Can you look around the corner and see where fraud and compliance risk lurk within your organization?
While 80 percent of governance and compliance professionals say they feel the pressure to use data analytics, less than 30 percent are incorporating detection or analytic techniques to monitor for potential fraud at their companies.
Many organizations have started to advance beyond basic compliance reporting, however, organizations should go a step further–incorporating predictive models, leveraging third-party data and evaluating connections and relationships–in order to realize greater benefits and cost savings that can only be achieved through more sophisticated analytics and capabilities. Armed with data analytics, compliance officers bring even greater value to their organizations.
Highly Reactive
Highly Reactive
- Focus on strength of organizational culture
- Development of robust compliance policies, procedures and controls
- Sampling techniques
- Reactive reviews
- Hotline-driven Investigations
Some Proactive
- Investigations teams
- Business rules and anomaly detection to identify potential risks
- Evaluation of 3rd party data
- Cover up to 100% of transactional data
- Recurring internal, external, and supplier/distributor audits
Highly Proactive
- Real-time predictive models
- Extensive use of text and network analytics
- Ongoing refinement including artificial intelligence and machine learning
- Opportunity for collective intelligence; aggregated data and knowledge sharing between organizations to maximize detection efforts
The prospect of standing up a robust data analytics program can seem overwhelming. To help organizations think this through, we discuss the following in this point-of-view:
- Regulator expectations and enforcement sensitivity around fraud detection
- How organizations are using analytics to identify risk today
- The use of analytics within enterprise governance
- The steps organizations can take to prepare for the future.
Download and read the point of view below.
