CN108711004A - Methods of risk assessment and device and computer readable storage medium - Google Patents
Methods of risk assessment and device and computer readable storage medium Download PDFInfo
- Publication number
- CN108711004A CN108711004A CN201810453569.1A CN201810453569A CN108711004A CN 108711004 A CN108711004 A CN 108711004A CN 201810453569 A CN201810453569 A CN 201810453569A CN 108711004 A CN108711004 A CN 108711004A
- Authority
- CN
- China
- Prior art keywords
- user
- information point
- evaluated
- risk
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000012502 risk assessment Methods 0.000 title claims abstract description 37
- 238000003860 storage Methods 0.000 title claims abstract description 14
- 230000006399 behavior Effects 0.000 claims description 23
- 238000004590 computer program Methods 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000011156 evaluation Methods 0.000 claims description 8
- 238000005259 measurement Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 claims description 3
- 230000003449 preventive effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 15
- 230000006870 function Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 238000009826 distribution Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Technology Law (AREA)
- Finance (AREA)
- Educational Administration (AREA)
- Accounting & Taxation (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
A kind of methods of risk assessment of disclosure proposition and device and computer readable storage medium, are related to risk assessment field.Method therein includes：Determine the set of information point；For any one information point to be assessed in set, the Financial Information for the user for having usage behavior to information point to be assessed is obtained；According to the Financial Information for the user for having usage behavior to information point to be assessed, the value of the risk indicator of information point to be assessed is calculated；According to the value of the risk indicator of information point to be assessed, the possibility for information point to be assessed occurring financial risks is assessed.The disclosure has the Financial Information of the user of usage behavior according to information point and to information point, and the possibility for information point occurring financial risks is assessed, to play certain preventive effect to financial risks.
Description
Technical Field
The present disclosure relates to the field of risk assessment, and in particular, to a risk assessment method and apparatus, and a computer-readable storage medium.
Background
Financial businesses face a number of financial risks such as credit risks, fraud risks, cash-outs, etc. Preventing financial risks is an important issue of great concern for financial services institutions.
Disclosure of Invention
The embodiment of the disclosure provides a financial risk assessment scheme, which can assess the possibility that financial risks occur to information points, thereby playing a certain precaution role on the financial risks.
According to an aspect of the present disclosure, a risk assessment method is provided, including:
determining a set of information points;
acquiring financial information of a user having a use behavior on any information point to be evaluated in the set;
calculating the value of the risk index of the information point to be evaluated according to the financial information of the user having the use behavior on the information point to be evaluated;
and according to the value of the risk index of the information point to be evaluated, evaluating the possibility of financial risk of the information point to be evaluated.
Optionally, the information points in the set are determined according to a receiving address of the user.
Optionally, when the plurality of user shipping addresses correspond to any one information point in the set, the distances between the plurality of user shipping addresses and the information point reference addresses are calculated, and the user shipping addresses with small distances in a preset range are selected to be used for determining the corresponding information points.
Optionally, the risk indicator includes a user type risk indicator, and calculating a value of the user type risk indicator of the information point to be evaluated includes:
calculating first use credibility of a first user on the information point to be evaluated, wherein the first user is any user having use behaviors on the information point to be evaluated;
calculating the sum of the use credibility of all the information points used by the first user;
determining the weight of the first user according to the proportion information of the first use reliability and the sum of the use reliabilities;
obtaining a value of a financial index associated with the user-type risk index for the first user;
and calculating the value of the user type risk index of the information point to be evaluated according to the weight of each first user and the values of the financial indexes related to the user type risk indexes of all the first users.
Optionally, calculating the value of the user type risk indicator of the information point to be evaluated includes:
carrying out weighted summation operation on credit measurement information of all the first users when applying for financial services by using the weight of each first user to obtain the value of the A card weighted risk index of the information point to be evaluated;
or, performing weighted summation operation on the risk measurement information of all the first users after participating in the financial activities by using the weight of each first user to obtain the value of the B-card weighted risk index of the information point to be evaluated;
or, under the condition that the user type risk index is a user weighted proportion index, the financial index related to the user weighted proportion index indicates whether the first user is a preset type user, and according to the weight of each first user, a preset type user and all first users are subjected to weighted proportion operation to obtain the value of the user weighted proportion index of the information point to be evaluated, wherein the preset type user includes at least one of the following: blacklisted users, overdue payment users, first order failed users, fraudulent users, pre-credited users, high quality users, low stability users.
Optionally, calculating the first usage credibility of the first user for the information point to be evaluated includes:
and determining the first use reliability of the first user on the information point to be evaluated according to the stability of the first user on the information point to be evaluated and the life cycle of the information point to be evaluated and in combination with the use degree of the first user on the information point to be evaluated.
Optionally, the risk indicator includes an address type risk indicator, and calculating a value of the address type risk indicator of the information point to be evaluated includes:
calculating a risk metric value of the information point to be evaluated as a high risk address point according to the category of the information point to be evaluated and the value of the commodity related to the financial payment overdue on the information point to be evaluated;
or calculating the information point to be evaluated as the risk metric value of the blacklist address point according to the distance between the information point to be evaluated and the blacklist address point.
Optionally, the method further comprises: and taking the evaluation result of the financial risk possibly occurring on the information point to be evaluated as a reference factor to evaluate the possibility of the financial risk occurring on the user using the information point to be evaluated.
According to still another aspect of the present disclosure, there is provided a risk assessment apparatus including:
the information point determining module is used for determining a set of information points;
the financial information acquisition module is used for acquiring the financial information of a user having a use behavior on any information point to be evaluated in the set;
the risk index calculation module is used for calculating the value of the risk index of the information point to be evaluated according to the financial information of the user having the use behavior on the information point to be evaluated;
and the risk evaluation module is used for evaluating the possibility of financial risk of the information point to be evaluated according to the value of the risk index of the information point to be evaluated.
Optionally, the information point determining module is configured to determine the set of information points according to a receiving address of the user.
Optionally, the information point determining module is configured to calculate distances between the multiple user shipping addresses and the information point reference addresses under the condition that the multiple user shipping addresses correspond to any one information point in the set, and select a user shipping address with a small distance within a preset range to determine the corresponding information point.
Optionally, the risk indicator includes a user type risk indicator, and the risk indicator calculating module is configured to calculate a value of the user type risk indicator of the information point to be evaluated, and includes:
calculating first use credibility of a first user on the information point to be evaluated, wherein the first user is any user having use behaviors on the information point to be evaluated;
calculating the sum of the use credibility of all the information points used by the first user;
determining the weight of the first user according to the proportion information of the first use reliability and the sum of the use reliabilities;
obtaining a value of a financial index associated with the user-type risk index for the first user;
and calculating the value of the user type risk index of the information point to be evaluated according to the weight of each first user and the values of the financial indexes related to the user type risk indexes of all the first users.
Optionally, when calculating the first usage reliability of the first user on the information point to be evaluated, the risk indicator calculation module is configured to:
and determining the first use reliability of the first user on the information point to be evaluated according to the stability of the first user on the information point to be evaluated and the life cycle of the information point to be evaluated and in combination with the use degree of the first user on the information point to be evaluated.
Optionally, the risk indicator includes an address type risk indicator, and the risk indicator calculating module is configured to calculate a value of the address type risk indicator of the information point to be evaluated, and includes:
calculating a risk metric value of the information point to be evaluated as a high risk address point according to the category of the information point to be evaluated and the value of the commodity related to the financial payment overdue on the information point to be evaluated;
or calculating the information point to be evaluated as the risk metric value of the blacklist address point according to the distance between the information point to be evaluated and the blacklist address point.
Optionally, the risk assessment module is further configured to use an assessment result that the financial risk may occur in the information point to be assessed as a reference factor to assess a possibility that the financial risk may occur in a user using the information point to be assessed.
According to still another aspect of the present disclosure, there is provided a risk assessment apparatus including:
a memory; and
a processor coupled to the memory, the processor configured to perform the risk assessment method of any of the preceding embodiments based on instructions stored in the memory.
According to yet another aspect of the present disclosure, a computer-readable storage medium is proposed, on which a computer program is stored, which when executed by a processor implements the risk assessment method of any of the preceding embodiments.
The method and the device evaluate the possibility of financial risk of the information point according to the information point and the financial information of the user who uses the information point, thereby playing a certain precaution role on the financial risk.
Drawings
The drawings that will be used in the description of the embodiments or the related art will be briefly described below. The present disclosure will be more clearly understood from the following detailed description, which proceeds with reference to the accompanying drawings,
it is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without undue inventive faculty.
Fig. 1 is a schematic flow diagram of some embodiments of a risk assessment method of the present disclosure.
Fig. 2 is a schematic flow chart illustrating a process of calculating a value of a user type risk indicator of an information point to be evaluated according to the present disclosure.
Fig. 3 is an example of a risk profile of the present disclosure.
Fig. 4 is a schematic structural diagram of some embodiments of a risk assessment device of the present disclosure.
FIG. 5 is a schematic structural diagram of another embodiment of the risk assessment device of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure.
Fig. 1 is a schematic flow diagram of some embodiments of a risk assessment method of the present disclosure.
As shown in fig. 1, the method of this embodiment includes: 110 to 140.
In step 110, a set of information points is determined.
A Point of Information (POI) is a landmark in a geographic Information system. An information point may be, for example, a sight (e.g., a park, a historic site, etc.), a commercial establishment (department store, supermarket, restaurant, hotel, hospital, etc.), a transportation facility (e.g., a station, a parking lot, etc.), a government office, etc., but is not limited to the examples given.
The information point has description information. The description information of the information point may include, for example: name, category (e.g., home, business, attraction, etc.), location area (e.g., province, city, district, or county), location coordinates (e.g., longitude and latitude), and the like. According to the description information of the information points, a unique information point can be positioned, so that the uniqueness of the information points is guaranteed.
In step 120, for any information point to be evaluated in the set, financial information of a user having a use behavior of the information point to be evaluated is acquired.
The usage behavior of the information point by the user includes, for example: the user purchases the item using the information point as a shipping address.
The financial information of the user includes, for example: whether to grant credit, whether to grant credit in advance, whether to activate, number of overdue days, historical maximum number of overdue days, amount owed, whether to have a ticket failed, whether to be fraudulent, whether to be blacklisted, etc., but not limited to the examples given.
In step 130, a value of a risk indicator of the information point to be evaluated is calculated according to financial information of a user having a usage behavior of the information point to be evaluated.
According to business needs, risk indicators can be preset. The risk indicator may be one or more. In general, multiple risk indicators may be set for more comprehensive assessment of financial risk.
In step 140, the probability of financial risk occurring at the information point to be evaluated is evaluated according to the value of the risk indicator of the information point to be evaluated.
The evaluation result of the financial risk possibly occurring at the information point to be evaluated can be used as a reference factor for evaluating the possibility of the financial risk occurring at the user using the information point to be evaluated.
According to the information point and the financial information of the user who uses the information point, the probability of financial risk occurring to the information point is evaluated, and therefore the financial risk is prevented to a certain extent.
With respect to step 110, some embodiments of the present disclosure also propose a method of determining a set of information points. The method takes a user receiving place as a data source for extracting the information points, and determines a set of the information points according to a user receiving address. The data source is more real and efficient, and therefore, the information points extracted based on the data source are also more real and efficient.
In some embodiments, determining the set of information points from the user shipping address comprises: firstly, performing word segmentation processing on a receiving address of a user to obtain location area information such as a name, a province, a city, a district or a county and the like, and category information such as a residential district or an office building; then classifying the user receiving addresses after word segmentation, for example, classifying the user receiving addresses belonging to the same cell or the same office building; and finally, determining each category obtained by the division as an information point.
In some embodiments, when there are a plurality of user shipping addresses in a category, that is, when a plurality of user shipping addresses correspond to one information point, the distances between the plurality of user shipping addresses and the information point reference address are calculated, and the user shipping address having a small distance within a preset range is selected to be used for determining the corresponding information point. Thereby guaranteeing the validity of the information point.
The information point reference address may be, for example: the user's shipping address in the middle area is selected from the plurality of user's shipping addresses, or the address of the information point in the electronic map is preliminarily determined based on the plurality of user's shipping addresses, but is not limited to the illustrated example.
The receiving address of the user whose distance is small within the preset range may be determined by means of a quantile, for example. For example, pick customer shipping addresses within a 90 quantile distance. The user's shipping address whose distance is small to the extent within the preset range may also adopt, for example, a distance threshold value determination method. For example, pick a customer shipping address that is within a preset distance threshold.
Some e-commerce platforms can provide both goods delivery functions and financial services, such as "pay-first-use" financial services, based on the shipping address. Thus, in some embodiments, at step 110, the set of information points may be determined from the customer shipping address recorded by the e-commerce platform, and at step 120, the financial information of the customer having the usage behavior of the information point to be evaluated may be obtained from the customer and his financial information recorded by the e-commerce platform.
In some embodiments, basic data such as a user's shipping address and financial information of the user collected from the e-commerce platform may be preprocessed to improve the effectiveness of the basic data. For example, considering that the order of the e-commerce platform is various, some orders related to virtual products do not need to be delivered by a courier at home, and the validity of the customer shipping address of such orders cannot be considered, so the customer shipping address of the order of the non-virtual product completed within a preset time (e.g., within one year) can be selected. In order to ensure that the financial information of the user is obtained, an order with the actual payment amount larger than 0 is selected. In addition, abnormal values in the basic data can be removed, data which are smaller than a first quantile threshold value (such as 2.5%) and larger than a second quantile threshold value (such as 97.5%) in the basic data are cut off, and data between 2.5% and 97.5% are used for subsequent risk assessment.
With respect to step 130, the risk indicators include, for example, a user type risk indicator and an address type risk indicator.
In some embodiments, as shown in fig. 2, calculating the value of the user-type risk indicator for the information point to be evaluated comprises: 210-250.
In step 210, a first usage reliability of the information point to be evaluated by a first user is calculated, wherein the first user is any user who has a usage behavior of the information point to be evaluated, and the "first" is not used to indicate a size or a time sequence.
In some embodiments, calculating a first usage trustworthiness of the first user for the information point to be evaluated comprises: and determining the first use reliability of the first user on the information point to be evaluated by a method of carrying out weighted summation calculation on the related parameters according to the stability of the first user on the information point to be evaluated and the life cycle of the information point to be evaluated and the use degree of the first user on the information point to be evaluated. Examples of parameters and their weights are shown in the following table:
TABLE 1
As shown in table 1, the weighted summation operation is performed on the three primary parameters according to their respective weights, so as to obtain the first use reliability of the first user on the information point to be evaluated, and the larger the value of the first use reliability is, the more reliable the behavior of the user using the information point to be evaluated is.
In addition, the value of the primary parameter can be calculated according to the following secondary parameters. For example, the stability of the information point to be evaluated by the first user can be calculated by a weighted sum operation method according to at least one of the following four secondary parameters (i.e., the number of days the first user places the information point, the number of days the first user has abandoned the information point, the total number of times the user places the information point, and the amount of money consumed by the user to use the information point). The life cycle of the information point to be evaluated can be calculated according to the following two secondary parameters (namely, the total number of orders placed by the information point and the number of orders placed by the information point) according to the formula 1.
Wherein,the poi _ life represents the life cycle of the information point to be evaluated, p represents the life cycle of the information point to be evaluated, order _ num represents the total number of orders placed for the information point, pin _ num represents the number of orders placed for the information point, n0Representing a preset order threshold. According to equation 1, human-average n0The life cycle of more than one information point is normalized to 1.
Wherein,weight represents the usage degree of the information point to be evaluated by the first user, order _ num represents the total ordering number of the information point, n0Representing a preset order threshold. According to formula 2, n is passed0The degree of use of more than one information point is normalized to 1.
In step 220, the sum of the usage reliabilities of all the information points used by the first user is calculated.
The calculation method using reliability refers to the aforementioned first calculation method using reliability, and is not described herein again.
In step 230, a weight of the first user is determined based on the ratio information of the first usage confidence level and the sum of the usage confidence levels.
At step 240, a value of a financial index associated with a user-type risk index of the first user is obtained.
Examples of user type risk indicators and their associated financial indicators are shown in table 2:
TABLE 2
The low-stability user refers to a user with stability lower than a preset threshold. The high-quality users are the category information of the information points used by the users, and the users using the information points such as government organs, national enterprises and public institutions are considered to belong to the high-quality users, so that the probability of financial risks of the users is low.
In step 250, the value of the user type risk indicator of the information point to be evaluated is calculated according to the weight of each first user and the values of the financial indicators related to the user type risk indicators of all the first users.
In some embodiments, the weighting summation operation is performed on the credit measurement information of all the first users when applying for the financial service by using the weight of each first user, so as to obtain the value of the a-card weighted risk indicator of the information point to be evaluated.
In some embodiments, the weighted sum operation is performed on the risk measurement information of all the first users after participating in the financial activity by using the weight of each first user, so as to obtain the value of the B-card weighted risk indicator of the information point to be evaluated.
In some embodiments, when the user type risk indicator is a user weighted proportion indicator, as in indexes 3 to 10 in table 2, a financial indicator related to the user weighted proportion indicator indicates whether the first user is a preset type of user, and according to the weight of each first user, a weighted proportion operation is performed on the preset type of user and all first users to obtain a value of the user weighted proportion indicator of the information point to be evaluated. Wherein the preset type of user comprises at least one of the following: blacklisted users, overdue payment users, first order failed users, fraudulent users, pre-credited users, high quality users, low stability users.
In some embodiments, the address type risk indicators include, for example: high risk address risk indicator, blacklist address risk indicator.
For the high risk address risk index, calculating the value of the address type risk index of the information point to be evaluated comprises the following steps: and calculating the risk metric value of the information point to be evaluated as the high-risk address point according to the category of the information point to be evaluated and the value of the commodity related to the financial payment overdue on the information point to be evaluated.
For example, for a residential type information point, if the amount of a commodity whose payment is overdue is greater than 500 yuan, the information point is considered as a risk address point, and the longer the overdue is, the larger the amount of the commodity is, the higher the risk of the information point is, and the larger the corresponding risk metric value is. For the information point of the shop type, if the commodity amount of payment overdue on the information point is larger than 10000 yuan, the information point is considered as a risk address point, and the longer the overdue is, the larger the commodity amount is, the higher the risk of the information point is, and the larger the corresponding risk metric value is. The numbers given and illustrated are examples.
Aiming at the blacklist address risk index, calculating the value of the address type risk index of the information point to be evaluated comprises the following steps: and calculating the risk metric value of the information point to be evaluated as the blacklist address point according to the distance between the information point to be evaluated and the blacklist address point. The closer the information points are to the blacklist address points, the greater the likelihood of their being blacklist address points, and the greater the corresponding risk metric value.
An exemplary method for calculating a risk metric using an information point as a blacklist address point is as follows:
wherein x represents the distance between the information point and the address point of the blacklist, and y represents the risk metric value of the information point as the address point of the blacklist.
Regarding step 140, if there are multiple risk indicators of the information point to be evaluated, a weighted summation operation is performed on the values of the risk indicators according to the preset weight of each risk indicator, and the operation result is used as an evaluation value of the financial risk that may occur in the information point.
In some embodiments, the risk indicator for the information point is determined according to the type of users having usage behavior for the information point, e.g. whether users of the type "pay-first-consumption" are included, and users of the type "pay-first-consumption" and users of non-type may select different risk indicators. Table 3 gives examples of risk indicators selected by "pay-before-consume" type users and non-type users.
TABLE 3
The determination method of the set of information points, the acquisition method of the financial information of the user having the use behavior of the information points, the construction method of the risk index of the information points, and the evaluation method of the financial risk that may occur in the information points, which are related to the steps 110 to 140, all belong to the contents of a financial risk evaluation model.
The disclosure also provides an assessment method for the financial risk assessment model. The assessment method assesses the financial risk assessment model in terms of both stability and discriminative power. Stability is used to gauge the usability of the financial risk assessment model. Discriminative power is used to measure the discriminative power of the financial risk assessment model for risk.
The stability was determined as follows:
wherein psi represents a measure of stability of the financial risk assessment model, and if psi is less than a predetermined value (e.g., 1%), the financial risk assessment model is considered stable, Ri(T) represents the proportion of i-th risk users counted in the Tth period, Ri(T-1) represents the proportion of the i-th risk users counted in the T-1 th period.
The determination method of the distinguishing capability comprises the following steps: and drawing a risk distribution graph of the estimated value of the financial risk possibly occurring on the information points and the user proportion, wherein the number of peaks in the distribution graph can represent the distinguishing capability of the financial risk assessment model. As shown in fig. 3, the risk distribution diagram has three peaks with horizontal and vertical coordinates of "the estimated value of the information point where the financial risk is likely to occur" and "the user ratio", respectively, corresponding to three user groups of low risk, medium risk and high risk.
Fig. 4 is a schematic structural diagram of some embodiments of a risk assessment device of the present disclosure.
As shown in FIG. 4, the risk assessment device includes modules 410-440.
An information point determination module 410 for determining a set of information points.
The financial information obtaining module 420 is configured to obtain, for any information point to be evaluated in the set, financial information of a user having a use behavior of the information point to be evaluated.
And the risk index calculation module 430 is configured to calculate a value of a risk index of the information point to be evaluated according to the financial information of the user having the usage behavior of the information point to be evaluated.
And the risk evaluation module 440 is configured to evaluate the possibility that the financial risk occurs to the information point to be evaluated according to the value of the risk indicator of the information point to be evaluated.
In some embodiments, the spot determination module 410 is configured to determine the set of spots based on the customer shipping address.
In some embodiments, the information point determining module 410 is configured to, in the case of any one information point in the corresponding set of the plurality of user shipping addresses, calculate distances between the plurality of user shipping addresses and the information point reference address, and select a user shipping address with a small distance within a preset range to be used to determine the corresponding information point.
In some embodiments, the risk indicator includes a user type risk indicator, and the risk indicator calculating module 430 is configured to calculate a value of the user type risk indicator of the information point to be evaluated, and includes: calculating the first use credibility of a first user on the information point to be evaluated, wherein the first user is any one user with use behaviors on the information point to be evaluated; calculating the sum of the use credibility of the first user to all the information points used by the first user; determining the weight of the first user according to the first use reliability and the proportion information of the sum of the use reliabilities; obtaining a value of a financial index related to a user type risk index of a first user; and calculating the value of the user type risk index of the information point to be evaluated according to the weight of each first user and the values of the financial indexes related to the user type risk indexes of all the first users.
In some embodiments, the risk indicator calculation module 430, when calculating the first user confidence level of use of the information point to be evaluated, is configured to: and determining the first use reliability of the first user on the information point to be evaluated according to the stability of the first user on the information point to be evaluated and the life cycle of the information point to be evaluated and in combination with the use degree of the first user on the information point to be evaluated.
In some embodiments, the risk indicator includes an address type risk indicator, and the risk indicator calculating module 430 is configured to calculate a value of the address type risk indicator of the information point to be evaluated, including:
calculating a risk metric value of the information point to be evaluated as a high risk address point according to the category of the information point to be evaluated and the value of the commodity related to the financial payment overdue on the information point to be evaluated;
or, calculating the information point to be evaluated as the risk metric value of the blacklist address point according to the distance between the information point to be evaluated and the blacklist address point.
In some embodiments, the risk assessment module 440 is further configured to use the assessment result of the financial risk that may occur in the information point to be assessed as a reference factor to assess the probability of the financial risk occurring in the user using the information point to be assessed.
FIG. 5 is a schematic structural diagram of another embodiment of the risk assessment device of the present disclosure.
As shown in fig. 5, the apparatus 500 of this embodiment includes: a memory 510 and a processor 520 coupled to the memory 510, the processor 520 configured to perform the risk assessment method of any of the foregoing embodiments based on instructions stored in the memory 510.
Memory 510 may include, for example, system memory, fixed non-volatile storage media, and the like. The system memory stores, for example, an operating system, an application program, a Boot Loader (Boot Loader), and other programs.
The apparatus 500 may also include an input-output interface 530, a network interface 540, a storage interface 550, and the like. These interfaces 530, 540, 550 and the connections between the memory 510 and the processor 520 may be, for example, via a bus 560. The input/output interface 530 provides a connection interface for input/output devices such as a display, a mouse, a keyboard, and a touch screen. The network interface 540 provides a connection interface for various networking devices. The storage interface 550 provides a connection interface for external storage devices such as an SD card and a usb disk.
The present disclosure also proposes a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the risk assessment method in any of the foregoing embodiments.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only exemplary of the present disclosure and is not intended to limit the present disclosure, so that any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
Claims (17)
1. A method of risk assessment, comprising:
determining a set of information points;
acquiring financial information of a user having a use behavior on any information point to be evaluated in the set;
calculating the value of the risk index of the information point to be evaluated according to the financial information of the user having the use behavior on the information point to be evaluated;
and according to the value of the risk index of the information point to be evaluated, evaluating the possibility of financial risk of the information point to be evaluated.
2. The method of claim 1, wherein the information points in the collection are determined based on a customer shipping address.
3. The method of claim 2, wherein,
and under the condition that a plurality of user receiving addresses correspond to any one information point in the set, calculating the distances between the plurality of user receiving addresses and the information point reference addresses, and selecting the user receiving addresses with small distances in a preset range to be used for determining the corresponding information points.
4. The method of claim 1, wherein the risk indicator comprises a user-type risk indicator, and calculating the value of the user-type risk indicator for the information point to be evaluated comprises:
calculating first use credibility of a first user on the information point to be evaluated, wherein the first user is any user having use behaviors on the information point to be evaluated;
calculating the sum of the use credibility of all the information points used by the first user;
determining the weight of the first user according to the proportion information of the first use reliability and the sum of the use reliabilities;
obtaining a value of a financial index associated with the user-type risk index for the first user;
and calculating the value of the user type risk index of the information point to be evaluated according to the weight of each first user and the values of the financial indexes related to the user type risk indexes of all the first users.
5. The method of claim 4, wherein calculating the value of the user-type risk indicator for the information point to be evaluated comprises:
carrying out weighted summation operation on credit measurement information of all the first users when applying for financial services by using the weight of each first user to obtain the value of the A card weighted risk index of the information point to be evaluated;
or, performing weighted summation operation on the risk measurement information of all the first users after participating in the financial activities by using the weight of each first user to obtain the value of the B-card weighted risk index of the information point to be evaluated;
or, under the condition that the user type risk index is a user weighted proportion index, the financial index related to the user weighted proportion index indicates whether the first user is a preset type user, and according to the weight of each first user, a preset type user and all first users are subjected to weighted proportion operation to obtain the value of the user weighted proportion index of the information point to be evaluated, wherein the preset type user includes at least one of the following: blacklisted users, overdue payment users, first order failed users, fraudulent users, pre-credited users, high quality users, low stability users.
6. The method of claim 4, wherein calculating a first confidence level of use of the information point to be evaluated by the first user comprises:
and determining the first use reliability of the first user on the information point to be evaluated according to the stability of the first user on the information point to be evaluated and the life cycle of the information point to be evaluated and in combination with the use degree of the first user on the information point to be evaluated.
7. The method of claim 1, wherein the risk indicator comprises an address type risk indicator, and calculating the value of the address type risk indicator for the information point to be evaluated comprises:
calculating a risk metric value of the information point to be evaluated as a high risk address point according to the category of the information point to be evaluated and the value of the commodity related to the financial payment overdue on the information point to be evaluated;
or calculating the information point to be evaluated as the risk metric value of the blacklist address point according to the distance between the information point to be evaluated and the blacklist address point.
8. The method of claim 1, further comprising:
and taking the evaluation result of the financial risk possibly occurring on the information point to be evaluated as a reference factor to evaluate the possibility of the financial risk occurring on the user using the information point to be evaluated.
9. A risk assessment device comprising:
the information point determining module is used for determining a set of information points;
the financial information acquisition module is used for acquiring the financial information of a user having a use behavior on any information point to be evaluated in the set;
the risk index calculation module is used for calculating the value of the risk index of the information point to be evaluated according to the financial information of the user having the use behavior on the information point to be evaluated;
and the risk evaluation module is used for evaluating the possibility of financial risk of the information point to be evaluated according to the value of the risk index of the information point to be evaluated.
10. The apparatus of claim 9, wherein the information point determining module is configured to determine the set of information points based on a customer shipping address.
11. The apparatus of claim 10, wherein,
and the information point determining module is used for calculating the distances between the plurality of user receiving addresses and the information point reference addresses under the condition that the plurality of user receiving addresses correspond to any one information point in the set, and selecting the user receiving addresses with the small distances in a preset range to determine the corresponding information points.
12. The apparatus of claim 9, wherein the risk indicator comprises a user type risk indicator, and the risk indicator calculating module is configured to calculate a value of the user type risk indicator for the information point to be evaluated, and comprises:
calculating first use credibility of a first user on the information point to be evaluated, wherein the first user is any user having use behaviors on the information point to be evaluated;
calculating the sum of the use credibility of all the information points used by the first user;
determining the weight of the first user according to the proportion information of the first use reliability and the sum of the use reliabilities;
obtaining a value of a financial index associated with the user-type risk index for the first user;
and calculating the value of the user type risk index of the information point to be evaluated according to the weight of each first user and the values of the financial indexes related to the user type risk indexes of all the first users.
13. The apparatus of claim 12, wherein the risk indicator calculation module, in calculating a first usage confidence of the first user for the information point to be assessed, is to:
and determining the first use reliability of the first user on the information point to be evaluated according to the stability of the first user on the information point to be evaluated and the life cycle of the information point to be evaluated and in combination with the use degree of the first user on the information point to be evaluated.
14. The apparatus according to claim 9, wherein the risk indicator includes an address type risk indicator, and the risk indicator calculating module is configured to calculate a value of the address type risk indicator of the information point to be evaluated, and includes:
calculating a risk metric value of the information point to be evaluated as a high risk address point according to the category of the information point to be evaluated and the value of the commodity related to the financial payment overdue on the information point to be evaluated;
or calculating the information point to be evaluated as the risk metric value of the blacklist address point according to the distance between the information point to be evaluated and the blacklist address point.
15. The apparatus of claim 9, wherein,
the risk assessment module is also used for taking the assessment result of the financial risk possibly occurring on the information point to be assessed as a reference factor to assess the possibility of the financial risk occurring on the user using the information point to be assessed.
16. A risk assessment device comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the risk assessment method of any of claims 1-9 based on instructions stored in the memory.
17. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the risk assessment method according to any one of claims 1-9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810453569.1A CN108711004A (en) | 2018-05-14 | 2018-05-14 | Methods of risk assessment and device and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810453569.1A CN108711004A (en) | 2018-05-14 | 2018-05-14 | Methods of risk assessment and device and computer readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108711004A true CN108711004A (en) | 2018-10-26 |
Family
ID=63868073
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810453569.1A Pending CN108711004A (en) | 2018-05-14 | 2018-05-14 | Methods of risk assessment and device and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108711004A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109492103A (en) * | 2018-11-09 | 2019-03-19 | 北京三快在线科技有限公司 | Label information acquisition methods, device, electronic equipment and computer-readable medium |
| CN110135694A (en) * | 2019-04-12 | 2019-08-16 | 深圳壹账通智能科技有限公司 | Product risks appraisal procedure, device, computer equipment and storage medium |
| CN111310784A (en) * | 2020-01-14 | 2020-06-19 | 支付宝(杭州)信息技术有限公司 | Resource data processing method and device |
| CN113408909A (en) * | 2021-06-22 | 2021-09-17 | 中国工商银行股份有限公司 | Bank user credit investigation evaluation method based on big data |
| CN113988671A (en) * | 2021-11-02 | 2022-01-28 | 城云科技（中国）有限公司 | Enterprise credit risk assessment method, device and application |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090248559A1 (en) * | 2008-03-28 | 2009-10-01 | Fortent Americas Inc. | Assessment of risk associated with doing business with a party |
| CN107203523A (en) * | 2016-03-16 | 2017-09-26 | 阿里巴巴集团控股有限公司 | A kind of method and device of the attribute information in determination geographical position |
| CN107808263A (en) * | 2017-12-01 | 2018-03-16 | 安徽中科超安科技有限公司 | Nuclear power station multi-risk System integrated estimation system and method based on information fusion |
-
2018
- 2018-05-14 CN CN201810453569.1A patent/CN108711004A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090248559A1 (en) * | 2008-03-28 | 2009-10-01 | Fortent Americas Inc. | Assessment of risk associated with doing business with a party |
| CN107203523A (en) * | 2016-03-16 | 2017-09-26 | 阿里巴巴集团控股有限公司 | A kind of method and device of the attribute information in determination geographical position |
| CN107808263A (en) * | 2017-12-01 | 2018-03-16 | 安徽中科超安科技有限公司 | Nuclear power station multi-risk System integrated estimation system and method based on information fusion |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109492103A (en) * | 2018-11-09 | 2019-03-19 | 北京三快在线科技有限公司 | Label information acquisition methods, device, electronic equipment and computer-readable medium |
| CN110135694A (en) * | 2019-04-12 | 2019-08-16 | 深圳壹账通智能科技有限公司 | Product risks appraisal procedure, device, computer equipment and storage medium |
| CN111310784A (en) * | 2020-01-14 | 2020-06-19 | 支付宝(杭州)信息技术有限公司 | Resource data processing method and device |
| CN113408909A (en) * | 2021-06-22 | 2021-09-17 | 中国工商银行股份有限公司 | Bank user credit investigation evaluation method based on big data |
| CN113988671A (en) * | 2021-11-02 | 2022-01-28 | 城云科技（中国）有限公司 | Enterprise credit risk assessment method, device and application |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109242261B (en) | Method for evaluating security risk based on big data and terminal equipment | |
| CN108711004A (en) | Methods of risk assessment and device and computer readable storage medium | |
| CN108665159A (en) | A kind of methods of risk assessment, device, terminal device and storage medium | |
| CN110689438A (en) | Enterprise financial risk scoring method and device, computer equipment and storage medium | |
| KR101762888B1 (en) | System and method of computing price of real propety using similar price zone and actual transaction price | |
| US8050959B1 (en) | System and method for modeling consortium data | |
| AU2014293388A1 (en) | Computing distances of devices | |
| CN106033575A (en) | Risk account identification method and apparatus | |
| CN113469789A (en) | Abnormal order detection method and device and computer equipment | |
| CN110009379A (en) | A kind of building of site selection model and site selecting method, device and equipment | |
| CN111062770B (en) | Merchant identification method, device and computer readable medium | |
| US20230419323A1 (en) | Systems and methods for routing electronic transactions using network simulation and forecasting | |
| US20170032707A1 (en) | Method for determining a fruition score in relation to a poverty alleviation program | |
| CN106875595A (en) | A kind of determination method and device of POS terminal place to use | |
| CN109583826B (en) | Declaration file generation method, declaration file generation device, server and readable storage medium | |
| CN111915256B (en) | Method for constructing dispatch fence, off-site signing and identifying method and related equipment | |
| US20160379327A1 (en) | Method of facilitating natural disaster relief planning | |
| CN115034788A (en) | Transaction risk assessment method and device, electronic equipment and storage medium | |
| CN115330468B (en) | Data processing method and related device | |
| CN110348983A (en) | Transaction Information management method and device, electronic equipment and non-transient storage media | |
| CN110555589A (en) | Risk order identification method and device | |
| US20220188831A1 (en) | Data verification in transactions in distributed network | |
| CN114862560A (en) | Automobile anti-fraud risk identification method and related equipment thereof | |
| CN113971247A (en) | Data processing method and computer program product | |
| CN112419008A (en) | Automatic grading early warning method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 100176 Beijing Daxing District Beijing Economic Development Zone, Chuang Chuang eleven Street 18 hospital C block 2 floor, 221 rooms. Applicant after: JINGDONG DIGITAL TECHNOLOGY HOLDINGS Co.,Ltd. Address before: 100176 Beijing Daxing District Beijing Economic Development Zone, Chuang Chuang eleven Street 18 hospital C block 2 floor, 221 rooms. Applicant before: BEIJING JINGDONG FINANCIAL TECHNOLOGY HOLDING Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: Room 221, 2nd floor, C Block, 18 Kechuang 11th Street, Beijing Daxing District, Beijing Applicant after: Jingdong Technology Holding Co.,Ltd. Address before: Room 221, 2nd floor, C Block, 18 Kechuang 11th Street, Beijing Daxing District, Beijing Applicant before: Jingdong Digital Technology Holding Co.,Ltd. Address after: Room 221, 2nd floor, C Block, 18 Kechuang 11th Street, Beijing Daxing District, Beijing Applicant after: Jingdong Digital Technology Holding Co.,Ltd. Address before: Room 221, 2nd floor, C Block, 18 Kechuang 11th Street, Beijing Daxing District, Beijing Applicant before: JINGDONG DIGITAL TECHNOLOGY HOLDINGS Co.,Ltd. |