Fraud costs businesses millions of dollars per year, and the resources and effort required to mitigate fraud can take precious focus way from core business initiatives. But enterprises must address this critical issue, if they are to protect their interests and the interests of their partners and customers. While one may think of fraud most commonly associated with financial and banking organizations or IT functions or networks, industries like healthcare, government and public sector are also at risk. And fraud can take many forms and affect the supply chain in numerous ways.
The good news is that a business can more readily and effectively anticipate fraud by identifying the signs and signals that indicate a problem and creating strategies and processes to monitor and manage risk so that the incidence of fraud is significantly decreased.
An enterprise can leverage predictive analytics to identify the most likely areas and actors that will be involved in fraudulent activities and by developing fraud detection models, the enterprise can reduce the cost and the negative impact to the business reputation and to the bottom line. Businesses that are proactive in identifying these risks can better optimize resources and respond to changing trends and patterns.
With the right tools, algorithms and assisted predictive modeling techniques, your business can create fraud behavior models and monitor ongoing activity to get ahead of the problem and to identify critical gaps or holes in processes, systems and activities.
Use Predictive Modeling and Predictive Analytics to create a profile of fraud risk and to manage and monitor fraud.
Learn More: Fraud Mitigation
We invite you to explore other use cases and discover how predictive analytics, and assisted predictive modeling can help your business to achieve its goals.
- Customer Targeting
- Product and Service Cross-Sell and Upsell
- Quality Control
- Demand Planning
- Human Resource Attrition
- Maintenance Management
- Loan Approval
- Marketing Optimization
- Predictive Analytics Using External Data
- Online Target Marketing
- Customer Churn
Learn more about Augmented Analytics, its uses, techniques and applications.
Contact Us today and find out how Predictive Analytics can increase the accuracy of predictions and improve risk avoidance and fraud monitoring processes.
Original Post: Predictive Analytics Use Case: Fraud Mitigation!Share