信贷数据宝居民信用贷款能力分析数据

1.数据适用范围：温州市及部分浙江省地区
2.数据内容：通过统计居民不动产权信息、车辆信息、企业信息、公积金缴存信息、社保参保信息等数据集来分析居民可支配收入能力情况。
数据应用场景：对公共数据授权运营平台的公共数据进行分析挖掘，通过公积金、社保、不动产等数据分析居民可支配收入能力情况，人均可支配收入的增加代表居民偿还贷款能力的增长。为金融机构贷前业务授信额度提供测算依据，为金融机构提供贷中管理的还款人还款情况进行风险评估服务，支撑金融机构贷款业务落地闭环。1.数据清洗：对数据集进行清洗，包括去除异常数据、处理缺失值
2.数据转换：将隐私信息进行掩码、关系映射、截断、泛化或分档等脱敏策略进行加工。
3.数据获取：根据姓名和身份证号对用户发起授权，用户同意后获取用户产权、产权抵押、车辆、企业、公积金缴存、社保参保相关信息。
4、计算规则：将上述信息与用户画像标签库匹配得出房产分值A、车辆分值B、产权抵押分值C、权利人分值D、公积金分值E、社保参保分值F，按照加权算术平均法计算最终得分，即：匹配计算结果=（A+B）*X权重+（C+D）*Y权重+(E+F)*Z权重。结果分值越高，表明居民人均可支配收入能力高，还款能力高，贷款额度高。

1. Scope of Data Application: Wenzhou City and parts of Zhejiang Province.
2. Data Content: Analyze residents' disposable income capacity by integrating multiple datasets including residents' real estate ownership information, vehicle information, enterprise information, housing fund contribution records, and social insurance participation records.
Data Application Scenarios: Perform analysis and mining on public data from the public data authorized operation platform. Analyze residents' disposable income capacity through data such as housing fund, social insurance, and real estate; an increase in per capita disposable income indicates growth in residents' loan repayment capacity. This provides a calculation basis for financial institutions to determine pre-loan business credit limits, conducts risk assessment services for financial institutions by evaluating borrowers' repayment status during loan management, and supports the closing loop of financial institutions' loan business operations.
1. Data Cleaning: Clean the dataset by removing abnormal data and handling missing values.
2. Data Transformation: Process sensitive information using desensitization strategies such as masking, relational mapping, truncation, generalization, or binning.
3. Data Acquisition: Initiate user authorization based on their name and ID number, and obtain information related to users' property rights, property right mortgages, vehicles, enterprises, housing fund contributions, and social insurance participation after obtaining user consent.
4. Calculation Rules: Match the aforementioned information with the user profile label library to derive property score A, vehicle score B, property right mortgage score C, right holder score D, housing fund score E, and social insurance participation score F. Calculate the final score via the weighted arithmetic mean method, as follows: Matching Calculation Result = (A + B) * X Weight + (C + D) * Y Weight + (E + F) * Z Weight. A higher result score signifies higher per capita disposable income capacity of residents, stronger repayment capacity, and higher approved loan quota.

搜集汇总

数据集介绍

特点

该数据集包含511条居民信用贷款能力分析数据，每日更新，涵盖产权、车辆、企业、公积金、社保等信息，用于评估居民可支配收入能力和贷款风险，为金融机构提供授信和风控支持。数据经过清洗和脱敏处理，采用加权算术平均法计算得分。