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Databricks > 实例探究 > AT&T 利用 Databricks Lakehouse 平台进行主动欺诈检测的旅程
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AT&T's Transformation: From Legacy Infrastructure to Cloud-Based Lakehouse for Enhanced Fraud Detection

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
  • 建筑与基础设施
  • 零售
用例
  • 欺诈识别
  • 实时定位系统 (RTLS)
服务
  • 数据科学服务
  • 培训
挑战
AT&T 面临着其传统本地数据架构的挑战,该架构在检测欺诈方面旷日持久、效率低下且反应迟钝。他们还努力获得实时洞察和自动化以优化调度。
关于客户
AT&T 是一家拥有 1.82 亿无线客户的通信服务提供商。他们致力于为客户提供安全可靠的通信,但面临欺诈攻击和运营效率低下的挑战。
解决方案
AT&T 在云中实施了 Databricks Lakehouse 平台,以实现其数据基础设施的现代化。他们使用数据和人工智能来提供用于欺诈检测和预防的预测解决方案。通过迁移到云端并利用机器学习模型,AT&T 能够在欺诈发生之前主动阻止欺诈。
运营影响
  • The migration to Databricks Lakehouse has significantly improved AT&T's operational efficiency. The company has been able to proactively stop fraud before it happens, reducing fraud by up to 80% with over 100 fraud detection ML models in production. The new system has also enabled real-time, automatic fraud detection, replacing the previous rules-based system. This has not only saved millions of dollars in potential fraud costs but also improved the customer experience. The company now has a robust roadmap to deliver more data-driven solutions that will help to democratize AI across the business. AT&T is also planning to increase adoption for use cases benefiting dispatch, service reliability, quality of coverage, and sales growth.
数量效益
  • 80% decrease in fraud attacks
  • Millions of dollars saved in potential fraud costs
  • Over 100 ML models in production for fraud detection

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