CN112102069A - Personal property mortgage loan information input analysis system - Google Patents
Personal property mortgage loan information input analysis system Download PDFInfo
- Publication number
- CN112102069A CN112102069A CN202010985561.7A CN202010985561A CN112102069A CN 112102069 A CN112102069 A CN 112102069A CN 202010985561 A CN202010985561 A CN 202010985561A CN 112102069 A CN112102069 A CN 112102069A
- Authority
- CN
- China
- Prior art keywords
- information
- loan
- client
- data
- customer
- 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
- 238000011156 evaluation Methods 0.000 claims abstract description 26
- 238000007781 pre-processing Methods 0.000 claims abstract description 22
- 238000012545 processing Methods 0.000 claims description 16
- 238000010276 construction Methods 0.000 claims description 13
- 238000012549 training Methods 0.000 claims description 13
- 238000003066 decision tree Methods 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 11
- 238000000605 extraction Methods 0.000 claims description 9
- 230000004927 fusion Effects 0.000 claims description 6
- 238000012360 testing method Methods 0.000 claims description 6
- 238000011161 development Methods 0.000 claims description 5
- 238000005516 engineering process Methods 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 3
- 238000007667 floating Methods 0.000 claims description 3
- 238000007499 fusion processing Methods 0.000 claims description 3
- 238000011896 sensitive detection Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 238000012856 packing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
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
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/283—Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
-
- 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
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/16—Real estate
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Data Mining & Analysis (AREA)
- Educational Administration (AREA)
- Entrepreneurship & Innovation (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Quality & Reliability (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Probability & Statistics with Applications (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Operations Research (AREA)
- Technology Law (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The invention belongs to the field of house mortgage loan, and particularly discloses a personal house mortgage loan information input analysis system which comprises a client side and a system server, wherein the client side is used for a client to automatically input client information on line and display loan application evaluation information and matched loan types, and the client information comprises application information, principal and lender data information, co-applicant data information and prover data information; the loan product management end presets loan products covered by different loan categories and manages the loan categories; and the input analysis evaluation subsystem is used for evaluating the client loan application according to the client information input by the client and the preset loan category, and matching the loan category suitable for the client requirement and the loan products corresponding to the category. The input analysis system can obtain the loan application prediction result by inputting the customer information with multiple dimensions, preprocessing the customer information, extracting the multi-dimensional characteristic information and performing prediction analysis, and the input and analysis are more comprehensive.
Description
Technical Field
The invention relates to the field of house mortgage loan, in particular to a personal house mortgage loan information input analysis system.
Background
Mortgage loan refers to a type of loan transaction that is conducted in a mortgage fashion. Such as: the house mortgage loan is a personal house loan service in which a purchaser mortises a house purchased and provides a stage guarantee by a real estate enterprise of the house purchased. The mortgage is that the mortgage releases the transfer of the property right of the house, and the beneficiary as a repayment guarantee person transfers the property right of the house to the mortgage immediately after the mortgage releases the loan, so that the mortgage enjoys the right of use in the process. With the rapid growth of national economy in China, the demand of mortgage loan of urban and rural residents increases, personal loan service has a better development trend in the future, and the proportion of the loan service in the life of consumers is larger and larger.
With the continuous development of economy, when people have insufficient funds, people can solve the problems caused by the insufficient funds through loan. In the existing loan service, the credit of the user is generally evaluated according to the acquired personal data of the user, previous loan records, bank flow and other information, so that the user is issued with a loan according to the credit of the user and the loan amount applied by the user. On the one hand this is not comprehensive enough and not precise. On the other hand, various types of personal credit products are various at present, the requirements of each product on a borrower are different, the offered loan conditions are also different, and the borrower is difficult to quickly select the most appropriate product from a plurality of types of loan products, so that a personal property mortgage loan information recording and analyzing system is needed.
Disclosure of Invention
The invention aims to provide a personal property mortgage loan information input analysis system to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a personal property mortgage loan information input analysis system comprises a client, a data processing module and a data processing module, wherein the client is used for a client to automatically input client information on line and display loan application evaluation information and matched loan types, and the client information comprises application information, principal and lender data information, co-applicant data information and prover data information; the loan product management end presets loan products covered by different loan categories and manages the loan categories; the input analysis and evaluation subsystem is used for evaluating the client loan application according to the client information input by the client and the preset loan category and matching the loan category suitable for the client requirement and the loan products corresponding to the category; and the manual service end intervenes and makes analysis evaluation on the client loan application when the input analysis evaluation subsystem cannot automatically evaluate the client loan application according to the rule.
Preferably, the application information includes loan application, interview records, image data, loan usage and other data, including project information, house information, mortgage information and customer manager opinions; the data information of the principal lender comprises an identity card, a spouse identity card, an identity certificate, a credit standing certificate and a repayment capability certificate; the information of the co-applicant data comprises an identity card, an identity certificate, a credit standing certificate, a repayment capability certificate and spouse related information, wherein the spouse related information comprises a spouse identity card, basic information, credit information, a relation with the current bank and income and expenditure information; the information of the guarantor data comprises an identity card, a spouse identity card, an identity certificate, a credit standing certificate and a repayment capability certificate.
Preferably, the client acquires the client information through an OCR technology and uploads the client information to the input analysis and evaluation subsystem, and the input analysis and evaluation subsystem stores and analyzes and evaluates the client information; the logging analytics evaluation subsystem includes: the preprocessing module is used for preprocessing the client information acquired by the client; the characteristic information construction module is used for extracting multi-dimensional characteristic information from the preprocessed customer information and constructing a training set according to the extracted multi-dimensional characteristic information; the prediction analysis module is used for acquiring customer information and characteristic information to construct a test set, and predicting the test set by using the decision tree so as to obtain a loan application prediction result of a customer; and the matching module is used for matching the loan category suitable for customer requirements, the loan products corresponding to the category and the matching result of the loan repayment risk of the borrower according to the loan application prediction result, and pushing the loan category and the loan products corresponding to the loan category to the client after matching is finished.
Preferably, the preprocessing module includes a preprocessing unit and a processing unit, the preprocessing unit is configured to obtain historical credit data and credit data of the customer according to customer information, transmit the historical credit data and credit data to the processing unit, and preprocess the historical credit data and credit data by the processing unit, where the preprocessing process includes: step a: extracting the historical credit data and the credit data or the data in the customer information, and adding the extracted data into a database; step b: and carrying out knowledge fusion on the knowledge base, wherein the knowledge fusion process comprises entity disambiguation and coreference resolution, and preprocessing data after the knowledge fusion.
Preferably, the feature information construction module comprises an extraction unit and a construction unit, the extraction unit extracts multi-dimensional feature information related to the feature information according to a preset extraction rule, the multi-dimensional feature information is uploaded to the construction unit, and the construction unit generates a decision tree according to the attributes to train the sub-training set.
Preferably, the multidimensional characteristic information includes personal data to be analyzed and evaluated, which is needed for training and generating the decision tree, and the personal data is used as a variable in the process of training and generating the decision tree, and the multidimensional characteristic information includes but is not limited to customer marital information, spouse information, famous property information, income growth rate and work information, and the work information includes work sustainable development information, salary floating information and the like.
The recording and analyzing method of the personal property mortgage loan information recording and analyzing system comprises the following steps:
s1: the loan client sends request information for requesting loan application to the system;
s2: the system acquires request information of a client, carries out sensitive detection on the request information, and pushes an information input window to the client after the detection is finished;
s3: a client inputs information in a self-service mode on line through a client;
s4: the system analyzes the input information of the client to obtain the client analysis information of the client, and the analysis information is preprocessed, subjected to multi-dimensional characteristic information extraction and predictive analysis to obtain a loan application prediction result;
s5: the system matches the loan category suitable for the customer requirement, the loan products corresponding to the category and the matching result of the loan repayment risk of the borrower according to the loan application prediction result.
Compared with the prior art, the invention has the beneficial effects that:
1. the input analysis system can obtain the loan application prediction result by inputting the customer information with multiple dimensions, preprocessing the customer information, extracting the multi-dimensional characteristic information and performing prediction analysis, and the input and analysis are more comprehensive and accurate enough.
2. The invention can match the loan category suitable for the customer requirement, the loan products corresponding to the category and the matching result of the loan repayment risk of the borrower through the analysis processing result, has the characteristics of strong real-time performance, high reliability and accuracy and the like of the evaluation and matching result, and can intelligently match the suitable loan products.
Drawings
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a block diagram of the structure of the logging analysis and evaluation subsystem of the present invention;
FIG. 3 is a flow chart of the logging analysis of the system of the present invention.
In the figure: 1. a client; 2. a loan product management side; 3. inputting an analysis and evaluation subsystem; 301. a preprocessing module; 301a, a pre-acquisition unit; 301b, a processing unit; 302. a characteristic information construction module; 302a, an extraction unit; 302b, a construction unit; 303. a predictive analysis module; 304. a matching module; 4. and (5) a manual service end.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
Referring to fig. 1-3, the present invention provides a technical solution: a personal property mortgage loan information input analysis system comprises a client 1, a data processing system and a data processing system, wherein the client 1 is used for a client to input client information in a self-service manner on line and display loan application evaluation information and matched loan types, and the client information comprises application information, principal and lender data information, co-applicant data information and guarantor data information; a loan product management terminal 2 which presets loan products covered by different loan categories and manages the loan categories; the input analysis and evaluation subsystem 3 is used for evaluating the client loan application according to the client information input by the client 1 and the preset loan category, and matching the loan category suitable for the client requirement and the loan products corresponding to the category; and the manual service end 4 is used for intervening and making analysis and evaluation on the client loan application when the input analysis and evaluation subsystem 3 cannot automatically evaluate the client loan application according to the rule.
In this embodiment, the application information includes loan application, interview records, image data, loan usage and other data, including project information, house information, mortgage information and customer manager opinions; the data information of the principal lender comprises an identity card, a spouse identity card, an identity certificate, a credit standing certificate and a repayment capability certificate; the information of the co-applicant data comprises an identity card, an identity certificate, a credit standing certificate, a repayment capability certificate and spouse related information, wherein the spouse related information comprises a spouse identity card, basic information, credit information, a relation with the current bank and income and expenditure information; the information of the guarantor data comprises an identity card, a spouse identity card, an identity certificate, a credit standing certificate and a repayment capability certificate.
In this embodiment, the information of the owner/lender part is as follows: the name is Li XX, gender (male and female), birthday (19XX-XX-XX), whether a house exists, whether a car exists, whether a life risk exists, whether a professional identity exists, salary, no industry, unfinished loan (0/XX ten thousand), the amount of credit card debt is 0/XX ten thousand, whether the credit condition is known, whether the credit belongs to credit investigation and blank credit, whether the credit is overdue or overdue.
In the embodiment, the client 1 collects the client information through an OCR technology and uploads the client information to the input analysis and evaluation subsystem 3, and the input analysis and evaluation subsystem 3 stores and analyzes and evaluates the client information; the logging analysis and evaluation subsystem 3 includes: the preprocessing module 301 is used for preprocessing the client information collected by the client; a feature information construction module 302, configured to extract multidimensional feature information from the preprocessed customer information, and construct a training set according to the extracted multidimensional feature information; the prediction analysis module 303 is configured to obtain customer information and feature information to construct a test set, and predict the test set by using the decision tree, so as to obtain a prediction result of the loan application of the customer; the matching module 304 matches the loan category suitable for the customer requirement, the loan products corresponding to the category and the matching result of the loan repayment risk of the borrower according to the loan application prediction result, and pushes the loan category and the loan products corresponding to the loan category to the client after the matching is finished.
In this embodiment, the preprocessing module 301 includes a pre-collecting unit 301a and a processing unit 301b, the pre-collecting unit 301a is configured to obtain the historical credit data and credit data of the customer according to the customer information, transmit the data and the customer information to the processing unit 301b, and perform preprocessing on the data and the credit data by the processing unit 301 b.
In this embodiment, the preprocessing process includes: reading a customer information text: obtaining a complete set chars _ set, bios _ set and relations _ set of the radicals of the words; traversing training data: packing the token _ id, token, bio, relations and headers in each sentence into the sentence as a list; secondly, traversing the current sentence to id the sample data, and packaging a word list embedding _ ids, a list char _ ids of radical id, a list bio _ ids of entity labels and a list scoping matrix heads of relationship into the sentence; and processing sentence id data to ensure that the dimension of each sentence in a batch of data is equal, the dimension of the longest sentence is taken as the maximum dimension, and the insufficient filling is 0.
In this embodiment, the preprocessing process includes: step a: extracting the historical credit data and the credit data or the data in the customer information, and adding the extracted data into a database; step b: and carrying out knowledge fusion on the knowledge base, wherein the knowledge fusion process comprises entity disambiguation and coreference resolution, and preprocessing data after the knowledge fusion.
In this embodiment, the feature information constructing module 302 includes an extracting unit 302a and a constructing unit 302b, where the extracting unit 302a extracts multi-dimensional feature information related to feature information according to a preset extraction rule, and uploads the multi-dimensional feature information to the constructing unit 302b, and the constructing unit 302b generates a decision tree according to an attribute to train a sub-training set.
In the embodiment, the multidimensional feature information includes personal data to be analyzed and evaluated, which is needed for training and generating the decision tree, and the personal data is used as a variable in the process of training and generating the decision tree, the multidimensional feature information includes, but is not limited to, customer marital information, spouse information, famous property information, income growth rate and work information, and the work information includes work sustainable development information, salary floating information and the like.
In this embodiment, the method for entering and analyzing the mortgage loan information of the personal property includes the following steps:
s1: the loan client sends request information for requesting loan application to the system;
s2: the system acquires request information of the client 1, performs sensitive detection on the request information, and pushes an information input window to the client 1 after the detection is completed;
s3: a client inputs information in a self-service mode on line through a client 1;
s4: the system analyzes the input information of the client 1 to obtain the customer analysis information of the client 1, and the analysis information is preprocessed, extracted by multi-dimensional characteristic information and subjected to prediction analysis to obtain a loan application prediction result;
s5: the system matches the loan category suitable for the customer requirement, the loan products corresponding to the category and the matching result of the loan repayment risk of the borrower according to the loan application prediction result.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A personal property mortgage loan information input analysis system is characterized by comprising a client (1) and a system server, wherein the client is used for a client to automatically input client information on line and display loan application evaluation information and matched loan types, and the client information comprises application information, principal and lender information, co-applicant information and guarantor information; a loan product management end (2) which is preset with loan products covered by different loan categories and manages the loan categories; the input analysis evaluation subsystem (3) is used for evaluating the client loan application according to the client information input by the client (1) and the preset loan category, and matching the loan category suitable for the client requirement and the loan products corresponding to the category; and the manual service end (4) intervenes and makes analysis evaluation on the client loan application when the input analysis evaluation subsystem (3) cannot automatically evaluate the client loan application according to the rule.
2. The personal property mortgage information entry analysis system of claim 1, wherein the application information includes loan application, interview records, image data, loan application and other data including project information, house information, mortgage information and customer manager opinions;
the data information of the principal lender comprises an identity card, a spouse identity card, an identity certificate, a credit standing certificate and a repayment capability certificate;
the information of the co-applicant data comprises an identity card, an identity certificate, a credit standing certificate, a repayment capability certificate and spouse related information, wherein the spouse related information comprises a spouse identity card, basic information, credit information, a relation with the current bank and income and expenditure information;
the information of the guarantor data comprises an identity card, a spouse identity card, an identity certificate, a credit standing certificate and a repayment capability certificate.
3. The personal property mortgage information entry analysis system according to claim 1, wherein the client (1) collects customer information through an OCR technology and uploads the customer information to the entry analysis evaluation subsystem (3), and the entry analysis evaluation subsystem (3) stores and analyzes and evaluates the customer information; the logging analysis evaluation subsystem (3) comprises:
the system comprises a preprocessing module (301) for preprocessing client information collected by a client;
the characteristic information construction module (302) is used for extracting multi-dimensional characteristic information from the preprocessed customer information and constructing a training set according to the extracted multi-dimensional characteristic information;
the prediction analysis module (303) is used for acquiring customer information and characteristic information to construct a test set, and predicting the test set by using the decision tree so as to obtain a loan application prediction result of a customer; and the matching module (304) is used for matching the loan category suitable for the customer requirement, the loan products corresponding to the category and the matching result of the loan repayment risk of the borrower according to the loan application prediction result, and pushing the loan category and the loan products corresponding to the loan category to the client after the matching is finished.
4. The system for personal property mortgage information entry analysis according to claim 3, wherein the preprocessing module (301) comprises a pre-collecting unit (301 a) and a processing unit (301 b), the pre-collecting unit (301 a) is used for obtaining the historical credit data and credit data of the client according to the client information and transmitting the data and the client information to the processing unit (301 b), the processing unit (301 b) preprocesses the data, and the preprocessing process comprises:
step a: extracting the historical credit data and the credit data or the data in the customer information, and adding the extracted data into a database;
step b: and carrying out knowledge fusion on the knowledge base, wherein the knowledge fusion process comprises entity disambiguation and coreference resolution, and preprocessing data after the knowledge fusion.
5. The personal property mortgage information entry analysis system according to claim 3, wherein the feature information construction module (302) comprises an extraction unit (302 a) and a construction unit (302 b), the extraction unit (302 a) extracts multi-dimensional feature information related to the feature information according to preset extraction rules, the multi-dimensional feature information is uploaded to the construction unit (302 b), and the construction unit (302 b) generates a decision tree according to attributes to train the sub-training set.
6. The system of claim 5, wherein the multidimensional characteristic information comprises personal data to be analyzed and evaluated, which is needed for training and generating the decision tree, and the personal data is used as a variable in the process of training and generating the decision tree, the multidimensional characteristic information comprises but is not limited to customer marital information, spouse information, famous property information, income growth rate and work information, and the work information comprises work sustainable development information, salary floating information and the like.
7. A method for entering and analyzing personal property mortgage loan information entering and analyzing system according to any one of claims 1 to 6, comprising the steps of:
s1: the loan client sends request information for requesting loan application to the system;
s2: the system acquires request information of the client (1), carries out sensitive detection on the request information, and pushes an information input window to the client (1) after the detection is finished;
s3: a client inputs information on line by self through a client (1);
s4: the system analyzes the input information of the client (1) to obtain the customer analysis information of the client (1), and the analysis information is preprocessed, extracted by multi-dimensional characteristic information and subjected to prediction analysis to obtain a loan application prediction result;
s5: the system matches the loan category suitable for the customer requirement, the loan products corresponding to the category and the matching result of the loan repayment risk of the borrower according to the loan application prediction result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010985561.7A CN112102069A (en) | 2020-09-18 | 2020-09-18 | Personal property mortgage loan information input analysis system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010985561.7A CN112102069A (en) | 2020-09-18 | 2020-09-18 | Personal property mortgage loan information input analysis system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112102069A true CN112102069A (en) | 2020-12-18 |
Family
ID=73759712
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010985561.7A Pending CN112102069A (en) | 2020-09-18 | 2020-09-18 | Personal property mortgage loan information input analysis system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112102069A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117764710A (en) * | 2023-12-19 | 2024-03-26 | 北京安泰伟奥信息技术有限公司 | Monitoring method for housing financial risk behaviors |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651570A (en) * | 2016-12-27 | 2017-05-10 | 中国建设银行股份有限公司 | System and method for real-time loan approval |
| CN106897918A (en) * | 2017-02-24 | 2017-06-27 | 上海易贷网金融信息服务有限公司 | A kind of hybrid machine learning credit scoring model construction method |
| CN107945014A (en) * | 2018-01-09 | 2018-04-20 | 安徽润谷网络科技有限公司 | One kind is based on LAOP platform small amount personal loan systems |
| CN108711103A (en) * | 2018-06-04 | 2018-10-26 | 中国平安人寿保险股份有限公司 | Personal loan repays Risk Forecast Method, device, computer equipment and medium |
| CN108765130A (en) * | 2018-05-21 | 2018-11-06 | 北京六行君通信息科技股份有限公司 | A kind of online personal consumption fiduciary loan application assessment matching process and device |
| CN109345261A (en) * | 2018-08-21 | 2019-02-15 | 上海淇毓信息科技有限公司 | A kind of credit cost automatic evaluation system |
-
2020
- 2020-09-18 CN CN202010985561.7A patent/CN112102069A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651570A (en) * | 2016-12-27 | 2017-05-10 | 中国建设银行股份有限公司 | System and method for real-time loan approval |
| CN106897918A (en) * | 2017-02-24 | 2017-06-27 | 上海易贷网金融信息服务有限公司 | A kind of hybrid machine learning credit scoring model construction method |
| CN107945014A (en) * | 2018-01-09 | 2018-04-20 | 安徽润谷网络科技有限公司 | One kind is based on LAOP platform small amount personal loan systems |
| CN108765130A (en) * | 2018-05-21 | 2018-11-06 | 北京六行君通信息科技股份有限公司 | A kind of online personal consumption fiduciary loan application assessment matching process and device |
| CN108711103A (en) * | 2018-06-04 | 2018-10-26 | 中国平安人寿保险股份有限公司 | Personal loan repays Risk Forecast Method, device, computer equipment and medium |
| CN109345261A (en) * | 2018-08-21 | 2019-02-15 | 上海淇毓信息科技有限公司 | A kind of credit cost automatic evaluation system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117764710A (en) * | 2023-12-19 | 2024-03-26 | 北京安泰伟奥信息技术有限公司 | Monitoring method for housing financial risk behaviors |
| CN117764710B (en) * | 2023-12-19 | 2024-06-04 | 北京安泰伟奥信息技术有限公司 | Monitoring method for housing financial risk behaviors |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111652710B (en) | Personal credit risk assessment method based on integrated tree feature extraction and Logistic regression | |
| US8032448B2 (en) | Detecting and measuring risk with predictive models using content mining | |
| US20110238566A1 (en) | System and methods for determining and reporting risk associated with financial instruments | |
| CN110472815B (en) | Risk control method and system for financing enterprise in supply chain financial business | |
| KR20180060044A (en) | Security System for Cloud Computing Service | |
| CN111429258A (en) | Method and device for monitoring loan fund flow direction | |
| CN112561598A (en) | Customer loss prediction and retrieval method and system based on customer portrait | |
| CN113989019A (en) | Method, device, equipment and storage medium for identifying risks | |
| CN112396437A (en) | Trade contract verification method and device based on knowledge graph | |
| CN115545886A (en) | Overdue risk identification method, overdue risk identification device, overdue risk identification equipment and storage medium | |
| CN117556225B (en) | Pedestrian credit data risk management system | |
| CN112950359B (en) | User identification method and device | |
| CN110222180A (en) | A kind of classification of text data and information mining method | |
| CN112102069A (en) | Personal property mortgage loan information input analysis system | |
| CN113269629A (en) | Credit limit determining method, electronic equipment and related product | |
| CN117273968A (en) | Accounting document generation method of cross-business line product and related equipment thereof | |
| CN112949963A (en) | Employee service quality evaluation method and device, storage medium and intelligent equipment | |
| CN111951105A (en) | Intelligent credit wind control system based on multidimensional big data analysis | |
| KR102110889B1 (en) | System for providing AI clause inspection | |
| CN115563176A (en) | Electronic commerce data processing system and method | |
| TWM583089U (en) | Smart credit risk assessment system | |
| CN114611515A (en) | Method and system for identifying actual control person of enterprise based on enterprise public opinion information | |
| Leonard et al. | Automating the credit decision process | |
| US20160092896A1 (en) | Method and system for determining political affiliation and attitude trends | |
| CN113283979A (en) | Loan credit evaluation method and device for loan applicant 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 |