan multiple; Suspend the "commercial to public" loan business: the system automatically calls the "commercial to public" loan business interface and closes the "commercial to public" application interface; Carry out the "public-to-private" loan business: call the "public-to-private" loan business modification interface and open the "public-to-private" application interface; Add restrictions on provident fund loan applications: add the application restrictions defined on the measure rule definition page to the request message, and call the provident fund loan application restriction modification interface; the application restrictions include that the provident fund loan applicant has paid social security in full for more than two years in the area where he is located, that the provident fund loan applicant has paid provident fund in full for more than one year in the area where he is located, the down payment ratio for the second set of housing must not be less than 50%, and the purchase area must not exceed the upper limit of the purchase area specified in the area.

8. The risk indicator early warning method based on customized rules of data mining according to claim 6 is characterized in that: When the triggered rules are that the provident fund individual loan rate is too low, liquidity is excessive, and the net flow of business funds is enlarged: Modify the provident fund loan multiple: adjust the current B1 times to B2 times, B1 is less than B2; add the provident fund loan multiple B2 defined on the measure rule definition page to the request message, call the provident fund loan multiple modification interface, and modify the provident fund loan multiple; Carry out "commercial to public" loan business: the system automatically calls the "commercial to public" loan business interface and opens the "commercial to public" application interface; Suspend the "public-to-private" loan business: call the "public-to-private" loan business modification interface and close the "public-to-private" application interface; Reduce the restrictions on provident fund loan applications; add the application restrictions defined on the measure rule definition page to the request message, and call the provident fund loan application restriction modification interface; the application restrictions include reducing the restrictions on provident fund loan applications, including that the provident fund loan applicant has paid social security in full for more than half a year in the area where he is located, that the provident fund loan applicant has paid provident fund in full for more than half a year in the area where he is located, the down payment ratio for the second house shall not be less than 30%, and the purchase area shall not exceed the upper or lower limit of the purchase area specified in the area.

9. The risk indicator early warning method based on customized rules of data mining according to claim 6 is characterized in that: The methods for automatically generating policy change notifications on the Provident Fund Center official website include: Step 1: Get the action rules defined on the action rule definition page; Step 2: Replace the measure rules in the policy change notification template with the measure rules defined this time, and replace the effective date in the policy change notification template with the effective date of the measure rules defined this time, to obtain a policy change notification; Step 3: Add the policy change notification to the request message, call the policy change notification publishing interface, and publish the policy change notification.

10. A risk indicator early warning system based on customized rules based on data mining, implementing the risk indicator early warning method based on customized rules based on data mining as claimed in any one of claims 1 to 9, characterized in that: include: A monitoring rule definition module is used to customize the monitoring data level on the monitoring rule definition page according to the business needs and policy requirements of the current region. The customized monitoring data level includes the provident fund individual loan rate level, the liquidity guarantee multiple level and the business fund net flow level; The first data collection module is used to collect key data of the provident fund center, the key data including the provident fund loan balance, the provident fund deposit balance, the non-business fund expenditure of the month, the provident fund withdrawal amount of the month, the provident fund deposit amount of the month, the provident fund loan amount of the month and the principal and interest of the provident fund loan recovered in the month; The first data processing module is used to process key data to obtain the monthly housing provident fund individual loan rate, the monthly business fund net flow and the monthly liquidity guarantee multiple; The rule engine warning module is used to determine whether to trigger the preset rule engine based on the monthly provident fund individual loan rate, the monthly business fund net flow and the monthly liquidity guarantee multiple; If the rule engine is triggered, warning information is automatically generated and reported; the warning information includes the rules of the rule engine and the warning level; The warning levels include level one warning, level two warning and level three warning; The action rule definition module customizes action rules on the action rule definition page according to the business needs and policy requirements of the current region when generating warning information; The publishing module is used to automatically generate policy change notifications on the provident fund center's official website based on the measures and rules defined on the measures and rules definition page.

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