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Provectus > 实例探究 > 基于机器学习的自动化欺诈检测平台:扩展信任和安全
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Appen's Transformation: From Manual to Automated Fraud Detection with AI/ML

技术
  • 分析与建模 - 机器学习
  • 网络安全和隐私 - 入侵检测
适用行业
  • 水泥
  • 教育
适用功能
  • 产品研发
  • 质量保证
用例
  • 欺诈识别
  • 预测性维护
服务
  • 数据科学服务
  • 培训
挑战
澳鹏需要自动化其手动欺诈检测机制,以更有效地检测和防止其平台上的恶意活动。他们希望扩大每天可以监控的分布式工作人员的数量,并减少分布式工作人员完成的体力工作量。
关于客户
澳鹏是一家为大规模构建有效人工智能系统的组织提供高质量培训数据的领先提供商。他们集成了Figure 8(一个由人工智能/机器学习驱动的人机交互平台),可以更有效地将文本、图像、音频和视频数据转换为高质量的训练数据。
解决方案
Provectus 使用 TensorFlow 和 AWS 产品设计并构建了一个具有人机交互功能的自动化端到端欺诈检测平台。他们开发了数据管道、训练了 ML/DL 模型,并创建了用户友好的 Web 应用程序,以高效处理和管理数据和警报。
运营影响
  • The new ML-powered fraud detection platform brought about significant operational improvements for Appen. The platform enabled the team to process and handle 20x more jobs per day, with almost 97% of all jobs handled automatically. This increased efficiency led to a 25% reduction in scammer activity and a 5x drop in churned judgements. The platform also resulted in greater productivity and efficiency of staff, as Appen managed to avoid hiring 20+ data analysts, thereby considerably reducing operational costs. Most importantly, the new fraud detection platform helped Appen meet the customers’ requirements in regard to data quality and service efficiency. The changes made allowed the company to better satisfy existing and attract new enterprise clients, accelerating their global expansion.

数量效益
  • Appen managed to scale trust and security of the platform, which allowed them to manage 20x more jobs per day

  • Appen's new platform detected 25% more scammers

  • 97% of all jobs were handled automatically

相关案例.

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