Data processing method and device

Abstract

The invention provides a data processing method and device, is applied to the field of data processing, and is used for improving the accuracy of credit risk assessment of a financial institution. The method comprises the steps of obtaining feature information of a first financial institution; determining one or more indexes according to the feature information of the first financial institution; one or more pieces of information are determined and output according to the one or more indexes, the one or more indexes are in one-to-one correspondence with the one or more pieces of information, and the information is used for indicating the credit risk of the first financial institution.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a data processing method and device. Background Art

[0002] The non-performing loan (or credit) rate of a financial institution (such as a bank) is usually an important piece of information that reflects credit risk, and changes in the non-performing loan rate are caused by different factors.

[0003] The existing technology uses macroeconomic indicators to evaluate the non-performing loan ratio of each financial institution, and the analysis results obtained are incomplete and have poor accuracy.

[0004] Therefore, how to improve the accuracy of credit risk assessment of financial institutions is an urgent problem to be solved. Summary of the invention

[0005] The present application provides a data processing method and device for improving the accuracy of credit risk assessment of financial institutions.

[0006] In a first aspect, an embodiment of the present application provides a data processing method, which can be applied to any electronic device with processing capabilities, including:

[0007] Acquire characteristic information of the first financial institution; the characteristic information includes the industry to which the credit of the first financial institution flows;

[0008] Determine at least one industry that has a correlation relationship with the credit risk of the first financial institution based on the characteristic information;

[0009] Determine at least one indicator according to at least one industry; wherein each industry in the at least one industry corresponds to one or more indicators in the at least one indicator;

[0010] At least one information is determined and outputted according to at least one indicator, the at least one indicator corresponds to the at least one information, and the information is used to indicate the credit risk of the first financial institution.

[0011] In this method, since the credit risk of the first financial institution is strongly correlated with the industry into which the credit flows, and the industry concentration of customers of different financial institutions is also different, at least one industry (i.e., industry) related to the credit risk of the first financial institution is screened out from the industry into which the credit of the first financial institution flows, and then at least one indicator is determined based on at least one industry, so that the indicator related to the credit risk of the first financial institution can be obtained, and then the credit risk of the first financial institution can be evaluated based on the indicator, which can improve the accuracy of the credit risk assessment.

[0012] Optionally, determining at least one indicator based on at least one industry includes: obtaining all indicators of each industry in at least one industry; screening out at least one indicator from all indicators, wherein the correlation between each indicator of the at least one indicator and the profit margin of the industry corresponding to each indicator is greater than a threshold.

[0013] In this method, after determining at least one industry related to the credit risk of the first financial institution, at least one indicator whose correlation with the profit margin of the corresponding industry is greater than a threshold is further screened out from all indicators of the at least one industry, that is, at least one indicator in each industry whose correlation with the profit margin of the industry is greater than a threshold. Since credit risk is mainly related to the profit margin (that is, income) of the industry, indicators with low correlation with the industry profit margin can be excluded first, thereby reducing the consumption of computing resources for credit risk assessment and improving the efficiency and accuracy of credit risk assessment.

[0014] Optionally, the characteristic information also includes the region where the first financial institution is located; the method also includes: determining at least one of the gross domestic product (GDP), inflation rate (CPI), unemployment rate, money supply, fiscal deficit, public external debt, and trade balance of the region where the first financial institution is located based on the region where the first financial institution is located; and determining and outputting at least one information based on the at least one item.

[0015] In this method, at least one indicator is determined based on the region where the first financial institution is located, so that the obtained indicator can more accurately reflect the economic situation of the region where the first financial institution is located, thereby improving the accuracy and reliability of subsequent risk assessment of the first financial institution.

[0016] Optionally, the characteristic information also includes the type of the first financial institution; the first financial institution is a bank; the method also includes: determining the interest rate of the bank according to the type of the bank; and determining and outputting a piece of information according to the interest rate.

[0017] In this method, the interest rate of a bank is determined according to the type of bank, and the interest rate of the bank is used as one of the indicators of the bank, so that the indicator can more accurately reflect the situation of the bank itself, thereby improving the accuracy and reliability of subsequent risk assessment of the bank.

[0018] Optionally, at least one industry includes an industrial industry, and at least one indicator is determined based on the at least one industry, including: determining at least one of the industrial producer purchase price index, industrial producer ex-factory price index, means of production price index, product output, and inventory of the industrial industry based on the industrial industry.

[0019] Optionally, at least one industry includes the real estate industry, and at least one indicator is determined based on the at least one industry, including: determining at least one of the real estate industry's commercial housing sales area, real estate construction area, real estate completion area, and actual real estate development investment based on the real estate industry.

[0020] Optionally, the method also includes: dividing multiple financial institutions into one or more sets according to characteristic information of the multiple financial institutions, each set includes financial institutions corresponding to the same characteristic information, and the multiple financial institutions include the first financial institution; determining at least one indicator based on the characteristic information corresponding to each set, and the determined at least one indicator corresponds to each financial institution in each set.

[0021] In this method, multiple financial institutions are divided into one or more sets according to their characteristic information. The characteristic information of the financial institutions in each set is the same. At least one indicator corresponding to each set is determined to facilitate credit risk assessment for each set, which can improve the efficiency of risk assessment and facilitate the display of the overall credit risk size of financial institutions in the same region and / or the same type.

[0022] In a second aspect, an embodiment of the present application provides a data processing device, including:

[0023] An acquisition module is used to: acquire characteristic information of the first financial institution; the characteristic information includes the industry to which the credit of the first financial institution flows;

[0024] A processing module, used to: determine at least one industry associated with the credit risk of the first financial institution based on the characteristic information; determine at least one indicator based on the at least one industry; wherein each industry in the at least one industry corresponds to one or more indicators in the at least one indicator; determine at least one information based on the at least one indicator, wherein the at least one indicator corresponds to the at least one information in a one-to-one manner, and the information is used to indicate the credit risk of the first financial institution;

[0025] The output module is used to: output at least one information.

[0026] Optionally, when determining at least one indicator based on at least one industry, the processing module is used to: obtain all indicators of each industry in at least one industry; filter out at least one indicator from all indicators, and the correlation between each indicator of the at least one indicator and the profit margin of the industry corresponding to each indicator is greater than a threshold.

[0027] Optionally, the characteristic information also includes the region where the first financial institution is located; the processing module is also used to: determine at least one item of the gross domestic product (GDP), inflation rate (CPI), unemployment rate, money supply, fiscal deficit, public external debt, and trade balance of the region where the first financial institution is located based on the region where the first financial institution is located, and determine and output at least one information based on the at least one item.

[0028] Optionally, the characteristic information also includes the type of the first financial institution; the first financial institution is a bank; and the processing module is further used to: determine the interest rate of the bank according to the type of the bank, and determine and output a piece of information according to the interest rate.

[0029] Optionally, at least one industry includes an industrial industry, and when the processing module determines at least one indicator based on at least one industry, it is used to: determine at least one of the industrial producer purchase price index, industrial producer ex-factory price index, means of production price index, product output, and inventory of the industrial industry based on the industrial industry.

[0030] Optionally, at least one industry includes the real estate industry. When determining at least one indicator based on at least one industry, the processing module is used to: determine at least one of the real estate industry's commercial housing sales area, real estate construction area, real estate completion area, and actual real estate development investment based on the real estate industry.

[0031] Optionally, the processing module is also used to: divide multiple financial institutions into one or more sets according to characteristic information of the multiple financial institutions, each set includes financial institutions corresponding to the same characteristic information, and the multiple financial institutions include the first financial institution; determine at least one indicator based on the characteristic information corresponding to each set, and the determined at least one indicator corresponds to each financial institution in each set.

[0032] In a third aspect, an embodiment of the present application provides an electronic device, comprising at least one processor, wherein the at least one processor is used to execute a computer program stored in a memory so that a method as in the first aspect or any optional implementation of the first aspect is implemented.

[0033] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which is used to store instructions. When the instructions are executed, the method in the first aspect or any optional implementation of the first aspect is implemented.

[0034] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program code, which, when executed on a computer, enables the method in the first aspect or any optional implementation of the first aspect to be implemented.

[0035] The technical effects or advantages of one or more technical solutions provided in the second, third, fourth and fifth aspects of the embodiments of the present application can be correspondingly explained by the technical effects or advantages of one or more corresponding technical solutions provided in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flow chart of a data processing method provided in an embodiment of the present application;

[0037] Figure 2 A structural diagram of a data processing device provided in an embodiment of the present application;

[0038] Figure 3 A structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] In the technical solution of this application, the collection, dissemination, and use of data are in compliance with the requirements of relevant national laws and regulations.

[0040] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0041] The technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0042] Introduction to professional terms:

[0043] 1. The non-performing credit ratio (i.e., non-performing credit loan ratio) refers to the proportion of non-performing credit of financial institutions to the total credit balance. Non-performing credit refers to the classification of credit into five categories based on risk when assessing credit quality: normal, special mention, substandard, doubtful and loss. The last three categories are collectively referred to as non-performing credit.

[0044] 2. Lag effect: It means that the dependent variable will not produce the expected effect immediately due to the change or influence of itself or an explanatory variable, but will only appear after a period of time.

[0045] 3. Price index: It is an economic indicator that reflects the direction, trend and degree of change in the price level of a group of commodities (service items) in different periods. It is a type of economic index and is usually expressed as a relative number comparing the reporting period (i.e. the current period) and the base period.

[0046] 4. In the description of the embodiments of the present application, "multiple" refers to two or more. "First", "second", etc. in the embodiments of the present application are used to distinguish different objects, rather than to describe a specific order. The term "and / or" in the embodiments of the present application is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "includes" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices. The module in the embodiments of the present application refers to a part with independent functions in a software system.

[0047] The assessment of the credit risk of financial institutions (such as the bank's non-performing loan ratio) usually adopts a static model, such as a static panel data model, the formula of which is as follows:

[0048] Y it =x it β it +z i δ+λ t +c i +u it

[0049] Among them, β it is the regression parameter of different time points (i.e. different periods) and different cross-sectional individuals (i.e. parameters related to credit risk), z i represents a variable that does not change over time, λ t represents the time effect that does not change with the cross-sectional individuals but changes with time, c i represents the individual effect that does not change with time but changes with the cross-sectional individuals, u it represents the random disturbance term, x it It refers to the indicators used, usually macroeconomic indicators such as gross domestic product (GDP) and consumer price index (CPI).

[0050] However, the above model does not take into account that the indicators that affect the credit risk of different regions and different types of financial institutions may be different; and different periods and different indicators have different effects on credit risk. It only analyzes the correlation between credit risk and some macroeconomic indicators, and does not take into account the indicators of various regions, nor the industry concentration attributes of customers of different types of financial institutions (such as banks). This will lead to an incomplete analysis of credit risk and poor accuracy of the analysis results. Customers in different industries involve different indicators, and different indicators have different degrees of impact on the credit risk of financial institutions, and thus the credit risk of financial institutions in different industries will also show different performance.

[0051] In view of this, an embodiment of the present application provides a data processing method, which determines at least one indicator of the first financial institution based on characteristic information of the first financial institution, including the region where the first financial institution is located, the type of the first financial institution, and the industry into which the credit of the first financial institution flows, so that the obtained indicator can more accurately reflect the situation of the first financial institution. According to each indicator of the at least one indicator, the impact of each indicator on the credit risk of the first financial institution is evaluated, so that the risk assessment of the first financial institution can be more accurate.

[0052] The data processing method provided in the embodiment of the present application is applicable to the credit risk assessment of financial institutions, including but not limited to the above-mentioned analysis of the bank's non-performing loan rate.

[0053] The data processing method provided in the embodiments of the present application can be applied to any electronic device with processing capabilities, such as servers, mobile phones, tablets, computers, etc.

[0054] See also Figure 1 , is a data processing method provided in an embodiment of the present application, taking the application to credit risk analysis as an example, the method includes steps S101 to S103:

[0055] S101. Obtain characteristic information of a first financial institution.

[0056] Exemplarily, the characteristic information of the first financial institution may include the industry into which the credit of the first financial institution flows.

[0057] The industries into which the first financial institution's credit flows include, for example, the industrial industry, agricultural industry, real estate industry, aerospace technology industry, etc. The corresponding industries are obtained based on the first financial institution's actual credit records.

[0058] S102. Determine at least one industry that has a correlation with the credit risk of the first financial institution based on the characteristic information.

[0059] For example, taking the first financial institution as a bank and the credit risk represented by the non-performing loan ratio, since the proportion of the amount of corporate credit flowing into different industries of different types of banks may vary greatly, it is necessary to determine whether the various industries into which the credit enters have an impact on the bank's credit risk.

[0060] Screening out at least one industry associated with the credit risk of the first financial institution from the industries into which the credit of the first financial institution flows, specifically including:

[0061] Taking the amount of bank credit flowing into a certain industry as x and the non-performing loan rate as Y, a Granger model is established to test whether the amount of credit loans flowing into the industry is related to the bank's non-performing loan rate.

[0062] The above method is used to verify whether each industry into which each bank's credit funds flow has an impact on the bank's non-performing loan rate.

[0063] Specifically, the formula of the Granger model is:

[0064] Among them, y t represents the value of the explained variable y at time t, x t represents the value of the explanatory variable x at time t, c1 is a constant term, α i and β j is the regression function, ε t is the error term.

[0065] The basic idea of ​​the Granger causality test is: assuming that the change of variable x is the cause of the change of variable y, then the change of variable x should be earlier than that of variable y in time, and variable x has a significant effect in predicting variable y, that is, in the regression model for predicting y, introducing the past observations of variable x as an independent variable should statistically significantly increase the explanatory power of the model.

[0066] Therefore, the Granger model can be used to screen out x that has a causal effect on y, that is, the flow of credit funds from a bank to a certain industry will have an effect on the bank's non-performing loan rate, thereby determining the industry that needs further analysis.

[0067] S103. Determine at least one indicator based on at least one industry.

[0068] Each industry in at least one industry corresponds to one or more indicators in at least one indicator.

[0069] Exemplarily, all indicators of the industry determined above that will affect the non-performing loan rate of the bank are determined. A specific example is given below:

[0070] Example 1: At least one industry includes an industrial industry, and at least one indicator is determined based on the at least one industry, including: determining at least one of the industrial producer purchase price index, industrial producer ex-factory price index, means of production price index, product output, and inventory of the industrial industry based on the industrial industry.

[0071] For the industrial sector, the factors affecting industry prosperity mainly include demand and supply. Therefore, indicators related to demand and supply can be selected as indicators for analyzing the industry.

[0072] Example 2: At least one industry includes the real estate industry, and at least one indicator is determined based on the at least one industry, including: determining at least one of the real estate industry's commercial housing sales area, real estate construction area, real estate completion area, and actual real estate development investment based on the real estate industry.

[0073] For the real estate industry, the factors that have a greater impact on the industry are mainly sales and investment. Therefore, indicators related to sales and investment can be selected as indicators for analyzing the industry.

[0074] It can be understood that the above are just two possible examples and are not limited thereto.

[0075] In a possible embodiment, all the indicators determined in the above steps based on at least one industry may be large in number, and there may be indicators that have little correlation with credit risk or industry economics. Using such indicators as indicators for analyzing credit risk has little research significance and consumes computing resources. Therefore, in order to improve the efficiency and accuracy of data processing, all the obtained indicators can be screened first.

[0076] Specifically, determining at least one indicator based on at least one industry includes: obtaining an indicator corresponding to each industry in at least one industry; screening out at least one indicator from the indicator, wherein the correlation between each indicator in the at least one indicator and the profit margin of the industry corresponding to each indicator is greater than a threshold.

[0077] It is understandable that since credit risk is usually related to the economics of various industries, indicators with strong correlation with industry profit margins can be screened out.

[0078] For example, based on the monthly industry data on the website of the National Bureau of Statistics, with the profit margin of each industry as the dependent variable and the following indicators of each industry as independent variables, an xgboost model is established to screen out variables that are strongly correlated with industry profit margins as the analysis object of credit risk.

[0079] It is understandable that the independent variable value range of the xgboost model established for each industry is different. Taking the industrial industry as an example, according to the industry data of the National Bureau of Statistics, the independent variables of the industrial industry include: industrial producer purchase price index, industrial producer ex-factory price index, production materials price index and other factors closely related to supply and demand. In addition, the independent variables of the industrial industry also include product output, inventory, various expenses, etc.

[0080] The independent variables of the industries listed above can be filtered according to the xgboost model to obtain only the indicators that are strongly correlated with the industry profit margin.

[0081] S104. Determine and output at least one information according to at least one indicator.

[0082] Therein, at least one indicator corresponds one-to-one to at least one information, and the information is used to indicate the credit risk of the first financial institution.

[0083] Exemplarily, by determining and outputting the credit risk of the first financial institution corresponding to each indicator, the impact of each indicator on the credit risk of the first financial institution can be determined, which facilitates subsequent credit risk management and control.

[0084] The size of credit risk can be reflected through various indicator data, such as the non-performing loan rate mentioned above, and can also include the lag effect.

[0085] It is understandable that the exposure of credit risk of financial institutions (such as banks) has a lag effect on some risk factors (i.e., target indicators), that is, at least one current indicator will not immediately affect credit risk (such as non-performing loan rate), but may have an impact on credit risk after a period of time. Therefore, studying the lag effect of risk factors (i.e., one or more indicators) is particularly important for early warning of financial risks.

[0086] Exemplarily, taking the first financial institution as a bank and the at least one information including a non-performing loan ratio and / or a lag period as an example, the at least one information may be determined according to the at least one indicator in the following manner.

[0087] Obtain at least one indicator obtained in the above step. Obtain monthly data for each indicator, that is, a series of monthly time series data can be obtained for each indicator. Each indicator is separately and separately used with the bank's current monthly non-performing loan rate to establish a lag model to determine the lag period of each indicator.

[0088] Specifically, the formula example of the distributed lag model is as follows:

[0089] Y t =α+β0X t +β1X t-1 +β2Xt-2 +…+β k X t-k +u t

[0090] In the distributed lag model, each coefficient reflects the different degrees of influence of each lagged value of the explanatory variable x (i.e., the target indicator) on the explained variable y (i.e., the non-performing loan rate), which is usually referred to as the multiplier effect. t The coefficient is called the short-term multiplier or the spot multiplier, which indicates the average impact of a unit change in the current period's independent variable x (i.e., the target indicator) on the dependent variable y (i.e., the current non-performing loan rate). The establishment of a distributed lag model can determine the number of periods in which the independent variable has a lag effect on the dependent variable. The weighted average of the independent variable coefficients in different periods in the model is the contribution ratio of the independent variables in different periods to the lag effect.

[0091] In the embodiment of the present application, the explanatory variable x and the explained variable y are both monthly data (i.e., monthly data). If the order of the explanatory variable x is first order, it means that the lag period is one month. If the order of x is second order, it means that the lag period is two months, and so on.

[0092] In this way, we can obtain the lag period of each indicator on the bank's non-performing loan ratio, as well as the impact of the indicator on the current bank's non-performing loan ratio in each period.

[0093] The calculation principle for the distributed lag model is:

[0094] First, determine the lag period. You can use methods such as calculating the correlation coefficient, calculating the determination coefficient, Schwartz criterion, Akaike criterion, etc. to determine the optimal lag period.

[0095] For example, the optimal lag period is the lag period of the indicator to the bank's non-performing loan ratio.

[0096] Then, the model is estimated by empirical weighting method, Almon polynomial method, etc. to obtain α, β0, β i The value of

[0097] Next, the obtained distributed lag model is verified and estimated using the regression equation or regression coefficient;

[0098] Finally, the hysteresis effect is analyzed.

[0099] For example, β0 is the short-term multiplier, which represents the impact of a one-unit change in the explanatory variable (i.e., the target indicator) on the explained variable (i.e., the non-performing loan rate) in the same period, i.e., the short-term impact.

[0100] β i(i>0) is the extension multiplier or dynamic multiplier, which reflects the impact of a one-unit change in the explanatory variable (i.e., the target indicator) in each lag period on the explained variable (i.e., the non-performing loan rate), that is, the lagged impact.

[0101] It is the (n-period) medium-term multiplier, reflecting the cumulative impact of a one-unit change in the explanatory variable (i.e., the target indicator) in each lag period on the explained variable (i.e., the non-performing loan ratio) over n periods, where n is a positive integer.

[0102] It is a long-term multiplier, reflecting the cumulative total impact of a one-unit change in the explanatory variable (i.e., the target index) on the explained variable (i.e., the non-performing loan ratio) in each lag period.

[0103] That is, the lag period and impact degree of each indicator on the non-performing loan rate can be determined based on the various parameters obtained.

[0104] In this implementation method, since the credit risk of the first financial institution is strongly correlated with the industry into which the credit flows, and the industry concentration of customers of different financial institutions is also different, at least one industry (i.e., industry) related to the credit risk of the first financial institution is screened out from the industry into which the credit of the first financial institution flows, and then at least one indicator is determined based on at least one industry, so that the indicator related to the credit risk of the first financial institution can be obtained, and then the credit risk of the first financial institution can be evaluated based on the indicator, which can improve the accuracy of the credit risk assessment.

[0105] In a possible design, the characteristic information of the first financial institution also includes the region where the first financial institution is located, and the method may further include:

[0106] Determining one or more indicators based on the characteristic information of the first financial institution, including: determining at least one of the gross domestic product (GDP), inflation rate (CPI), unemployment rate, money supply, fiscal deficit, public external debt, and trade balance of the region where the first financial institution is located based on the region where the first financial institution is located;

[0107] At least one information is determined and outputted according to the at least one item.

[0108] Specifically, the region where the first financial institution is located can be a national scope, such as China, South Korea, Russia, etc., or it can be a specific provincial level, such as Fujian Province, China, Guangdong Province, China, etc., and it can also be refined to a specific city or county level or even district, such as Guangzhou City, Guangdong Province, China, Qingyang District, Chengdu City, Sichuan Province, China, etc. It can be determined based on the specific circumstances of the actual financial institution to be analyzed, and the embodiments of the present application do not limit this.

[0109] It is understandable that if the same national macroeconomic indicators are used to conduct credit risk assessment on various financial institutions, the assessment results obtained cannot accurately reflect the specific credit risk size of each financial institution. However, using the macroeconomic indicators of the region where each financial institution is located can better reflect the emergency situation of the region where each financial institution is located, and then analyze the relationship between the credit risk of each financial institution and the macroeconomic indicators of the region where each financial institution is located, so that the credit risk assessment results obtained are more accurate and reliable.

[0110] Similarly, the method in S104 above may be used to calculate the at least one information of the at least one item, which will not be described in detail herein.

[0111] In a possible design, the characteristic information of the first financial institution further includes the type of the first financial institution; the first financial institution is a bank; and the method further includes:

[0112] Determine the interest rate of the bank based on the type of bank;

[0113] Output a message based on the interest rate.

[0114] Exemplarily, taking the first financial institution being a bank as an example, the types of the first financial institution (i.e., bank) may include at least one of a central bank, a policy bank, a state-owned commercial bank, a national joint-stock commercial bank, a city commercial bank, a rural credit cooperative, a rural commercial bank, a village bank, a cooperative bank, an investment bank, the World Bank, and a foreign bank; or, each type may be further divided, for example, the state-owned commercial banks include the Industrial and Commercial Bank of China, the Agricultural Bank of China, the Bank of China, the China Construction Bank, the Bank of Communications, the Postal Savings Bank of China, etc., and each state-owned commercial bank may be regarded as a type. The above is only one possible example, and other division methods may actually be used.

[0115] It is understandable that if the first financial institution is a bank, there is also a strong correlation between the bank's interest rate and credit risk, and different types of banks have different interest rates, so the interest rate of the bank can be obtained according to the specific type of the bank. In this way, the interest rate of the bank is used as an indicator of the bank, so that the indicator can more accurately reflect the situation of the bank itself, thereby improving the accuracy and reliability of subsequent risk assessment of the bank.

[0116] The above are only possible examples. In practice, the characteristic information of the first financial institution may also be used as an indicator of the financial institution, and the embodiments of the present application do not limit this.

[0117] Similarly, the information corresponding to the interest rate may be calculated using the method in S104 above, which will not be described in detail here.

[0118] In a possible design, the embodiment of the present application further provides a method for evaluating the credit risks of multiple financial institutions, including:

[0119] Divide multiple financial institutions into one or more sets according to their characteristic information, each set includes financial institutions corresponding to the same characteristic information, and the multiple financial institutions include the first financial institution; determine at least one indicator based on the characteristic information corresponding to each set, and the determined at least one indicator corresponds to each financial institution in each set.

[0120] Exemplarily, multiple financial institutions may be divided into different groups according to their different regions and types. Each group includes financial institutions of the same type and region. Steps S101 to S104 are performed in each group. One or more indicators of the group are determined as a whole. Based on the one or more indicators of each group, one or more information reflecting the credit risk of the group is determined.

[0121] In this way, the characteristic information of the financial institutions in each set is the same, which facilitates credit risk assessment for each set, improves the efficiency of risk assessment, and facilitates the display of the overall credit risk size of financial institutions in the same region and / or the same type.

[0122] It can be understood that the above-mentioned way of dividing the set is only a possible example. The division can be based only on the region where the financial institution is located, the type of financial institution, or the industry into which the financial institution's credit flows, etc., or the characteristic information of the above-mentioned financial institutions can be freely combined, and other characteristic information such as the popularity of the financial institution, the number of branches, etc. can also be used for division. The embodiments of the present application do not impose any restrictions on this.

[0123] The method provided by the embodiment of the present application is introduced above, and the device provided by the embodiment of the present application is introduced below.

[0124] Based on the same technical concept, an embodiment of the present application provides a data processing device, which includes a module / unit / means for executing the method executed by the electronic device with processing capability in the above method embodiment. The module / unit / means can be implemented by software, or by hardware, or the corresponding software can be implemented by hardware.

[0125] For example, Figure 2 As shown, the apparatus 200 may include:

[0126] The acquisition module 201 is used to: acquire characteristic information of the first financial institution; the characteristic information includes the industry to which the credit of the first financial institution flows;

[0127] The processing module 202 is used to: determine at least one industry associated with the credit risk of the first financial institution based on the characteristic information; determine at least one indicator based on the at least one industry; wherein each industry in the at least one industry corresponds to one or more indicators in the at least one indicator; determine at least one information based on the at least one indicator, wherein the at least one indicator corresponds to the at least one information in a one-to-one manner, and the information is used to indicate the credit risk of the first financial institution;

[0128] The output module 203 is used to output at least one information.

[0129] It should be understood that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0130] Based on the same technical concept, see Figure 3 The embodiment of the present application further provides an electronic device 300, including:

[0131] At least one processor 301; and a communication interface 303 that is communicatively connected to the at least one processor 301; the at least one processor 301 executes instructions stored in the memory 302, so that the electronic device 300 executes the method steps performed by the billboard in the above method embodiment through the communication interface 303.

[0132] Optionally, the memory 302 is located outside the electronic device 300 .

[0133] Optionally, the electronic device 300 includes the memory 302, the memory 302 is connected to the at least one processor 301, and the memory 302 has instructions that can be executed by the at least one processor 301. Figure 3 The dashed lines indicate that the memory 302 is optional for the electronic device 300 .

[0134] The at least one processor 301 and the memory 302 may be coupled via an interface circuit or may be integrated together, which is not limited here.

[0135] The specific connection medium between the at least one processor 301, the memory 302 and the communication interface 303 is not limited in the embodiment of the present application. Figure 3 In the embodiment, at least one processor 301, a memory 302 and a communication interface 303 are connected via a bus 304. Figure 3 The connection between other components is only for schematic illustration and is not intended to be limiting. The bus part may be an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 It is represented by only one thick line, but it does not mean that there is only one bus or one type of bus.

[0136] It should be understood that the processor mentioned in the embodiments of the present application can be implemented by hardware or by software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc. When implemented by software, the processor can be a general-purpose processor implemented by reading software code stored in a memory.

[0137] Exemplarily, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0138] It should be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both a volatile memory and a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which acts as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (DirectRambus RAM, DR RAM).

[0139] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, the memory (storage module) can be integrated into the processor.

[0140] It should be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0141] Based on the same technical concept, an embodiment of the present application also provides a computer-readable storage medium, which is used to store instructions. When the instructions are executed, the computer executes the method steps executed by any device in the above method embodiments.

[0142] Based on the same technical concept, an embodiment of the present application also provides a computer program product, including computer program code. When the computer program code is executed on a computer, the method steps executed by any device in the above method embodiment are implemented.

[0143] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0144] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0145] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0146] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0147] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A data processing method, characterized in that: include: Obtaining characteristic information of the first financial institution; The characteristic information includes the industry to which the credit of the first financial institution flows; Determine at least one industry associated with the credit risk of the first financial institution based on the characteristic information; Determine at least one indicator according to the at least one industry, wherein each industry in the at least one industry corresponds to one or more indicators in the at least one indicator; At least one information is determined and outputted according to the at least one indicator, the at least one indicator corresponds to the at least one information in a one-to-one manner, and the information is used to indicate the credit risk of the first financial institution.

2. The method according to claim 1, characterized in that The determining of at least one indicator according to the at least one industry comprises: Obtain all indicators for each industry in the at least one industry; At least one indicator is selected from all the indicators, and the correlation between each indicator in the at least one indicator and the profit margin of the industry corresponding to each indicator is greater than a threshold.

3. The method according to claim 1, characterized in that The characteristic information also includes the region where the first financial institution is located; The method further comprises: Determine at least one of the gross domestic product (GDP), inflation rate (CPI), unemployment rate, money supply, fiscal deficit, public external debt, and trade balance of the region where the first financial institution is located according to the region where the first financial institution is located; At least one of the information is determined and outputted according to the at least one item.

4. The method according to claim 1, characterized in that The characteristic information includes the type of the first financial institution; the first financial institution is a bank; The method further comprises: determining the interest rate of said bank according to the type of said bank; The information is determined and outputted based on the interest rate.

5. The method according to claim 1, characterized in that The at least one industry includes an industrial industry, and determining at least one indicator according to the at least one industry includes: At least one of the industrial producer purchase price index, industrial producer ex-factory price index, means of production price index, product output and inventory of the industrial industry is determined according to the industrial industry.

6. The method according to claim 1, characterized in that The at least one industry includes the real estate industry, and determining at least one indicator according to the at least one industry includes: Determine at least one of the real estate industry's commercial housing sales area, real estate construction area, real estate completion area, and actual real estate development investment in the real estate industry based on the real estate industry.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: dividing a plurality of financial institutions into one or more sets according to the characteristic information of the plurality of financial institutions, each set including financial institutions corresponding to the same characteristic information, the plurality of financial institutions including the first financial institution; At least one indicator is determined according to the characteristic information corresponding to each set, and the determined at least one indicator corresponds to each financial institution in each set.

8. A data processing device, characterized in that: include: An acquisition module, used to: acquire characteristic information of the first financial institution; The characteristic information includes the industry to which the credit of the first financial institution flows; A processing module, configured to: determine at least one industry associated with the credit risk of the first financial institution according to the characteristic information; determine at least one indicator according to the at least one industry, wherein each industry in the at least one industry corresponds to one or more indicators in the at least one indicator; determine at least one information according to the at least one indicator, wherein the at least one indicator corresponds to the at least one one-to-one, and the information is used to indicate the credit risk of the first financial institution; An output module is used to output the at least one information.

9. An electronic device, characterized in that: include: A memory for storing program instructions; A processor is used to call the program instructions stored in the memory, and execute the steps included in the method according to any one of claims 1 to 7 according to the obtained program instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to have a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the method according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that The computer program product comprises: a computer program code, and when the computer program code is run on a computer, the computer is enabled to execute the method according to any one of claims 1 to 7.

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