TITLE IU.K. [X1VALUATION AND RISK-BASED CAPITAL REQUIREMENTS (PILLAR I), ENHANCED GOVERNANCE (PILLAR II) AND INCREASED TRANSPARENCY (PILLAR III)]

CHAPTER VIU.K. SOLVENCY CAPITAL REQUIREMENT — FULL AND PARTIAL INTERNAL MODELS

SECTION 3 U.K. Statistical quality standards

Article 231U.K.Data used in the internal model

1.Data used in the internal model shall only be considered accurate for the purposes of Article 121(3) of Directive 2009/138/EC where all of the following conditions are met:

(a)the data are free from material errors;

(b)data from different time periods used for the same estimation are consistent;

(c)the data are recorded in a timely manner and consistently over time.

2.Data used in the internal model shall only be considered complete for the purposes of Article 121(3) of Directive 2009/138/EC where all of the following conditions are met:

(a)data include sufficient historical information to assess the characteristics of the underlying risk, in particular to identify trends in the risks;

(b)data that comply with point (a) of this paragraph are available for all relevant model parameters and no such relevant data are excluded from the use in the internal model without justification.

3.Data used in the internal model shall only be considered appropriate for the purposes of Article 121(3) of Directive 2009/138/EC where all of the following conditions are met:

(a)the data are consistent with the purposes for which it is to be used;

(b)the amount and nature of the data ensure that the estimations made in the internal model on the basis of the data do not include a material estimation error;

(c)the data are consistent with the assumptions underlying the actuarial and statistical techniques that are applied to them in the internal model;

(d)the data reflect the relevant risks to which the insurance or reinsurance undertaking is exposed;

(e)the data are collected, processed and applied in a transparent and structured manner, based on a specification of the following areas:

(i)

the definition and assessment of the quality of data, including specific qualitative and quantitative standards for different data sets;

(ii)

the use and setting of assumptions made in the collection, processing and application of data;

(iii)

the process for carrying out data updates, including the frequency of regular updates and the circumstances that trigger additional updates.

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