CN110807708A - Risk prompting method and device - Google Patents
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- CN110807708A CN110807708A CN201911051034.2A CN201911051034A CN110807708A CN 110807708 A CN110807708 A CN 110807708A CN 201911051034 A CN201911051034 A CN 201911051034A CN 110807708 A CN110807708 A CN 110807708A
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Abstract
The application discloses a risk prompting method and device. The method comprises the following steps: acquiring a first user risk report; executing preset operation on the first user risk report, and determining a first risk characteristic; and outputting the prompt information generated according to the first risk characteristics on the first terminal of the first user. The device includes: an acquisition module for acquiring a first user risk report; the determining module is used for executing preset operation on the first user risk report and determining a first risk characteristic; and the prompt module is used for outputting the prompt information generated according to the first risk characteristic on the first terminal of the first user. The method and the device solve the technical problem that the intelligence degree is not high enough due to the fact that the user needs to artificially screen the risk characteristics in the risk report.
Description
Technical Field
The application relates to the field of insurance, in particular to a risk prompting method and device.
Background
The inventor finds that the online insurance system needs the user to input personal information and select insurance types, guarantee contents, guarantee amounts and the like through interface operation; the risk report is introduced, but the risk report has more contents, still needs manual screening to obtain risk characteristics, and has insufficient intelligence.
Aiming at the problem that the intelligence degree is not high enough due to the fact that users need to manually screen risk characteristics in a risk report in the related technology, an effective solution is not provided at present.
Disclosure of Invention
The main purpose of the present application is to provide a risk prompting method and device, so as to solve the problem that the intelligence degree is not high enough due to the fact that a user needs to manually screen risk features in a risk report.
In order to achieve the above object, according to one aspect of the present application, a risk suggesting method is provided.
The risk prompting method comprises the following steps: acquiring a first user risk report; executing preset operation on the first user risk report, and determining a first risk characteristic; and outputting the prompt information generated according to the first risk characteristics on the first terminal of the first user.
Further, the performing a preset operation on the first user risk report and determining the first risk characteristic further includes: receiving a prompt request of a first user at a first terminal; and outputting the prompt information generated according to the first risk characteristics on the first terminal of the first user according to the prompt request.
Further, obtaining the first user risk report includes: acquiring a financial risk report of a first user; performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises: performing preset extraction operation on the financial risk report, and determining a first financial risk characteristic; and executing a preset prediction operation on the financial risk report to predict a second financial risk characteristic.
Further, obtaining the first user risk report includes: acquiring a health risk report of a first user; performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises: executing preset extraction operation on the health risk report, and determining a first health risk characteristic; and executing preset prediction operation on the health risk report to predict a second health risk characteristic.
Further, obtaining the first user risk report includes: acquiring a behavior risk report of a first user; performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises: executing preset extraction operation on the behavior risk report, and determining a first behavior risk characteristic; and executing preset prediction operation on the behavior risk report, and predicting a second behavior risk characteristic.
In order to achieve the above object, according to another aspect of the present application, there is provided a risk suggesting device.
The risk prompting device according to the application comprises: an acquisition module for acquiring a first user risk report; the determining module is used for executing preset operation on the first user risk report and determining a first risk characteristic; and the prompt module is used for outputting the prompt information generated according to the first risk characteristic on the first terminal of the first user.
Further, the performing a preset operation on the first user risk report and determining the first risk characteristic further includes: the receiving module is used for receiving a prompt request of a first user at a first terminal; and the output module is used for outputting the prompt information generated according to the first risk characteristic on the first terminal of the first user according to the prompt request.
Further, the obtaining module includes: acquiring a financial risk report of a first user; the execution module comprises: performing preset extraction operation on the financial risk report, and determining a first financial risk characteristic; and executing a preset prediction operation on the financial risk report to predict a second financial risk characteristic.
Further, the obtaining module includes: acquiring a health risk report of a first user; the execution module comprises: executing preset extraction operation on the health risk report, and determining a first health risk characteristic; and executing preset prediction operation on the health risk report to predict a second health risk characteristic.
Further, the obtaining module includes: acquiring a behavior risk report of a first user; the execution module comprises: executing preset extraction operation on the behavior risk report, and determining a first behavior risk characteristic; and executing preset prediction operation on the behavior risk report, and predicting a second behavior risk characteristic.
In the embodiment of the application, a risk extraction and active prompt mode is adopted, and a first user risk report is obtained; executing preset operation on the first user risk report, and determining a first risk characteristic; outputting prompt information generated according to the first risk characteristics on a first terminal of the first user; the risk characteristic is actively extracted and prompted in the risk report, and the purpose of artificially screening the risk characteristic is not needed, so that the technical effect of improving the intelligent degree is achieved, and the technical problem that the intelligent degree is not high enough due to the fact that a user needs to artificially screen the risk characteristic in the risk report is solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
fig. 1 is a schematic flowchart of a risk indication method according to a first embodiment of the present application;
fig. 2 is a schematic flowchart of a risk indication method according to a second embodiment of the present application;
fig. 3 is a schematic flowchart of a risk indication method according to a third embodiment of the present application;
fig. 4 is a schematic flowchart of a risk indication method according to a fourth embodiment of the present application;
fig. 5 is a schematic flowchart of a risk indication method according to a fifth embodiment of the present application;
fig. 6 is a schematic structural diagram of a risk presentation device according to a first embodiment of the present application;
fig. 7 is a schematic structural diagram of a risk suggestion device according to a second embodiment of the application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the invention and its embodiments and are not intended to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meanings of these terms in the present invention can be understood by those skilled in the art as appropriate.
Furthermore, the terms "mounted," "disposed," "provided," "connected," and "sleeved" are to be construed broadly. For example, it may be a fixed connection, a removable connection, or a unitary construction; can be a mechanical connection, or an electrical connection; may be directly connected, or indirectly connected through intervening media, or may be in internal communication between two devices, elements or components. The specific meanings of the above terms in the present invention can be understood by those of ordinary skill in the art according to specific situations.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
According to an embodiment of the present invention, there is provided a risk indicating method, as shown in fig. 1, the method includes the following steps S100 to S104:
s100, acquiring a first user risk report;
step S102, executing preset operation on the first user risk report, and determining a first risk characteristic;
preferably, according to an embodiment of the present invention, as shown in fig. 3,
obtaining the first user risk report includes:
step S300, acquiring a financial risk report of a first user;
performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises:
step S302, executing preset extraction operation on the financial risk report, and determining a first financial risk characteristic;
and S304, executing preset prediction operation on the financial risk report, and predicting a second financial risk characteristic.
After generating and storing the financial risk report, the server defaults to a program for acquiring the financial risk report from the database, extracts corresponding first financial risk characteristics from the financial risk report, and predicts second financial risk characteristics; for example, extracting the previous investment risk characteristics from the financial risk report, and predicting the future investment risk characteristics according to the investment income trend; the purpose of screening risk characteristics without human is achieved, the intelligent degree is improved, and a guarantee is provided for giving a risk prompt.
Preferably, according to an embodiment of the present invention, as shown in fig. 4,
obtaining the first user risk report includes:
step S400, acquiring a health risk report of a first user;
performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises:
step S402, executing preset extraction operation on the health risk report, and determining a first health risk characteristic;
and S404, executing preset prediction operation on the health risk report, and predicting a second health risk characteristic.
After generating and storing a financial risk report, the server defaults to a program for acquiring a health risk report from the database, extracts corresponding first health risk characteristics from the health risk report, and predicts second health risk characteristics; for example, previous medical history risk characteristics are extracted from the health risk report, and disease risk characteristics are predicted according to health data (heart rate, respiration, sleep and the like); the purpose of screening risk characteristics without human is achieved, the intelligent degree is improved, and a guarantee is provided for giving a risk prompt.
Preferably, according to an embodiment of the present invention, as shown in fig. 5,
obtaining the first user risk report includes:
step S500, acquiring a behavior risk report of a first user;
performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises:
step S502, executing preset extraction operation on the behavior risk report, and determining a first behavior risk characteristic;
and step S504, executing preset prediction operation on the behavior risk report, and predicting second behavior risk characteristics.
After generating and storing the financial risk report, the server defaults to a program for acquiring the behavior risk report from the database, extracts corresponding first behavior risk characteristics from the behavior risk report, and predicts second behavior risk characteristics; for example, extracting the safety risk characteristics of the previous frequent residence from the behavior risk report, and predicting the possible future safety risk characteristics according to frequent places, vehicles and the like; the purpose of screening risk characteristics without human is achieved, the intelligent degree is improved, and a guarantee is provided for giving a risk prompt.
According to the embodiment of the present invention, preferably, as shown in fig. 2, after the performing a preset operation on the first user risk report and determining the first risk characteristic, the method further includes:
step S200, receiving a prompt request of a first user at a first terminal;
step S202, according to the prompt request, outputting the prompt information generated according to the first risk characteristic on the first terminal of the first user.
The first user can send a prompt request in an operation interface of the first terminal, and only when the prompt request is sent, the risk characteristics are output; therefore, the first risk characteristics are output to the first terminal for the first user to check the risk characteristics, and manual selection of insurance products, guarantee contents and the like can be performed more accurately according to the risk characteristics.
And step S104, outputting the prompt information generated according to the first risk characteristics on the first terminal of the first user.
After the first risk characteristics are obtained, the server actively sends a prompt to the associated first terminal; therefore, the first risk characteristics are output to the first terminal for prompting, so that the first user can check the risk characteristics, and further, artificial insurance products, guarantee contents and the like can be selected more accurately according to the risk characteristics.
According to the embodiment of the present invention, preferably, the acquiring of the risk report includes:
step A, acquiring first-dimension user data;
and B, inputting the first-dimension user data into a first preset risk analysis model to generate a first user risk report.
According to embodiments of the present invention, it is preferable,
acquiring the first-dimension user data includes:
the method comprises the steps that a user database acquires financial consumption data of a first user periodically;
inputting the first-dimension user data into a first preset risk analysis model, and generating a first user risk report comprises:
and inputting the financial consumption data into a preset financial risk analysis model, and generating a financial risk report of the first user.
After the personal data is built, when a user opens application processing software at a mobile phone end and enters a financial operation interface, three selection buttons are arranged in the financial operation interface, and the three selection buttons are respectively used for manually inputting financial data, automatically crawling financial data generated by the user at the mobile phone end and manually importing the financial data generated at the mobile phone end by the user.
In actual use, a user can select any one type to enter financial data according to actual conditions, and can also combine two or more types to enter financial data; the integrity of the financial data is guaranteed.
In this embodiment, manually entering the financial data is manually entering personal financial data for the user with reference to his financial information.
In the embodiment, a user manually imports financial data generated at a mobile phone end to access interfaces of a payment bank, a WeChat and the like after the financial data is authorized by the user, automatically analyzes a short message of the mobile phone of the user, and perfects the financial data of the user according to consumption short messages of a daily mobile phone bank, the payment bank, the WeChat and the like; and an entry is provided for inputting a bank flow data report, and the user income and expenditure conditions are analyzed and analyzed.
In the embodiment, financial data generated by the user at the mobile phone end is automatically crawled as an authorized binding user mailbox, and financial data such as the user payment treasure WeChat is analyzed through a POP3/SMTP/IMAP protocol, so that the financial data is further improved.
In this embodiment, preferably, the financial consumption data in the preset period is obtained by combining the three modes, so as to provide data security for the generation of the financial risk report in the next step.
And after the financial consumption data are obtained, inputting the financial consumption data into a preset financial risk analysis model for risk analysis, and obtaining a financial risk report.
Such as: uniformly analyzing WeChat, bill of Paibao and income level in the financial consumption data, analyzing the proportion of expenditure to income, judging whether the proportion is higher than a certain threshold value, and if so, giving out a risk prompt that expenditure is too high and the expenditure is not paid out; setting the balance proportion, the risk prompt and the personal information of the user into a block, and generating a financial risk report.
For another example: analyzing the investment income in the financial consumption data, analyzing the loss rate or the return rate, and giving a prompt whether the investment has continuous loss risk or not; and setting the loss rate or return rate, the risk prompt and the personal information of the user into a block to generate a financial risk report.
Therefore, the user can check the financial risk report, correspondingly adjust or purchase corresponding insurance to prevent risks, and accurately know the financial insurance type to be selected according to the risk type, so that the defect of difficulty in selecting the financial insurance is overcome.
According to embodiments of the present invention, it is preferable,
acquiring the first-dimension user data includes:
the user database acquires health data of a first user periodically;
inputting the first-dimension user data into a first preset risk analysis model, and generating a first user risk report comprises:
and inputting the health data into a preset health risk analysis model to generate a health risk report of the first user.
After the personal data is filed, when a user opens application processing software at a mobile phone end and enters a health operation interface, the user can import health data in an interface mode; or, the health data (such as family medical history) is automatically input at the mobile phone end.
In this embodiment, a user manually imports health data generated at a mobile phone end; or, health data (such as family medical history) is automatically input at the mobile phone end, and the health data is accessed or input into interfaces of wearable equipment, step counting software and the like after being authorized by the user, and data such as exercise step number, heart rate, blood pressure, sleep, pressure and the like of the user are imported.
And after the health data are obtained, inputting the health data into a preset health risk analysis model for risk analysis to obtain a health risk report.
Such as: analyzing the heart rate in the health data, judging whether the heart rate is within a preset threshold range, if so, indicating that the heart rate is abnormal, and giving a risk prompt; the abnormal heart rate, the risk prompt and the personal information of the user are set to one block, and a health (heart rate) risk report is generated.
For another example: analyzing the breath in the health data, judging whether the breath is in a preset threshold range, if so, indicating that the breath is abnormal, and giving a risk prompt; the breathing abnormality, the risk prompt and the personal information of the user are set to one block, and a health (breathing) risk report is generated.
For another example: analyzing the heart rate, the blood pressure, the sleep and the pressure in the health data at the same time, judging whether the heart rate, the blood pressure, the sleep and the pressure are in a preset threshold range, if so, indicating that the problems of abnormal heart rate, blood pressure, sleep and pressure exist, and giving a risk prompt; the heart rate, blood pressure, sleep, abnormal pressure, risk prompt and personal information of the user are set to one block, and a health (heart rate, blood pressure, sleep, pressure) risk report is generated.
For another example: analyzing family medical history in the health data, judging the probability of the same focus of the user, judging whether the probability is in a preset threshold range, and if not, considering that the user has a disease risk and giving a risk prompt; the risk of illness, the risk prompt and the personal information of the user are set to one block, and a health (illness) risk report is generated.
Therefore, the user can check the health risk report, correspondingly adjust or purchase corresponding health insurance, and when the risk is prevented, the user can accurately know the type of the health insurance to be selected according to the risk type, so that the defect of difficulty in selecting the health insurance is overcome.
According to embodiments of the present invention, it is preferable,
acquiring the first-dimension user data includes:
the user database acquires behavior data of a first user periodically;
inputting the first-dimension user data into a first preset risk analysis model, and generating a first user risk report comprises:
and inputting the behavior data into a preset behavior risk analysis model to generate a behavior risk report of the first user.
After the personal data is finished being filed, when a user opens application processing software at a mobile phone end to enter a behavior operation interface, the user can import behavior data in an interface mode; or, the behavior data is automatically input at the mobile phone end.
In this embodiment, a user may import behavior data in an interface manner; or, the behavior data is automatically input at the mobile phone end to access a mobile phone short message interface and software interfaces for travel, traffic, dining, lodging and the like, user traffic data (automobiles, airplanes, dripping and the like) are imported, dining data (mysterious, hungry, popular, kendiry and the like), lodging data (travel, pig flight, same travel and the like) are imported, and the like.
In this embodiment, the user may also authorize positioning, and the system coarsely records the user position to form user activity data.
And after the behavior data are obtained, inputting the behavior data into a preset behavior risk analysis model for risk analysis to obtain a behavior risk report.
Such as: analyzing the traffic data in the behavior data, and analyzing frequent residence places, frequent business places, vehicles, frequently used ticket purchasing software and the like of the users, so that a traffic risk prompt can be given according to the analyzed information; setting frequent residence places, frequent business places, vehicles, frequently used ticket purchasing software and the like and user personal information into a whole to generate a behavior (traffic) risk report.
For another example: the catering data in the behavior data is analyzed, frequent catering merchants of the user, frequently used takeout software and the like can be analyzed, and therefore a prompt of a food delivery delay risk can be given according to the analyzed information; setting frequent eating merchants, frequently used takeout software and the like and user personal information into a whole to generate a behavior (dining) risk report.
For another example: the lodging data in the behavior data is analyzed, and frequent lodging hotels of the user, frequent lodging software and the like can be analyzed, so that a prompt of safety risks can be given according to the analyzed information; setting frequent catering merchants, frequently used takeout software and the like and user personal information into a whole to generate a behavior (accommodation) risk report.
For another example: the position data in the behavior data are analyzed, the position of the user can be analyzed, and then activity data are formed, so that the prompt of traffic jam and safety risk can be given according to the analyzed information; and setting the position of the user and the personal information of the user into a block to generate a behavior (accommodation) risk report.
Therefore, the user can check the health risk report, correspondingly adjust or purchase corresponding health insurance, and when the risk is prevented, the user can accurately know the type of the health insurance to be selected according to the risk type, so that the defect of difficulty in selecting the health insurance is overcome.
According to the embodiment of the present invention, preferably, before acquiring the first-dimension user data, the method further includes:
acquiring user personal data acquired by wearable intelligent equipment;
and establishing a user database according to the personal data of the user.
The user personal data includes: information such as user age, gender, name, mobile phone number, height, weight and the like; in this embodiment, preferably, the information of the age, sex, name, and phone number of the user can be actively entered through the phone terminal; the height and weight information can be acquired through wearable equipment.
The entering of the corresponding information at the mobile phone end may be: entering a registration page, and filling corresponding information in the page to complete registration; corresponding information may also be accessed from third party interfaces, such as: corresponding information is accessed from interfaces such as WeChat and Payment treasures; and the user can be guided to complete registration through a mobile phone terminal in a line-down mode.
After information is input, the server defaults to complete user profiling, and data of each user is stored according to a structural storage mode; when other data of the user appears, the data is also stored under the file name.
According to the embodiment of the invention, preferably, two or three of financial consumption data, health data and behavior data of a user can be acquired simultaneously, and input into a corresponding model for risk analysis, and finally an all-round risk report is generated; according to the risk types in the risk report, the personnel can know the insurance types to be selected, and the defect of difficulty in selecting health insurance is overcome.
From the above description, it can be seen that the present invention achieves the following technical effects:
in the embodiment of the application, a risk extraction and active prompt mode is adopted, and a first user risk report is obtained; executing preset operation on the first user risk report, and determining a first risk characteristic; outputting prompt information generated according to the first risk characteristics on a first terminal of the first user; the risk characteristic is actively extracted and prompted in the risk report, and the purpose of artificially screening the risk characteristic is not needed, so that the technical effect of improving the intelligent degree is achieved, and the technical problem that the intelligent degree is not high enough due to the fact that a user needs to artificially screen the risk characteristic in the risk report is solved.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
According to an embodiment of the present invention, there is also provided a device for implementing the risk prompting method, as shown in fig. 6, the device includes:
an obtaining module 10, configured to obtain a first user risk report;
a determining module 20, configured to perform a preset operation on the first user risk report, and determine a first risk characteristic;
according to embodiments of the present invention, it is preferable,
the acquisition module 10 includes:
acquiring a financial risk report of a first user;
the execution module 20 includes:
performing preset extraction operation on the financial risk report, and determining a first financial risk characteristic;
and executing a preset prediction operation on the financial risk report to predict a second financial risk characteristic.
After generating and storing the financial risk report, the server defaults to a program for acquiring the financial risk report from the database, extracts corresponding first financial risk characteristics from the financial risk report, and predicts second financial risk characteristics; for example, extracting the previous investment risk characteristics from the financial risk report, and predicting the future investment risk characteristics according to the investment income trend; the purpose of screening risk characteristics without human is achieved, the intelligent degree is improved, and a guarantee is provided for giving a risk prompt.
According to embodiments of the present invention, it is preferable,
the acquisition module 10 includes:
acquiring a health risk report of a first user;
the execution module 20 includes:
executing preset extraction operation on the health risk report, and determining a first health risk characteristic;
and executing preset prediction operation on the health risk report to predict a second health risk characteristic.
After generating and storing a financial risk report, the server defaults to a program for acquiring a health risk report from the database, extracts corresponding first health risk characteristics from the health risk report, and predicts second health risk characteristics; for example, previous medical history risk characteristics are extracted from the health risk report, and disease risk characteristics are predicted according to health data (heart rate, respiration, sleep and the like); the purpose of screening risk characteristics without human is achieved, the intelligent degree is improved, and a guarantee is provided for giving a risk prompt.
According to embodiments of the present invention, it is preferable,
the acquisition module 10 includes:
acquiring a behavior risk report of a first user;
the execution module 20 includes:
executing preset extraction operation on the behavior risk report, and determining a first behavior risk characteristic;
and executing preset prediction operation on the behavior risk report, and predicting a second behavior risk characteristic.
After generating and storing the financial risk report, the server defaults to a program for acquiring the behavior risk report from the database, extracts corresponding first behavior risk characteristics from the behavior risk report, and predicts second behavior risk characteristics; for example, extracting the safety risk characteristics of the previous frequent residence from the behavior risk report, and predicting the possible future safety risk characteristics according to frequent places, vehicles and the like; the purpose of screening risk characteristics without human is achieved, the intelligent degree is improved, and a guarantee is provided for giving a risk prompt.
According to the embodiment of the present invention, preferably, as shown in fig. 7, after the performing a preset operation on the first user risk report and determining the first risk characteristic, the method further includes:
a receiving module 40, configured to receive a prompt request of a first user at a first terminal;
and an output module 50, configured to output, according to the prompt request, the prompt information generated according to the first risk characteristic on the first terminal of the first user.
The first user can send a prompt request in an operation interface of the first terminal, and only when the prompt request is sent, the risk characteristics are output; therefore, the first risk characteristics are output to the first terminal for the first user to check the risk characteristics, and manual selection of insurance products, guarantee contents and the like can be performed more accurately according to the risk characteristics.
And a prompt module 30, configured to output, on the first terminal of the first user, prompt information generated according to the first risk characteristic.
After the first risk characteristics are obtained, the server actively sends a prompt to the associated first terminal; therefore, the first risk characteristics are output to the first terminal for prompting, so that the first user can check the risk characteristics, and further, artificial insurance products, guarantee contents and the like can be selected more accurately according to the risk characteristics.
According to an embodiment of the present invention, there is also provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the risk notification method when executing the program.
There is also provided, according to an embodiment of the present invention, a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, performs the steps of the risk alert method.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and they may alternatively be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or fabricated separately as individual integrated circuit modules, or fabricated as a single integrated circuit module from multiple modules or steps. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A risk prompting method is characterized by comprising the following steps:
acquiring a first user risk report;
executing preset operation on the first user risk report, and determining a first risk characteristic;
and outputting the prompt information generated according to the first risk characteristics on the first terminal of the first user.
2. The risk prompting method according to claim 1, wherein the performing a preset operation on the first user risk report further comprises, after determining the first risk characteristic:
receiving a prompt request of a first user at a first terminal;
and outputting the prompt information generated according to the first risk characteristics on the first terminal of the first user according to the prompt request.
3. The risk suggesting method according to claim 1,
obtaining the first user risk report includes:
acquiring a financial risk report of a first user;
performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises:
performing preset extraction operation on the financial risk report, and determining a first financial risk characteristic;
and executing a preset prediction operation on the financial risk report to predict a second financial risk characteristic.
4. The risk suggesting method according to claim 1,
obtaining the first user risk report includes:
acquiring a health risk report of a first user;
performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises:
executing preset extraction operation on the health risk report, and determining a first health risk characteristic;
and executing preset prediction operation on the health risk report to predict a second health risk characteristic.
5. The risk suggesting method according to claim 1,
obtaining the first user risk report includes:
acquiring a behavior risk report of a first user;
performing a preset operation on the first user risk report, wherein determining a first risk characteristic comprises:
executing preset extraction operation on the behavior risk report, and determining a first behavior risk characteristic;
and executing preset prediction operation on the behavior risk report, and predicting a second behavior risk characteristic.
6. A risk suggestion device, comprising:
an acquisition module for acquiring a first user risk report;
the determining module is used for executing preset operation on the first user risk report and determining a first risk characteristic;
and the prompt module is used for outputting the prompt information generated according to the first risk characteristic on the first terminal of the first user.
7. The risk prompting device of claim 6, wherein the performing a preset operation on the first user risk report further comprises, after determining the first risk characteristic:
the receiving module is used for receiving a prompt request of a first user at a first terminal;
and the output module is used for outputting the prompt information generated according to the first risk characteristic on the first terminal of the first user according to the prompt request.
8. The risk suggesting device according to claim 6,
the acquisition module includes:
acquiring a financial risk report of a first user;
the execution module comprises:
performing preset extraction operation on the financial risk report, and determining a first financial risk characteristic; and executing a preset prediction operation on the financial risk report to predict a second financial risk characteristic.
9. The risk suggesting device according to claim 6,
the acquisition module includes:
acquiring a health risk report of a first user;
the execution module comprises:
executing preset extraction operation on the health risk report, and determining a first health risk characteristic;
and executing preset prediction operation on the health risk report to predict a second health risk characteristic.
10. The risk suggesting device according to claim 6,
the acquisition module includes:
acquiring a behavior risk report of a first user;
the execution module comprises:
executing preset extraction operation on the behavior risk report, and determining a first behavior risk characteristic;
and executing preset prediction operation on the behavior risk report, and predicting a second behavior risk characteristic.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911051034.2A CN110807708A (en) | 2019-10-30 | 2019-10-30 | Risk prompting method and device |
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| CN109302338A (en) * | 2018-08-31 | 2019-02-01 | 南昌努比亚技术有限公司 | Intelligent indicating risk method, mobile terminal and computer readable storage medium |
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| US20160140864A1 (en) * | 2013-08-05 | 2016-05-19 | Drexel University | System and method for managing binge eating disorders |
| CN108766569A (en) * | 2018-05-07 | 2018-11-06 | 苏州超云生命智能产业研究院有限公司 | Health data processing method and health data processing system |
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