ROE solutions offers a unique approach to quality management in the (re)insurance industry based on a  four pillar approach designed specifically for (re)insurance processes.

Why consider a QM approach?
 

Every (re)insurance carrier, big or small, has a data need for internal & external reporting as well as managing/steering the business. Much of this data is needed for processes in real-time. Whether it is a regulatory mandate or for internal management, quality data is foundational for all functions within the (re)insurance value chain. Whatever the need is, (re)insurance professionals do not want and cannot afford to make decisions or report poor or incorrect data. QM is often a forgotten or overlooked element but, when implemented well, can represent a true competitive advantage.

 

Four Pillars of QM

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People

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No quality can be achieved without first talking about the people involved in the process and management of an organization’s data. Those involved are not only employees but also customers and third parties. There must be a palpable culture created among employees to be stewards of maintaining the necessary quality standards within an organization for internal and external use.

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Process

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Any attempt in improving quality without first analyzing the process landscape will not lead to the required goals. A well-defined process landscape is not only necessary for initially implementing but also sustaining QM, while also being a prerequisite for system upgrades and implementations. All processes need to be defined with the respective controls clearly defined. This will lead to a significant improvement on the risk management side as well.

Systems
 

A new or upgraded system alone will not lead to a higher level of quality but a good system will help to get the business users to a higher level of efficacy. Systems can also lend further support to reaching desired quality levels via additional system/automated controls.

 

Data

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Data quality cannot be achieved without defining and maintaining the other three pillars well. Therefore, we always suggest to look at the QM model first before starting a data clean-up project, as these types of endeavors are short-term solutions rather than long-term QM enterprise frameworks.

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In many cases our clients are facing tight deadlines to achieve higher data quality. This can be achieved with technology, and as such, we partner with technology companies who bring the required tools and solutions to meet our clients’ needs.  

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Our main services implement an enterprise data quality framework or a sub-unit/specific function as a pilot program. These offerings often go run in parallel to system implementations. One of our specialties is to address (re)insurance related issues in a confined environment and bring higher and sustainable quality in a short time frame.

Pricing

We believe in transparency, upfront and often. Pricing for our QM subject matter experts is set-forth below:

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Quality Management SME - $165/hr