Data challenges in actuarial science and regulation



1) RGPD: Actuarial Regulatory Issues and constraints

  • data: a growing need and a universal theme, local debates
  • deciphering the principles of the RGPD and the impacts of data manipulation in the models
  • data privacy officer: embodying data protection, spreading a culture within the company
  • key compliance steps for insurers
  • the practical consequences for the insurance industry: actuaries, risk managers, data scientists, etc.

2) Comparison of internal vs. external data 

the challenges for the insurance industry
Quality of the data defined by Solvency 2: completeness, depth of history, accuracy
similarities and differences between internal and external sources: volume, velocity, variability, truthfulness
common aggregation and anonymization issues
regulation of price discrimination in insurance
business licences

3) Open Data: valuation of external data

  • plurality of sources
  • reliability assessment
  • operating techniques for actuarial models
  • application examples

4) API: operation, integration and constraints

  • many modes of operation
  • commercial vs. open-source use
  • integrability into established processes
  • demonstration of sustainable use
  • focus on regulatory constraints to date

5) Webscrapping: techniques and applications

  • definition
  • legal aspect: case law in insurance and elsewhere
  • good practices
  • interact with web pages
  • tool presentation
  • actuarial examples and feedback

6) Data acquisition project: collection and exploitation of external data to produce an original statistical report.