CMF®, Claims Management Filter®, is a high-end data analytics tool that makes handling claims much more efficient, resulting in both lower costs and lower claims. By using machine learning algorithms, the quality also increases. The tool has now been implemented in 8 countries. In the animation you can see the power of CMF® in a nutshell. Our combined technical and statistical filter for the claims management process offers different types of solutions:
CMF® determines per claim which steps need to be taken. Claims handlers are therefore only used for necessary cases.
The reports that follow from CMF® provide insight into the claims handling and points for optimization.
CMF® offers optimal control with savings in both costs and time without compromising the quality of the repair.
CMF® carefully checks each claim for all relevant variables.
CMF® provides monthly advice on improving technical and statistical rules.
Check for fraudulent claims, because CMF® analyzes large amounts of data in no time.
Not so long ago, the period between a car accident, the claim process and the moment the vehicle became available would easily take weeks. Read in the whitepaper how CMF® provides convenience in the claims handling process.
The technical rules are the business rules that a claim must meet. Examples are: “The hourly rate for labor may not be higher than € …” or “If the point of application of the damage is left, no parts from the right side may be entered.”
A database is formed from the customer’s data. This database serves as the basis for the statistical test for the claims that are assessed by CMF®. The database and the test are constantly kept up-to-date. In this way, the profitability of the company increases substantially!
Depending on the results of the technical rules and statistical test, CMF® provides an advice that is appropriate to the method of claim handling. Possible advice is for example:
A. Pay out
B. Call the customer for more information or do tele-expertise
C. Send an expert.
The statistical test is arranged per customer with the available data. Modern models from statistics and machine learning are used to make the test as accurate as possible.
Determine on the basis of scores how a claim relates to the market. It is checked whether the costs of materials and labor are in line with similar claims.
Not just software, but software validated by a committee of scientists in the Netherlands.
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