In Chapter 10 there is a very small section on the importance of data quality under SII. The second reason it is deemed crucial is that it allows: the application of a wider range of methodologies for calculating the best estimate, which improves the chances of application of adequate and robust methods for each case. How does data quality allow for a wider range of methodologies? I thought the best estimate had to be calculated using the prescribed methodology under SII? Thank you
Here's an example: having good data might facilitate using a stochastic model for valuing options / guarantees, rather than having to take a more approximate 'option pricing' type approach.
Hi Another small question for Chapter 10: - we are given the example that ancillary own funds could be unpaid shareholder capital, could it also include a contingent loan? - is it true that a mutual would not be expected to have ancillary OF, but if they did it would only be as a result of an exceptional injection of capital, perhaps from the same provider of seed capital? Thank you,
Hi Another small question: - would it ever be appropriate to use model points instead of policy data for the calculation of regulatory capital requirements? I think the answer would be no, though they might possibly be used in the ORSA or equivalent (depending on the jurisdiction). Thank you
Model points can be used under Solvency II, provided certain conditions are met - including being able to validate that they give a result that is sufficiently accurate.
This is a minor and relatively obscure part of the SA2 course. If you want to read up more on ancillary own funds (although not something that I would recommend as a good use of precious study time!) the following might be of interest: https://www.bankofengland.co.uk/-/media/boe/files/paper/2020/december/gl-ancillary-own-funds.pdf https://register.eiopa.europa.eu/CE...unds-Criteria-supervisory-approval-of-AOF.pdf
