Page 335 - Special Topic Session (STS) - Volume 1

STS441 Olivia H.

The integration of micro-data sets into a macro-
prudential regulatory landscape,
exemplified by the AnaCredit regulation
Olivia Hauet
Nordea Bank, Stockholm, Sweden

Abstract
By introducing the AnaCredit regulation, the European Central Bank (ECB) has
taken the concept of data-driven regulatory reporting to an unprecedented
level. In addition to an ever-increasing burden of traditional template-based
reports serving both supervisory and statistical purposes, credit institutions of
the Euro area are requested to deliver micro-data on a loan-by-loan and
borrower-by-borrower level on a monthly and quarterly basis. The data are
compiled according to precise definitions and organised into an entity-
relationship model.
This innovative approach to data collection within the banking sector is
premised on the following principles: any aggregated data can be obtained
from granular data, but the reverse is not true – granular data enabling both
drill-down and roll-up analysis; in order to be comparable, data need to be
harmonised and standardised by way of common definitions and standards;
data are of better quality when they are organised in a model reproducing
business reality and input systems to the extent possible; top-down indicators
calculated from granular data are not necessarily known in advance as new
indicators can emerge from correlations observed between the underlying
data.
Ultimately, this approach should alleviate the reporting burden put on credit
institutions since new macro-prudential indicators will be possible to compute
from already collected data. In the longer term, and to the extent that rules for
data dissemination across the national and European authorities allow, it could
also establish a bridge between statistical and supervisory needs.
This article explores, by illustrative examples, how some of the caveats of the
AnaCredit regulation, from its conception to its application, may impede the
fulfilment of its double objective, with regards to the collection of high-quality
granular credit data across the Euro area and to the reduction of the reporting
burden. It concludes by the necessity to break the remaining silos within banks
but also within national and European authorities, and to pursue the work
initiated on a larger scale, through initiatives such as the Banks’ Integrated
Reporting Dictionary (BIRD) and the Integrated Reporting Framework (IReF).

Keywords
granular data, credit data, standardisation, data model, data dictionary

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