Context
Insurance fraud - a billion-dollar business for criminals and opportunists
Companies need to better understand their customers and their own customer-centric processes in order to set up suitable controls at the right execution points and implement them seamlessly in the process flow. Documented processes and metadata help to keep the factors influencing decisions along the handling processes transparent and traceable.
By continuously adapting their prevention and analysis measures, companies can react to evolving fraud patterns. This requires the creation of technical prerequisites and a dynamic, interdisciplinary, cooperative environment between specialist and technology units. Cyclical testing and simulations make a significant contribution to expanding and maintaining the quality of fraud detection mechanisms.
Companies need diverse and sophisticated capabilities to enable timely, data-driven analyses - in the areas of data collection, data management and analytical tools. Only with the right skills can fraud patterns be identified quickly and suitable countermeasures taken. The quality and availability of the data basis plays just as important a role as the selection of suitable technology.
An effective operating model for a fraud management system is more than just measuring fraud performance metrics. It manages the interactions between fraud detection, its impact on the effective costs and savings achieved and customer satisfaction. A key aspect is continuous development. New fraud patterns, changes to customer products and applications must be incorporated into the fraud system on an ongoing basis. Empowering employees and assigning roles to perform the necessary tasks and responsibilities helps to ensure the sustainable operation of a fraud solution.
Our approach
#1
Explore the Business
We analyze your initial situation with regard to fraud analytics and the threat situation of the company or business unit. On this basis, we work with your management to derive the appropriate fraud management strategy.
Leading questions:
- How high is the fraud risk in the process area under consideration?
- How high is the potential benefit for fraud analytics?
Leading question:
- Which Fraud Analytics Management Strategy fits the existing business and data strategy?
#2
Identify Fields of Action
The analytics, data & operating model capabilities are aligned with the data strategy. We derive measures and recommendations for data-driven fraud detection and continuous adaptation to new fraud risks.
Leading question:
- Which analytical skills for fraud detection are available and which need to be supplemented?
Leading question:
- What activities along the data and technologies for analysis and automation in fraud detection are necessary?
Leading question:
- How and with what skills & resources are operations and continuous innovations ensured?
#3
Set Direction
We support your teams during implementation or take on project responsibility - from rollout to operation.
Main tasks
- Planning and management of the fraud analytics management project - from business case to implementation.
Main tasks
- Coaching and support for further development cycles to expand and maintain the value of the Fraud Analytics Management System.
Your added value
Proven approach
Our process model is standardized and ensures high quality and predictability.
360° perspective
You will receive a 360° view of your fraud prevention potential and recommendations for setting up your fraud analytics management system.
Neutral point of view
We offer a provider-neutral view of your specialist and IT solutions and can therefore provide you with optimum support in the further design.
Further information
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