Ernst & Young: Using Tableau for Fraud Analysis
公司规模
1,000+
地区
- Europe
国家
- United Kingdom
产品
- Tableau
技术栈
- SQL
- Oracle
实施规模
- Departmental Deployment
影响指标
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 数据挖掘
- 应用基础设施与中间件 - 数据可视化
适用行业
- Professional Service
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
Ernst & Young is a global leader in assurance, tax, transaction, and advisory services. The company has a Fraud Investigation and Dispute Services (FIDS) practice that works in a broad spectrum of providing analytical services related to identifying factors related to fraud and forensics. They also work within investigations, and they work within the anti-bribery and corruption fields as well. The FIDS team analyzes all types of fraud that can be coming from all types of different data sets, whether or not those data sets are transactional data in form. They also try to uncover elements of unusual patterns or unusual behavioral activity within unstructured data sets of text data – such as emails, instant messages, or SMS text messages that are exchanged in an organization from employee to employee.
挑战
Ernst & Young's Fraud Investigation and Dispute Services (FIDS) practice works in a broad spectrum of providing analytical services related to identifying factors related to fraud and forensics. They analyze all types of fraud that can be coming from all types of different data sets, whether or not those data sets are transactional data in form. They also try to uncover elements of unusual patterns or unusual behavioral activity within unstructured data sets of text data – such as emails, instant messages, or SMS text messages that are exchanged in an organization from employee to employee. The challenge was to analyze these large volumes of data and present the results in a way that is easily understandable by a variety of individuals across an organization—from analysts and end users right up to C-suite professionals.
解决方案
Ernst & Young uses Tableau for data visualization. They perform all of their analytics within SQL and compute fraud scores that will identify errors that need further investigation. Those computations are then fed directly into Tableau. Tableau outputs them very quickly into a visual format, so they’re very easy to understand. For instance, they have four-dimensional charts that help to hone in on individuals that may need further investigation. They connect to different databases directly, which they find to be a very useful feature. It gives them lots of transferability with regards to their underlying data structures. They work with SQL. They work with Oracle. They work with a whole variety of different databases.
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