Method, device, electronic device and storage medium for determining bank liquidity index

Abstract

The embodiment of the present invention discloses a method, device, electronic device and storage medium for determining bank liquidity indicators. The method for determining bank liquidity indicators includes: obtaining adjustment configuration parameters set by a user, determining parameter interface data according to the adjustment configuration parameters; obtaining capital data from an external component, determining cash flow detail data according to the parameter interface data and the capital data; and determining the liquidity indicator result according to the cash flow detail data and the parameter interface data. By participating in the determination process of the liquidity indicator result according to the adjustment configuration parameters set by the user, the data collection caliber of the products participating in the calculation of the liquidity indicator is updated in a timely manner to improve the timeliness of the determination of the bank's liquidity indicators; and the calculation of the liquidity indicator can be customized according to the needs of different bank users, which is convenient for bank users to scientifically plan the asset structure, save time and cost for risk analysis, and improve efficiency.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of banking and financial technology, and in particular to a method, device, electronic device and storage medium for determining a bank liquidity indicator. Background Art

[0002] Commercial banks' static methods for measuring liquidity risk are collectively referred to as liquidity indicators. Liquidity indicators simply and clearly reflect a bank's liquidity level at a given point in time. Existing liquidity indicator calculation methods are complex, and with increasingly stringent regulatory requirements, the types of high-quality liquid assets and cash flows included in liquidity indicators are constantly changing. Changing business needs also require modifications to the indicator processing and storage process. Given the large number of overseas branches of large commercial banks and the individual differences in regulatory requirements across different countries and regions, developing multiple liquidity indicator calculation programs to meet the needs of each overseas branch is necessary. This not only consumes significant database cluster storage space but also increases the difficulty of subsequent system operations and maintenance.

[0003] Furthermore, because bank users currently cannot modify the liquidity indicator calculation program at any time, the cash flow details involved in the liquidity indicator calculation cannot be updated in a timely manner to meet regulatory requirements, resulting in delayed effectiveness of liquidity indicator reports for bank users. If liquidity indicators fail to meet compliance limits due to poor timeliness and untimely cash flow updates, bank users may even face the risk of penalties from local regulators. Therefore, the current liquidity indicator calculation system suffers from issues such as delayed product data retrieval and the use of a single stored procedure that cannot be customized to meet the needs of different bank users. Summary of the Invention

[0004] Embodiments of the present invention provide a method, device, electronic device, and storage medium for determining a bank liquidity indicator, which improve the timeliness of determining a bank liquidity indicator by participating in the determination process of a liquidity indicator result according to adjustment configuration parameters set by the user.

[0005] In a first aspect, an embodiment of the present invention provides a method for determining a bank liquidity indicator, comprising:

[0006] Acquire adjustment configuration parameters set by the user, and determine parameter interface data according to the adjustment configuration parameters;

[0007] Obtaining fund data from an external component, and determining cash flow detail data based on the parameter interface data and the fund data;

[0008] A liquidity indicator result is determined based on the cash flow detail data and the parameter interface data.

[0009] In a second aspect, an embodiment of the present invention further provides a device for determining a bank liquidity indicator, comprising:

[0010] A parameter data determination module is used to obtain adjustment configuration parameters set by the user and determine parameter interface data according to the adjustment configuration parameters;

[0011] A cash flow detail determination module, configured to obtain fund data from an external component and determine cash flow detail data based on the parameter interface data and the fund data;

[0012] The liquidity indicator determination module is used to determine the liquidity indicator result according to the cash flow detail data and the parameter interface data.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device, including:

[0014] one or more processors;

[0015] a storage device for storing one or more programs,

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the bank liquidity indicator determination method as described in any embodiment of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for determining bank liquidity indicators as described in any embodiment of the present invention.

[0018] The embodiments of the present invention are based on obtaining user-set adjustment configuration parameters, determining parameter interface data based on the adjustment configuration parameters; obtaining capital data from an external component, determining cash flow detail data based on the parameter interface data and the capital data; and determining liquidity indicator results based on the cash flow detail data and the parameter interface data. By participating in the process of determining liquidity indicator results based on the user-set adjustment configuration parameters, the data collection criteria for products involved in liquidity indicator calculations are updated in a timely manner, thereby improving the timeliness of bank liquidity indicator determination. Furthermore, the calculation of liquidity indicators can be customized based on the needs of different bank users, facilitating scientific asset structure planning for bank users, saving time and costs for risk analysis, and improving efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flow chart of the method for determining bank liquidity indicators in the first embodiment of the present invention;

[0020] Figure 2 This is a schematic diagram of the structure of the bank liquidity indicator determination system in the second embodiment of the present invention;

[0021] Figure 3 This is a schematic diagram of the structure of a data acquisition module in the bank liquidity indicator determination system in the second embodiment of the present invention;

[0022] Figure 4 This is a schematic diagram of the structure of a parameter configuration module in the bank liquidity indicator determination system in the second embodiment of the present invention;

[0023] Figure 5 This is a schematic diagram of the structure of the indicator processing module in the bank liquidity indicator determination system in the second embodiment of the present invention;

[0024] Figure 6 This is a schematic diagram of the structure of a user interaction module in the bank liquidity indicator determination system in the second embodiment of the present invention;

[0025] Figure 7 This is a schematic diagram of the structure of the device for determining bank liquidity indicators in the third embodiment of the present invention;

[0026] Figure 8 It is a structural diagram of an electronic device in the fourth embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be further described in detail below with reference to the accompanying drawings and examples. It will be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the present invention, not all structures.

[0028] Example 1

[0029] Figure 1 This is a flow chart of the method for determining bank liquidity indicators in the first embodiment of the present invention. This embodiment is applicable to the case where bank liquidity indicators are determined based on data collection criteria that are adjusted in real time. The method can be executed by a bank liquidity indicator determination device, which can be implemented in software and / or hardware and can be configured in an electronic device, such as a background server or other device with communication and computing capabilities. Figure 1 As shown, the method specifically includes:

[0030] Step 101: Acquire adjustment configuration parameters set by the user, and determine parameter interface data according to the adjustment configuration parameters.

[0031] In the "Measures for the Management of Liquidity Risk of Commercial Banks (Trial Implementation)" issued by the China Banking Regulatory Commission, liquidity risk is defined as the risk that a commercial bank will be unable to obtain sufficient funds in a timely manner at a reasonable cost to repay maturing debts, fulfill other payment obligations, and meet other funding needs for normal business operations. Commercial banks use static methods for measuring liquidity risk, generally referred to as liquidity indicators, to simply and clearly reflect a bank's liquidity level at a given point in time.

[0032] The calculation process of liquidity indicators requires determining the data collection caliber. This caliber is used to complete the data collection work from the bank component and determine the calculation parameters of the liquidity indicator. Due to changes in regulatory requirements or the different regions where banks are located, the data collection caliber may change. For example, for the cash flow generated by the same type of product, banks in region A can include it in high-quality liquid assets, but banks in region B cannot include it in high-quality liquid assets; or due to changes in regulatory requirements, the cash flow generated by the same type of product cannot be included in high-quality liquid assets after the regulatory requirements change, or the weight of high-quality liquid assets changes, etc. These changes will cause the data collection caliber to change accordingly. Otherwise, the asset data determined from the bank component will be inaccurately located, resulting in errors or delays in the calculation of liquidity indicators. Among them, adjusting the configuration parameters is used to determine the data collection caliber, that is, to determine the range of asset data that can be included in the calculation of liquidity indicators.

[0033] In a feasible embodiment, the configuration parameters are adjusted so that users can set them according to changes in regulatory policies. Specifically, when regulatory policies change, users can make corresponding adjustments to the configuration parameters in the front-end interface of the bank liquidity indicator determination system. For example, the cash flow types involved in the calculation or the weights of the types of related cash flow types involved in the calculation are adjusted according to the changes in the regulatory policies, so that when the regulatory policies are issued and changed at any point in time, bank users can adjust the configuration parameters by themselves, and realize the flexible adjustment of the cash flow product range and data acquisition caliber for calculating liquidity indicators. In addition, there is no need to suspend the system to provide external services during the adjustment process, so that the generated liquidity indicators are updated in real time as regulatory requirements change, so as to report the liquidity status to local regulators in a timely manner. In addition, the same set of liquidity indicators can be used to determine the storage method for different regions, and bank users in different regions only need to configure their own parameters according to their local regulatory actual requirements.

[0034] Specifically, obtain the adjustment configuration parameters set by the user, and adjust the configuration parameters according to the

[0035] Banking personnel can independently select the type of cash flow data to be displayed in the liquidity indicator report on the system front page. By adding, deleting, modifying and querying product parameters, they can determine the parameter interface data, that is, update the scope of funds data involved in the liquidity indicator calculation in real time.

[0036] In a feasible embodiment, adjusting the configuration parameters includes the cash flow types and type weights involved in the calculation; wherein, the cash flow types involved in the calculation are determined by common dimensions; the common dimensions include at least one of the following: unique number, multi-entity identifier, major category code, major category name, subcategory code, subcategory name, caller component number, product number, account number, interbank lending code, customer type, customer code, removal type, removal code, forecast days, cycle flag, event type, whether to limit pre-interest, interest and event amount type, amount symbol, term type, investment type, credit type, regional category identifier, currency and bond rating.

[0037] Banks offer a wide variety of products, and due to varying regulatory policies, the types of cash flows used to calculate liquidity indicators, as well as their weightings, often vary from location to location. Users can add, delete, modify, and query parameters on the front-end page to determine and adjust configuration parameters, describing the nature of the product and accurately locating each cash flow transaction. The common dimensions of the parameter configuration model for liquidity indicators include: unique number, multi-entity identifier, major category code, major category name, subcategory code, subcategory name, caller component number, product number, account number, interbank lending code, customer type, customer code, removal type, removal code, forecast days, recurrence flag, event type, whether to restrict pre-interest, interest and event amount type, amount symbol, term type, investment type, credit type, regional category identifier, currency, and bond rating.

[0038] Among them: The unique number as the primary key can uniquely locate and distinguish a parameter configuration record. The multi-entity identifier is used to distinguish the overseas branch to which the parameter belongs. The major category code and major category name are used to summarize and display the major product categories. Different major categories have different type weights when calculating liquidity indicators, and therefore have different degrees of impact on the indicator values. The subcategory code and subcategory name make a more fine-grained distinction at the product level. The caller component number is used to identify the data source system of the upstream cash flow. Other attributes characterize the product characteristics from different angles, thereby capturing the capital data that meets user needs into the cash flow details interface.

[0039] In one possible embodiment, the removal type and removal code are used to define the filtered cash flow type.

[0040] The two fields, Removal Type and Removal Code, are used to filter when the cash flow generated by a certain product business should not be included in the indicator calculation due to its special nature. The removal attributes of the removal type and removal code are defined.

[0041] In a feasible embodiment, step 101 includes:

[0042] Obtain the adjustment configuration parameters set by the user, and transmit the adjustment configuration parameters to the intermediate parameter interface table of the intermediate database through the network protocol;

[0043] The intermediate parameter interface table in the intermediate database is synchronized to the target parameter interface table in the target database to obtain the parameter interface data in the target parameter interface table.

[0044] Because this method allows users to set and adjust configuration parameters at any time, to facilitate system management, after users set and adjust configuration parameters, the adjusted configuration parameters are first transferred to the intermediate parameter interface table in the intermediate database. Finally, the intermediate parameter interface table in the intermediate database is synchronized with the target parameter interface table in the target database to obtain the parameter interface data in the target parameter interface table. The timing of synchronizing the intermediate parameter interface table in the intermediate data to the target parameter interface table in the target database can be determined based on the actual needs of the indicator determination and is not limited here.

[0045] In a feasible embodiment, the intermediate parameter interface table in the intermediate database is synchronized with the target parameter interface table in the target database to obtain the parameter interface data in the target parameter interface table, including:

[0046] The scheduling server periodically triggers a copy job to synchronize all parameters in the intermediate parameter interface table to the target parameter interface table, obtains the parameter interface data in the target parameter interface table, and transmits the parameter interface data in the target parameter interface table back to the intermediate parameter interface table for front-end report display.

[0047] For example, when a bank user updates parameters on the system page, the parameter changes, namely the parameter interface data, are transmitted via the network protocol to the parameter interface table in the ORACLE database. This is equivalent to the intermediate parameter interface table in the intermediate data. The scheduling server then triggers a copy job on a scheduled basis, synchronizing all parameters in the parameter interface table to a parameter interface table with the same structure in the GreenPlum database at a preset time each day. The parameter interface table in the GreenPlum database is then used to participate in script batch execution. The full set of parameters in the parameter interface table includes not only the parameter interface data changed by the user, but also the original parameter interface data.

[0048] Step 102: Obtain capital data from the external component, and determine cash flow details based on the parameter interface data and the capital data.

[0049] The product range for indicator calculation is determined based on user-provided parameter interface data. The data warehouse then accesses source data from upstream components, including account-level data from systems like the general ledger and corporate credit contracts, and cash flow-level data from systems like interbank clearing, fund trading backend, fixed and demand deposits, loans, and agency trading. Detailed cash flow data is then determined from the source data based on the product range.

[0050] Optionally, after obtaining fund data from external components, store the existing data in the distributed database GreenPlum using institution, currency, and account number as distribution keys to prepare for filtering and summarizing cash flow details.

[0051] In a feasible embodiment, the external components include a fund transaction backend component, a customer agency component, an interbank clearing component, a deposit component, a loan component, a credit contract component, and a general ledger component, and the fund data includes account granularity data and cash flow granularity data.

[0052] In view of the characteristics of commercial banks' existing businesses, the embodiment of the present invention loads upstream data through a data subscription platform. The components involved include fund transaction backend, agency, interbank clearing, deposits, loans, credit contracts, general ledger, etc.

[0053] In a feasible embodiment, obtaining capital data from an external component and determining cash flow details data based on parameter interface data and the capital data include:

[0054] Obtain fund data from external components and perform data cleaning and preprocessing on the fund data;

[0055] Determine the data retrieval scope based on the cash flow type involved in the calculation in the parameter interface data, and determine the cash flow detail data from the fund data based on the data retrieval scope.

[0056] Process and process the collected capital data. Any abnormal data requires filtering and cleaning. Design cash flow data selection rules based on the product range and business scope of the parameter interface data provided by different users, including but not limited to table join conditions and record filtering conditions. Develop stored procedures and store batch execution results in the physical fact table of the relational database. This stores detailed cash flow data determined from the capital data based on the data retrieval criteria.

[0057] In a feasible embodiment, the data acquisition caliber is determined according to the cash flow type involved in the calculation in the parameter interface data, so as to determine the cash flow detail data from the capital data according to the data acquisition caliber, including:

[0058] Based on the parameter interface data for the initial left join of funds data, the caller component number and multi-entity identifier are used as join conditions to determine the data retrieval range, calculate the remaining term of the cash flow, and determine the remaining term sign based on its position on the timeline. The initial left join of funds data is obtained based on the data retrieval range and remaining term sign.

[0059] Based on the secondary left-association parameter interface data of the initial left-association fund data result, conditional judgment is used to match the corresponding field with the initial left-association fund data according to the removal type value to remove the target fund data and obtain the secondary left-association fund data result as the cash flow detail data involved in the calculation.

[0060] First, the basic data table is initially left-joined with the parameter interface data using the funding data retrieved from the upstream component. The caller component number and the institution's multi-entity identifier are used as join conditions to define the data range. The remaining cash flow term is then calculated, for example, using 180 days and 365 days as time nodes, and the product's remaining term symbol is defined based on where the remaining term falls on the timeline. Finally, SQL (Structured Query Language) conditional statements are used to address specific requirements within the processing rules. The removal type codes 1, 2, 3, 4, 5, 6, and 7 (character type) represent the contract number, available product number, customer number, corporate customer type code IS_CODE, currency, event type number, and account type, respectively. If the removal type field in the parameter interface table is non-null, the field referenced by its code value is not used as a filter condition. Assuming the other join conditions are met, all cash flow details are retained to serve as the data basis for subsequent reverse elimination. The initial left join is performed to determine the product data range that can be included in the liquidity indicator calculation.

[0061] Based on the secondary left-link parameter interface data from the initial left-linked fund data results, a conditional statement is used to match the corresponding fields with the primary left-linked fund data results based on the removal type value. Because only the primary left-linked fund data results that are to be removed can be secondary-linked to the filter parameter data in the parameter interface data, during the secondary left-link, simply set the filter condition to ensure that the institution multi-entity field in the secondary-link parameter table in the result table has a non-null value. This removes the target fund data records, and uses the secondary left-linked fund data results after removal as the cash flow details data for subsequent indicator calculations.

[0062] Step 103: Determine the liquidity indicator result based on the cash flow detail data and parameter interface data.

[0063] Classify cash flow details by business date, currency, product category, and other dimensions. Accumulate high-quality liquid assets, cash inflows, cash outflows, available stable funds, and stable funds required for the business. By importing the liquidity indicator measurement model, you can obtain the value of the liquidity indicator results at the target time node.

[0064] In one possible embodiment, the liquidity indicators include a liquidity coverage ratio and a net stable funding ratio;

[0065] Accordingly, the liquidity indicator results are determined based on the cash flow details data and parameter interface data, including:

[0066] Determine high-quality current assets, net cash outflow within the next 30 days, available stable funds, and stable funds required for business operations based on cash flow details and type weights in the parameter interface data;

[0067] The liquidity coverage ratio and net stable funding ratio are determined based on high-quality liquid assets, net cash outflow within the next 30 days, available stable funds, and stable funds required for business operations.

[0068] The Liquidity Coverage Ratio (LCR) = High-Quality Liquid Assets / Net Cash Outflows over the Next 30 Days. It primarily measures an institution's ability to manage liquidity risk from a short-term perspective, ensuring it has sufficient liquidity resources to address short-term liquidity risks within 30 days. Regulatory requirements generally require a value of no less than 1. The Net Stable Funding Ratio (NSFR) = Available Stable Funds (ASF) / Required Stable Funds (RSF). The Net Stable Funding Ratio indicates whether a bank has a stable source of funding to sustain operations and survive for at least one year under sustained stress. It aims to encourage banks to adopt more stable and sustainable funding channels, improve their ability to manage liquidity risk over the long term, and optimize their financing structure. Regulatory requirements generally require a value greater than 1. For example, commercial banks use the Liquidity Coverage Ratio (LCR) (short-term, next 30 days) and the Net Stable Funding Ratio (NSFR) (long-term, one year and above) as liquidity indicators to assess the balance of on- and off-balance sheet assets and liabilities and reflect future liquidity conditions. In order to submit reports to local regulators in a timely manner and quickly adjust the asset-liability scale and maturity mismatch structure based on the indicator results, bank users will provide end-of-day LCR / NSFR reports and intraday LCR reports (2 batches). The end-of-day reports are effective on T+1, the local business time, and the intraday reports are effective at 10:30 and 14:30 on T, the local business time. The purpose is to monitor the changing trend of liquidity exposure on a daily basis and to be informed of changes in cash flow on the business day.

[0069] Specifically, detailed cash flow data is summarized by dimensions such as business date, currency, and product category. At the same time, high-quality liquid assets, cash inflows, cash outflows, available stable funds, and stable funds required for the business are accumulated, and the LCR and NSFR measurement models are imported to obtain the values ​​of the liquidity coverage ratio LCR and the net stable funding ratio NSFR at the target time node.

[0070] In one possible embodiment, the method further includes:

[0071] The cash flow details data, parameter interface data and liquidity indicator results are sent to the intermediate data table for front-end report display and for users to view, so that users can adjust configuration parameters and independently enter fund data based on the cash flow details data, parameter interface data and liquidity indicator results.

[0072] When the script batch job is completed, the cash flow details data, liquidity indicator results and parameter interface data are sent back to the ORACLE database for front-end report display, so that users can receive the liquidity indicator query results under the latest data caliber in a timely manner.

[0073] If the liquidity indicator query result does not meet the user's requirements, the user can continue to adjust the configuration parameters to generate new parameter interface data and obtain new liquidity indicator query results until the liquidity indicator query result meets the user's requirements.

[0074] Specifically, in addition to providing users with a one-way visual display of indicator calculation results, the embodiment of the present invention also provides a data verification function, which supports users to download and obtain the original detailed data used to calculate each indicator and the event amount summarized under each major item / sub-item, so as to facilitate users to check and verify the results of the liquidity indicator report. When the indicator value does not meet local regulatory requirements, the problem can be quickly located, thereby more scientifically planning the short-term and long-term asset-liability structure.

[0075] Optionally, the query information configured by the user on the client side is transmitted to the server side through the HTTP protocol. The server side calls the interface to receive the cash flow details and indicators under the corresponding business date and currency in the result table, and finally returns the calculation results to the user in the form of a report. The embodiment of the present invention provides bank users with personalized autonomous query functions through job configuration and user selection of business attributes such as data date, expiration date, currency, etc. at the front desk. Job configuration allows different users to obtain reports and page function menus under their jurisdiction and shield other irrelevant information. When displaying liquidity indicators and liquidity fund details, only valid data under the selected conditions are presented to the user, allowing them to obtain more accurate calculation results within the scope of their authority.

[0076] In a feasible embodiment, the method further includes: obtaining the self-recorded supplementary fund data input by the user;

[0077] Accordingly, the method further includes:

[0078] Verify the liquidity indicator results based on the self-recorded fund data and fund data.

[0079] If the current liquidity indicator results do not meet the user's requirements, the user can independently re-enter funds data based on the actual situation of the bank's products. For example, in addition to having external components provide data in batches on a scheduled basis, embodiments of the present invention support users to independently re-enter funds data on demand through incremental import or single entry. Various fields in the user-entered funds data can be verified based on actual business conditions, thereby achieving the purpose of automated system data configuration and collection.

[0080] The embodiments of the present invention are based on obtaining user-set adjustment configuration parameters, determining parameter interface data based on the adjustment configuration parameters; obtaining capital data from an external component, determining cash flow detail data based on the parameter interface data and the capital data; and determining liquidity indicator results based on the cash flow detail data and the parameter interface data. By participating in the process of determining liquidity indicator results based on the user-set adjustment configuration parameters, the data collection criteria for products involved in liquidity indicator calculations are updated in a timely manner, thereby improving the timeliness of bank liquidity indicator determination. Furthermore, the calculation of liquidity indicators can be customized based on the needs of different bank users, facilitating scientific asset structure planning for bank users, saving time and costs for risk analysis, and improving efficiency.

[0081] Example 2

[0082] Figure 2 This is a schematic diagram of the structure of the bank liquidity indicator determination system in the second embodiment of the present invention. This second embodiment is a preferred implementation of the first embodiment. Figure 2 As shown, the system includes a data acquisition module 210, a parameter configuration module 220, an indicator processing module 230 and a user interaction module 240:

[0083] like Figure 3 Shown is a structural diagram of the data acquisition module.

[0084] The data acquisition module includes enterprise-level account granularity and cash flow granularity data collection and data storage.

[0085] When collecting data, this system, tailored to the specific characteristics of commercial banks' existing businesses, loads upstream data from a data subscription platform. The involved components include fund transaction backend, agency services, interbank clearing, deposits, loans, credit contracts, and the general ledger. In addition to scheduled batch data feeds from external components, users can independently enter data on demand through incremental import or single entry. Various fields can be verified based on actual business conditions, achieving automated system data configuration and collection.

[0086] When storing data, the existing data is stored in the distributed database GreenPlum using the institution, currency, and accounting account number as the distribution key, in preparation for screening and summarizing cash flow details.

[0087] like Figure 4 The figure shows the structural diagram of the parameter configuration module.

[0088] The parameter configuration module includes configurable product parameters. Users can configure the configurable product parameters according to actual needs in the system front-end interface, and after the configuration is completed, it is transmitted to the back-end server through the network protocol.

[0089] Due to the diverse product offerings of commercial banks and differing regulatory policies, the cash flows involved in calculating liquidity indicators and their weighting often vary from place to place. This system allows users to add, delete, modify, and query relevant configuration parameters in LCR and NSFR on the front-end page, describing the nature of the product to accurately locate the details of each cash flow transaction. The common dimensions involved in the LCR and NSFR parameter configuration model include: unique number, multi-entity identifier, major category code, major category name, subcategory code, subcategory name, caller component number, product number / account number / interbank lending code, customer type, customer code, removal type, removal code, forecast days, recurrence flag, event type, whether to restrict pre-accrual interest, interest and event amount type, amount symbol, term type, investment type, credit type, regional category identifier, currency, bond rating, etc.

[0090] The parameter configuration module also includes a scheduled parameter replication task. When a bank user updates parameters on the system page, the parameter changes, namely the parameter interface data, are transmitted via the network protocol to the parameter interface table in the ORACLE database. This is equivalent to the intermediate parameter interface table in the intermediate data. The scheduling server then triggers a scheduled copy job to synchronize all parameters in the parameter interface table to the parameter interface table with the same structure in the GreenPlum database at a preset time each day. The parameter interface table in the GreenPlum database is then used to participate in script batch execution. The full set of parameters in the parameter interface table includes not only the parameter interface data changed by the user, but also the original parameter interface data.

[0091] like Figure 5 Shown is a structural diagram of the indicator processing module.

[0092] The financial data collected by the data acquisition module is processed and handled. Any abnormal data is filtered and cleaned, and pre-processed according to a predetermined unified format. The data acquisition scope is determined based on the LCR and NSFR parameter configuration information in the parameter interface table of the configuration module. For example, the data acquisition scope is determined based on the product number, customer type, event type, and accounting subject in the parameter configuration table. Cash flow fund details are then determined based on the data acquisition scope.

[0093] Specifically, when retrieving data based on the data retrieval criteria, the upstream component base data table is first left-joined with the parameter interface table, using the caller component number and the institution's multi-entity identifier as join conditions to define the data retrieval range. The remaining cash flow term is then calculated, using 180 days and 365 days as time nodes, and the product remaining term symbol is defined based on where the remaining term falls on the timeline. Finally, SQL conditional statements are used to address special requirements within the processing rules. The rejection type Reject_Type codes 1, 2, 3, 4, 5, 6, and 7 (character type) represent the contract number, saleable product number, customer number, public customer type code IS_CODE, currency, event type number, and account type, respectively. If the value of this field in the parameter interface table is not null, the field referenced by the code value is not used as a filtering condition. Assuming that the other join conditions are met, the full cash flow details are retained and used as the data basis for subsequent reverse elimination. The parameter interface table is then left-joined again, and a conditional statement is used to match the corresponding field with the master data table based on the rejection type value. Because only the main table records that need to be eliminated can be secondary-associated with the parameter records, you only need to set the filtering conditions to ensure that the value of the organization multi-entity field of the secondary-associated parameter table in the result table is not empty, then you can eliminate the target records and use the remaining details to participate in the indicator calculation.

[0094] After pre-processing the funds data according to the data collection criteria, a planned detailed screening and storage process is performed to generate cash flow details and store them in the cash flow details physical table. The cash flow data in the cash flow details physical table is imported into the liquidity indicator LCR and NSFR measurement model. The model generates a liquidity indicator report display result table based on the indicator calculation formula.

[0095] For example, when the indicator calculation task is completed, the cash flow details table, liquidity indicator result table and parameter interface table are sent back to the ORACLE database for front-end report display, so that users can receive the liquidity indicator query results under the latest caliber in a timely manner.

[0096] like Figure 6 Shown is a structural diagram of the user interaction module.

[0097] In the user interaction module, users interact with the system front-end interface to enter product parameters to be included in the calculation, confirm the product range of the parameter configuration table, associate the subcategory details of the master data table, summarize the major categories according to the report display dimensions, calculate and return liquidity indicators, and users query the report results according to the conditions.

[0098] Furthermore, within the user interaction module, the system provides users with personalized, self-service query capabilities through job configuration and user-selected business attributes such as data date, expiration date, and currency. Job configuration permissions allow different users to access reports and page function menus within their respective jurisdictions while blocking irrelevant information. When displaying indicators and details, only valid data within the selected conditions is presented to users, enabling more accurate calculation results within their permissions. Job configuration can be determined using the bank's unique identifier.

[0099] To speed up report refreshes when scope changes occur and enhance the user experience, a data preloading unit is included in the user interaction module to periodically schedule scripts to run batch jobs. This means that regardless of whether the user is viewing the report, the system will periodically schedule ETL (Extract-Transform-Load) jobs and copy the indicator calculation results to the corresponding interface tables in the ORACLE database for data preloading. After asynchronously acquiring parameter changes, they are applied to the indicator processing stored procedures in the GreenPlum database on the same day, providing users with timely feedback on the latest indicator values ​​under the latest scope, meeting system timeliness requirements.

[0100] In the user interaction module, in addition to providing users with a one-way visual display of calculation results, a data verification unit is also set up to support users in downloading and obtaining the original detailed data used to calculate each indicator and the event amounts summarized under each major item and sub-item. This facilitates users to check and verify the report results, and when the indicator values ​​do not meet local regulatory requirements, the problem can be quickly located.

[0101] In the bank liquidity indicator determination system provided by the embodiments of the present invention, user-provided adjustment configuration parameters can be promptly applied to the indicator processing stored procedures, updating the data retrieval caliber and thus meeting the timeliness requirements of reports. Furthermore, by pre-defining data interface models for ORACLE and GreenPlum databases, a scheduled ETL job is triggered daily to run batches and copy the full data to a publicly accessible area. The final results can then be displayed on the system front page according to pre-defined reports, making it easier for users to adjust configuration parameters based on the reports and improve their understanding of liquidity indicators.

[0102] The embodiments of the present invention provide a system that can flexibly adjust the product range and data acquisition caliber for calculating liquidity indicators, solving the problem of previously requiring the system to suspend external services and modify stored procedures, resulting in poor report timeliness and a poor user experience. Furthermore, bank users can independently select the current cash flow data to be displayed in the liquidity indicator report on the system front page. By adding, deleting, modifying, and querying product parameters, the data range involved in the indicator calculation is updated in real time, generating reports that are consistent with actual business operations. This allows for timely reporting of liquidity status to local regulators, more scientific planning of short-term and long-term asset-liability structures, saving time and costs for risk analysis, and improving work efficiency.

[0103] Example 3

[0104] Figure 7 This is a schematic diagram of the structure of the bank liquidity index determination device in the third embodiment of the present invention. This embodiment is applicable to the case where the bank liquidity index is determined based on the data acquisition caliber adjusted in real time. Figure 7 As shown, the device includes:

[0105] The parameter data determination module 710 is used to obtain the adjustment configuration parameters set by the user and determine the parameter interface data according to the adjustment configuration parameters;

[0106] A cash flow detail determination module 720 is configured to obtain capital data from an external component and determine cash flow detail data based on the parameter interface data and the capital data;

[0107] The liquidity indicator determination module 730 is configured to determine a liquidity indicator result based on the cash flow detail data and the parameter interface data.

[0108] The embodiments of the present invention are based on obtaining user-set adjustment configuration parameters, determining parameter interface data based on the adjustment configuration parameters; obtaining capital data from an external component, determining cash flow detail data based on the parameter interface data and the capital data; and determining liquidity indicator results based on the cash flow detail data and the parameter interface data. By participating in the process of determining liquidity indicator results based on the user-set adjustment configuration parameters, the data collection criteria for products involved in liquidity indicator calculations are updated in a timely manner, thereby improving the timeliness of bank liquidity indicator determination. Furthermore, the calculation of liquidity indicators can be customized based on the needs of different bank users, facilitating scientific asset structure planning for bank users, saving time and costs for risk analysis, and improving efficiency.

[0109] Optionally, the adjustment configuration parameters are set by the user according to changes in regulatory policies.

[0110] Optionally, the adjustment configuration parameters include the cash flow types involved in the calculation and the type weights; wherein, the cash flow types involved in the calculation are determined by common dimensions; the common dimensions include at least one of the following: unique number, multi-entity identifier, major category code, major category name, subcategory code, subcategory name, caller component number, product number, account number, interbank lending code, customer type, customer code, removal type, removal code, forecast days, cycle flag, event type, whether to limit pre-interest, interest and event amount type, amount symbol, term type, investment type, credit type, regional category identifier, currency and bond rating.

[0111] Optionally, the removal type and the removal code are used to define a filtered cash flow type.

[0112] Optionally, a parameter data determination module includes:

[0113] An intermediate transmission unit, configured to obtain adjustment configuration parameters set by a user, and transmit the adjustment configuration parameters to an intermediate parameter interface table of an intermediate database via a network protocol;

[0114] The parameter synchronization unit is used to synchronize the intermediate parameter interface table in the intermediate database to the target parameter interface table in the target database to obtain the parameter interface data in the target parameter interface table.

[0115] Optional parameter synchronization unit, specifically used for:

[0116] The scheduling server periodically triggers a copy operation to synchronize all parameters in the intermediate parameter interface table to the target parameter interface table, obtains the parameter interface data in the target parameter interface table, and transmits the parameter interface data in the target parameter interface table back to the intermediate parameter interface table for front-end report display.

[0117] Optionally, the device further includes a return module, configured to:

[0118] The cash flow detail data, the parameter interface data and the liquidity indicator results are sent to the intermediate data table for front-end report display for user viewing, so that the user can adjust the configuration parameters and independently supplement the fund data according to the cash flow detail data, the parameter interface data and the liquidity indicator results.

[0119] Optionally, the external components include a funds transaction backend component, a customer agency component, an interbank clearing component, a deposit component, a loan component, a credit contract component, and a general ledger component, and the funds data includes account granularity data and cash flow granularity data.

[0120] Optionally, the device further includes a user funds supplementary recording module, which is used to: obtain the self-supplementary funds data input by the user;

[0121] Accordingly, the device further includes a liquidity indicator verification module, which is used to:

[0122] The liquidity indicator result is verified based on the self-recorded fund data and the fund data.

[0123] Optional module for determining cash flow details, including:

[0124] A fund data preprocessing unit, configured to obtain fund data from an external component and perform data cleaning and data preprocessing on the fund data;

[0125] The fund data acquisition unit is used to determine the acquisition caliber according to the cash flow type involved in the calculation in the parameter interface data, so as to determine the cash flow detail data from the fund data according to the acquisition caliber.

[0126] Optional fund data acquisition unit, specifically used for:

[0127] Initially left-associate the parameter interface data based on the capital data, determine the data retrieval range using the caller component number and the multi-entity identifier as association conditions, calculate the remaining term of the cash flow, determine the remaining term sign based on the position of the remaining term on the time axis, and obtain the initial left-association result of the capital data based on the data retrieval range and the remaining term sign;

[0128] According to the result of the initial left-association of funds data, the parameter interface data is left-associated for the second time, and the conditional judgment is used to match the corresponding field with the initial left-association of funds data according to the value of the removal type to remove the target funds data and obtain the result of the secondary left-association of funds data as the cash flow detail data involved in the calculation.

[0129] Optionally, the liquidity indicators include liquidity coverage ratio and net stable funding ratio;

[0130] Accordingly, the liquidity indicator determination module is specifically used to:

[0131] Determine high-quality current assets, net cash outflow within the next 30 days, available stable funds, and stable funds required for business operations based on the cash flow details data and the type weights in the parameter interface data;

[0132] The liquidity coverage ratio and net stable funding ratio are determined based on the high-quality liquid assets, net cash outflow within the next 30 days, available stable funds, and stable funds required for business operations.

[0133] The bank liquidity indicator determination device provided in the embodiment of the present invention can execute the bank liquidity indicator determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the bank liquidity indicator determination method.

[0134] Example 4

[0135] Figure 8 This is a structural diagram of an electronic device provided in Example 4 of the present invention. Figure 8 A block diagram of an exemplary electronic device 12 suitable for implementing embodiments of the present invention is shown. Figure 8 The electronic device 12 shown is only an example and should not limit the functionality and scope of use of the embodiments of the present invention.

[0136] like Figure 8 As shown, electronic device 12 is implemented as a general-purpose computing device. Components of electronic device 12 may include, but are not limited to, one or more processors or processing units 16, system memory 28, and a bus 18 connecting various system components (including system memory 28 and processing unit 16).

[0137] Bus 18 represents one or more of several types of bus structures, including a storage device bus or storage device controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. Examples of these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0138] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0139] The system storage device 28 may include computer system readable media in the form of volatile storage devices, such as random access memory devices (RAM) 30 and / or cache memory devices 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 8 Not shown, often called a "hard drive"). Although Figure 8Although not shown, a magnetic disk drive for reading and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. Storage device 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of various embodiments of the present invention.

[0140] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in storage device 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may include an implementation of a network environment. Program modules 42 generally implement the functions and / or methods of the embodiments described herein.

[0141] The electronic device 12 may also communicate with one or more external devices 14 (e.g., a keyboard, a pointing device, a display 24, etc.), one or more devices that enable a user to interact with the device 12, and / or any device that enables the device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed through an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 20. Figure 8 As shown, the network adapter 20 communicates with other modules of the electronic device 12 via the bus 18. Figure 8 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0142] The processing unit 16 executes various functional applications and data processing by running programs stored in the system storage device 28, such as implementing the bank liquidity indicator determination method provided in an embodiment of the present invention, including:

[0143] Acquire adjustment configuration parameters set by the user, and determine parameter interface data according to the adjustment configuration parameters;

[0144] Obtaining fund data from an external component, and determining cash flow detail data based on the parameter interface data and the fund data;

[0145] A liquidity indicator result is determined based on the cash flow detail data and the parameter interface data.

[0146] Example 5

[0147] The fifth embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for determining a bank liquidity indicator provided in the embodiment of the present invention is implemented, including:

[0148] Acquire adjustment configuration parameters set by the user, and determine parameter interface data according to the adjustment configuration parameters;

[0149] Obtaining fund data from an external component, and determining cash flow detail data based on the parameter interface data and the fund data;

[0150] A liquidity indicator result is determined based on the cash flow detail data and the parameter interface data.

[0151] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or components, or any combination thereof. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by an instruction execution system, device or device or used in combination with it.

[0152] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0153] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0154] The computer program code for performing the operations of the present invention can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0155] Note that the above are only preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments and may include many other equivalent embodiments without departing from the concept of the present invention. The scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for determining a bank liquidity index, characterized in that: include: Acquire the adjustment configuration parameters set by the user, and determine the parameter interface data according to the adjustment configuration parameters; the adjustment configuration parameters are set by the user in the front-end interface of the bank liquidity indicator determination system according to the change of the regulatory policy, and are used to determine the range of asset data that can be included in the calculation of the liquidity indicator; The parameter interface data determination method includes: the user independently selects the type of cash flow data to be displayed in the liquidity indicator report on the system front-end interface, and adds, deletes, modifies and queries product parameters; Acquire the capital data from the external component, and determine the cash flow detail data according to the parameter interface data and the capital data, including: acquiring the capital data from the external component, and performing data cleaning and data preprocessing on the capital data; determining the data acquisition caliber according to the cash flow type involved in the calculation in the parameter interface data, so as to determine the cash flow detail data from the capital data according to the data acquisition caliber; The liquidity indicator result is determined according to the cash flow detail data and the parameter interface data, including: classifying the cash flow detail data by business date, currency, and product category, accumulating liquidity high-quality assets, cash inflows, cash outflows, available stable funds, and stable funds required for the business, importing the liquidity indicator measurement model, and obtaining the value of the liquidity indicator result at the target time node.

2. The method according to claim 1, characterized in that The adjustment configuration parameters include the cash flow types involved in the calculation and the type weights; wherein, the cash flow types involved in the calculation are determined by common dimensions; the common dimensions include at least one of the following: unique number, multi-entity identifier, major category code, major category name, subcategory code, subcategory name, caller component number, product number, account number, interbank lending code, customer type, customer code, removal type, removal code, forecast days, cycle flag, event type, whether to limit pre-interest, interest and event amount type, amount symbol, term type, investment type, credit type, regional category identifier, currency and bond rating.

3. The method according to claim 2, characterized in that The removal type and the removal code are used to define the filtered cash flow type.

4. The method according to claim 1, characterized in that: Acquiring the adjustment configuration parameters set by the user, and determining the parameter interface data according to the adjustment configuration parameters, including: Acquire the adjustment configuration parameters set by the user, and transmit the adjustment configuration parameters to the intermediate parameter interface table of the intermediate database through the network protocol; The intermediate parameter interface table in the intermediate database is synchronized with the target parameter interface table in the target database to obtain the parameter interface data in the target parameter interface table.

5. The method according to claim 4, characterized in that Synchronizing the intermediate parameter interface table in the intermediate database to the target parameter interface table in the target database to obtain parameter interface data in the target parameter interface table, including: The scheduling server periodically triggers a copy operation to synchronize all parameters in the intermediate parameter interface table to the target parameter interface table, obtains the parameter interface data in the target parameter interface table, and transmits the parameter interface data in the target parameter interface table back to the intermediate parameter interface table for front-end report display.

6. The method according to any one of claims 4-5, characterized in that: The method further comprises: The cash flow detail data, the parameter interface data and the liquidity indicator result are sent to the intermediate data table for front-end report display for users to view, so that users can adjust configuration parameters and independently supplement fund data according to the cash flow detail data, the parameter interface data and the liquidity indicator result.

7. The method according to claim 1, characterized in that The external components include a fund transaction backend component, an agency component, an interbank clearing component, a deposit component, a loan component, a credit contract component and a general ledger component, and the fund data includes account granularity data and cash flow granularity data.

8. The method according to claim 1, characterized in that The method further includes: obtaining the self-recorded supplementary fund data input by the user; Accordingly, the method further includes: The liquidity indicator result is verified based on the self-recorded fund data and the fund data.

9. The method according to claim 1, characterized in that: Determining the data acquisition caliber according to the cash flow type involved in the calculation in the parameter interface data, so as to determine the cash flow detail data from the capital data according to the data acquisition caliber, including: The parameter interface data is initially left-associated with the capital data, the data acquisition range is determined with the caller component number and the multi-entity identifier as the association conditions, and the remaining term of the cash flow is calculated, the remaining term symbol is determined according to the position of the remaining term on the time axis, and the initial left-associated capital data result is obtained according to the data acquisition range and the remaining term symbol; The parameter interface data is left-associated for a second time according to the result of the initial left-association of the funds data, and conditional judgment is used to match the initial left-association of the funds data according to the corresponding field based on the value of the removal type to remove the target funds data, and obtain the result of the secondary left-association of the funds data as the cash flow detail data involved in the calculation.

10. The method according to claim 1, characterized in that The liquidity indicators include liquidity coverage ratio and net stable funding ratio; Accordingly, the liquidity indicator result is determined according to the cash flow detail data and the parameter interface data, including: Determine high-quality current assets, net cash outflow within the next 30 days, available stable funds, and stable funds required for the business based on the cash flow detail data and the type weights in the parameter interface data; The liquidity coverage ratio and net stable funding ratio are determined based on the high-quality current assets, net cash outflow within the next 30 days, available stable funds and stable funds required for the business.

11. A device for determining a bank liquidity index, characterized in that: include: A parameter data determination module, used to obtain adjustment configuration parameters set by the user, and determine parameter interface data according to the adjustment configuration parameters; wherein the adjustment configuration parameters are set by the user in the front-end interface of the bank liquidity indicator determination system according to the change of the regulatory policy, and are used to determine the range of asset data that can be included in the calculation of the liquidity indicator; The parameter data determination module is specifically used for the user to independently select the type of cash flow data to be displayed in the liquidity indicator report on the front-end interface of the system, and to add, delete, modify and query product parameters; A cash flow detail determination module, used to obtain capital data from an external component and determine cash flow detail data according to the parameter interface data and the capital data; The cash flow details determination module includes: a capital data preprocessing unit and a capital data acquisition unit; The fund data preprocessing unit is used to obtain the fund data from the external component and perform data cleaning and data preprocessing on the fund data; The fund data acquisition unit is used to determine the acquisition caliber according to the cash flow type involved in the calculation in the parameter interface data, so as to determine the cash flow detail data from the fund data according to the acquisition caliber; A liquidity indicator determination module, used to determine a liquidity indicator result according to the cash flow detail data and the parameter interface data; The liquidity indicator determination module is specifically used to classify the cash flow detail data according to business date, currency, and product category dimensions, while accumulating high-quality liquidity assets, cash inflows, cash outflows, available stable funds, and stable funds required for the business, importing the liquidity indicator measurement model, and obtaining the value of the liquidity indicator result at the target time node.

12. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the bank liquidity indicator determination method as described in any one of claims 1-10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for determining a bank liquidity indicator as described in any one of claims 1 to 10 is implemented.

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