Concordia University

https://www.concordia.ca/content/shared/en/events/artsci/math-stats/2019/12/06/msc-thesis-defence-in-mathematics11111.html

Workshops & seminars

Dong Qiu - MSc Thesis Defence

Individual Claims Reserving: Using Machine Learning Methods

Date and time
Date & time

December 6, 2019
10 a.m. – 12 p.m.

Where
Where

Room 921-04
J.W. McConnell Building
1400 De Maisonneuve W.
Sir George Williams Campus

Cost
Cost

This event is free

Wheelchair accessible
Wheelchair accessible

Yes

Contact
Contact

Carmelina Buffone
Ext. 3250

Speaker:  Mr. Dong Qiu (MSc)

Abstract:  To date, most methods for loss reserving are still used on aggregate data, arranged in a triangular form such as the Chain-Ladder (CL) Method and the over-dispersed Poisson (ODP) Method. With the booming of machine learning methods and the significant increment of computing power, the loss of information resulting from the aggregation of the individual claims data into accident and development year buckets is no longer justifiable. Machine learning methods like Neural Networks (NN) and Random Forest (RF) are then applied and the results are compared with the traditional methods on both simulated data and real data (aggregate at company level).

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