GRA · Actuarial and Quantitative Risk
Spatial financeWhere capital meets hazard, exposure and transition
Innovation and practical technology
Quantitative practice is changing: machine learning in pricing and reserving, climate-conditioned event sets, open modelling frameworks and new longevity data. The platform studies each for model risk and transparency and promotes no tool.
The order things happen in.
- 01Draftsources cited, labels attached
- 02Evidence checkevery value traced
- 03Independent reviewconflicts declared
- 04Editionpublished with its limits
- 05Correctiona new version, never a silent edit
Evaluate before adopting.
- 01
Need
Which problem does the technology address, and for whom?
- 02
Evidence
What has been demonstrated, under what conditions, and what remains untested?
- 03
Constraints
Cost, skills, infrastructure, data and governance requirements.
- 04
Consequences
Effects on safety, rights, equity and the environment.
Practice and questions.
| Change | Question |
|---|---|
| Machine learning in pricing | Explainability and fairness |
| Climate-conditioned event sets | Validation |
| Open modelling frameworks | Comparability |
For each change, Actuarial and Quantitative Risk asks what new dependency, concentration or model risk it creates for actuaries, and which of IAA, EIOPA and IAIS has addressed it so far.
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Questions and answers.
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