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CP10 (Full Document) - European Banking Authority

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etween systems, recording of data that are excluded or introduced<br />

at different stages of data manipulation, etc. Significant<br />

discrepancies should be investigated.<br />

444. Institutions should work on an ongoing basis to ensure that their<br />

data is of good enough quality to support their risk management<br />

processes and to calculate their capital requirements.<br />

445. Institutions should define their own standards for ensuring data<br />

quality and should look to develop and improve these over time. It is<br />

the institutions' responsibility to ensure the quality of their data. The<br />

institutions should be able to demonstrate that they achieve high<br />

standards in terms of coverage, completeness and correctness of<br />

their data. Examples of activities aiming to improve the data quality<br />

standards are:<br />

· the construction of decision trees to assign losses to event type<br />

and business lines;<br />

· the computation of average time between when loss events<br />

occurred and when they are captured;<br />

· the review of the structure of input data to identify outliers or<br />

implausible values and changes from previous periods;<br />

· periodic cross checking against material accounting data with<br />

institutions needing to identify and explain material divergences.<br />

446. There should be minimum checks by an independent function to<br />

ensure that internal data are comprehensive and external data are<br />

relevant. Supervisors could assess specific parts of this process to<br />

verify the conclusions reached by the independent function.<br />

447. Institutions should have policies concerning their tolerance for any<br />

gaps in their internal data. They should also be able to fully justify<br />

their approaches to adjusting values.<br />

Data documentation<br />

448. While all the relevant documentation should be available for<br />

assessment by supervisors, the following types of documentation are<br />

essential:<br />

· Data policy and statement of responsibility: Institutions should<br />

establish an explicit data policy.<br />

· Institutions should document work­flows, procedures and systems<br />

related to data collection and data storage.<br />

· Data directory: Institutions should have clear definitions of data<br />

items that are made available for inspection by supervisors.<br />

· Database descriptions: <strong>Document</strong>ation for material databases<br />

should be sufficient to allow institutions to provide supervisors<br />

Page 105 of 123

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