对公流水贷风控综合解决方案

我国大多数的中小微企业，普遍存在抗风险能力较弱、财务信息不透明等问题，银行难以对其偿债能力进行准确评估。针对这个痛点，本方案从数据、策略及模型三方面帮助银行有效地识别和控制申请欺诈和信用风险，提供线上信贷全生命周期服务。 数据层面：依托丰富的特征工程业务实践，从业务角度和算法角度构建海量的特征库，覆盖企业流水、个人征信报告、对公征信报告等多个领域。 策略层面：面对高频、复杂多变的业务场景下，基于流水数据构建企业风控策略全景图，实现快速精准决策，帮助金融机构提升风险决策水平。 模型层面：借助稳定、可解释的机器学习算法，基于样本数据提供定制化的贷前申请评分模型，能够有效的区分违约客户和正常客户，协助机构管控信用风险。

Most small and medium-sized enterprises (SMEs) in China generally face challenges such as weak risk resilience and opaque financial information, making it difficult for banks to accurately evaluate their solvency.
To address this critical pain point, this solution assists banks in effectively identifying and mitigating application fraud and credit risks across three dimensions: data, strategy and model, while providing end-to-end online credit lifecycle services.

Data Dimension: Leveraging rich business practices in feature engineering, this solution constructs a massive feature repository from both business and algorithmic perspectives, covering multiple domains including enterprise bank statements, personal credit reports and corporate credit reports.

Strategy Dimension: In high-frequency, complex and volatile business scenarios, this solution builds a comprehensive enterprise risk control strategy map based on bank statement data, enabling fast and accurate decision-making and helping financial institutions enhance their risk decision-making capabilities.

Model Dimension: Utilizing stable and interpretable machine learning algorithms, this solution provides customized pre-loan application scoring models based on sample data, which can effectively distinguish defaulting customers from normal ones and assist institutions in managing and controlling credit risks.

搜集汇总

背景与挑战

背景概述

该数据集名为'对公流水贷风控综合解决方案'，由北银金融科技有限责任公司苏州分公司提供，应用于人工智能领域，交付类型为数据模型。数据集旨在帮助银行评估中小微企业的偿债能力，通过数据、策略及模型三方面识别和控制申请欺诈和信用风险，提供线上信贷全生命周期服务。具体包括流水特征挖掘、风控策略挖掘和信用评分模型等功能。