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Innovative Reserving process in non-life insurance

Date

Apr 30 2021
Expired!

Time

16:00 - 17:00

Category

Conference,
Congress,
Properties & Casualties,
Reserving
présentation de l'événement, titre, date et horaires
Innovative Reserving process in non-life insurance
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Annual e-Convention of the German Actuarial Associations DAV and DGVFM

Key addactis® speakers:
Thomas LALLEMENT | Senior Consultant P&C Modeling & Risk
Bryan GAUTIER | Consultant P&C Modeling & Risk

Our two addactis experts will exemplify a new reserving approach concerning advantages and challenges of individual claim analysis and forecasting, based on data science, at the annual e-conference of German Actuarial Associations DAV and DGVFM e-Conference.

Our experts will present you the following topic:

Innovative Reserving process in non-life insurance: a challenge for Risk Management

Recent surveys carried out among various market players have shown that aggregated reserving methodologies remain preferred in the calculations of non-life insurance reserves. However, the recent development of Machine Learning in actuarial sciences allows the emergence of new visions of claims and show a growing interest in new ways to estimate reserve based on individual assessment.

This presentation presents a new way to integrate these methods by the actuarial reserving team to produce a complete and innovated process.

The use of data analysis and data science techniques helps to complete the database if necessary, to better understand the impact of each of the variables on the claims experience, and thus to define finer homogeneous cohorts and large claims thresholds better adapted to the underlying risk.

These preliminary analyses make it possible, for example, to anticipate the future deterioration of specific cases using a segmentation model for serious and attritional claims. It is also interesting to consider individual reserving within the different cohorts created, especially when the development of claims strongly differs. This is precisely what the ASICR methodology offers: within each of the cohorts, an individual assessment of the future development of a case is estimated from an average of the historical developments observed, weighted by the proximity of the claims records to each other.

Reserving can therefore be approached in a different way, with a global and innovative process starting with a precise data analysis and ending with an individual estimate of its reserves. In particular, this enhances the use of data available by the insurer in order to help it define an appropriate risk management policy, in view of the risk profiles that could affect its profitability.

 

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Key words: Non-life insurance, Reserving, Individual Reserving, Data Science, CART, Link Ratio

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