Schedule of Loss Modelling, Reserving and Fraud analytics
| Day 1, Thursday, 3 June | |
| 15:00 - 18:00 | Loss modelling analytics By ANTONIO Katrien |
| Day 2, Thursday, 10 June | |
| 15:00 - 18:00 | Claims reserving analytics By ANTONIO Katrien |
| Day 3, Thursday, 17 June | |
| 15:00 - 18:00 | Insurance fraud analytics By ANTONIO Katrien |
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From 15:00 to 18:00
Loss modelling analytics
By ANTONIO KatrienTopics include:
- data sets used in the course: MTPL and SecuraRe losses
- data handling and visualization tools with {ggplot} and {dplyr}
- building frequency models: Poisson, Negative Binomial, ZI and Hurdle, maximum likelihood estimation and goodness-of-fit
- building severity models: simple to complex parametric distributions, splicing to construct a global fit, mixing, estimating a risk measure.
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From 15:00 to 18:00
Claims reserving analytics
By ANTONIO KatrienTopics include:
- data sets used in the course: individual claims, daily data
- data handling and visualization tools with {ggplot} and {dplyr}
- from daily to yearly data, from individual claims to triangles
- fitting well known claims reserving methods
- when the simple methods fail: what else is there? Case study demonstration.
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From 15:00 to 18:00
Insurance fraud analytics
By ANTONIO KatrienTopics include:
- insurance fraud detection strategies
- network and tabular data
- ranking algorithms, e.g. PageRank, BiRank
- network featurization steps
- supervised learning with imbalanced data, sampling methods like SMOTE
- evaluation metrics, eg AUROC, AUPR, top decile lift
- wrap up.