The complexity of the financial services industry presents a number of challenges that your organization must tackle on a daily basis. Fraud can cause not only financial losses, but also reputational impacts that can be crippling. One of the biggest challenges in this area is that monitoring is done in silos, causing an inability to connect insights across areas to detect complex fraud. With more organizations moving more solutions to the cloud and digital services, detecting fraud is more difficult than ever.
To solve these issues, it's essential to have a centralized tool for data, like Splunk Enterprise Security, as well as the ability to correlate and analyze the data across many different technologies and data sources.
What are the benefits of effective fraud management?
You can benefit from implementing solutions to monitor for active fraud threats and complex behavior patterns. Some of the benefits include:
- Ability to see data from multiple siloed sources
- Reduced false positives and analyst burden
- Detection of threat behavior before a fraud event occurs
What are fraud management best practices?
In order to reduce the threat of fraud, and to actively monitor for incidents, you should implement monitoring and analysis across relevant data sources. These best practices will make your implementation more efficient in detecting fraud.
- Centralize data
- Structured and machine generated data
- Logs, metrics and traces
- On-premise or cloud data
- Existing point solutions
- External data lookups
- Analysis across silos
- Reduced monitoring blind spots
- Track fraud journey across silos
- Fraud modeling across all channels
- Detect complex multi-channel fraud through correlation of log and structured data
- Platform collaboration
- Detection, prevention, investigation, analysis & reporting
- Configure fraud indicators and risk scoring
- Orchestration, automation & case management
- Streaming data, real-time, batch processing
- Team collaboration
- Reduced organizational silos
- Tools consolidation
- Fusion center
- Data reuse, analysis and intelligence sharing across security, fraud, financial crime, and compliance teams