H20.ai for Payment Fraud
公司规模
1,000+
地区
- America
国家
- United States
产品
- H2O Driverless AI
- H2O open source
- H2O MOJO
技术栈
- Machine Learning
- Big Data
- Automated Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
技术
- 分析与建模 - 大数据分析
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 欺诈识别
服务
- 数据科学服务
关于客户
The customer in this case study is not explicitly mentioned. However, it can be inferred that the customers are leading banks, payment processors, and credit card companies that are struggling with the challenge of fraud detection. These financial institutions are grappling with the balance between enabling spending, stopping fraud, and maintaining customer relationships. They are also dealing with the challenge of managing new data sources from mobile apps and third-party providers, which while helpful in improving fraud detection, also create new issues for their fraud and risk management teams. These teams are already struggling with rules and statistical modeling systems and limited resources.
挑战
Fraud is a significant problem in financial services, with fraudsters constantly changing their tactics. Fraud detection is a balance between enabling spending, stopping fraud, and closing the loop with customers. However, new data sources from mobile apps and third-party providers can help improve fraud detection, but the increase in data size and variety creates new issues for fraud and risk management teams. These teams are already struggling with rules and statistical modeling systems and limited resources. Fraud cost US financial institutions almost $10 billion in 2018 and is a key issue for regulators. Customer acquisition and retention, however, is top of mind for many bank executives with new competitors from fintech startups to technology companies jumping into payments. Fraud and resulting customer churn can significantly impact profitability, customer trust, and regulatory compliance.
解决方案
H2O.ai provides a platform that is used by leading banks, payment processors, and credit card companies to stop fraud and improve customer experiences. The platform has a unique combination of capabilities ideally suited to prevent fraud and improve customer experiences at the same time. H2O Driverless AI is a powerful automated machine learning system with a unique, evolutionary model for discovering signals in data that will lead to more accurate production models. This automated process runs on the most powerful computing environments to discover new data features and techniques in hours, not days or weeks, while fraud occurs. With these new features and optimized modeling techniques in hand, data scientists can build new AI models using all the available data using the H2O open-source modeling environment. The H2O MOJO is an ultra-low latency scoring model that customers can deploy anywhere. This highly optimized approach is ideally for fraud detection, where decisions happen in milliseconds.
运营影响
数量效益
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