November 2016

AnaCredit Analytical Credit Dataset of the ECB - ImplementationChallenges and Approaches

THE AUTHORS

Sergio Gianni is a partner at Avantage Reply. Sergio has over 20 years of experience in

Prudential Risk, Finance and Regulation. Prior to establishing Avantage Reply Italy in 2008,

he worked for two large consultancies. His expertise includes credit risk management,

financial analysis, compliance and cover both the setting of governance, strategy, model

development and validation as well as their implementation in policy, system development

and regulatory reporting. He has also contributed articles to various publications and

frequently speaks in industry conferences.

Sergio Gianni

About Avantage Reply

Established in 2004, Avantage Reply (a

member firm of Reply) is a pan-European

specialised management consultancy de-

livering change initiatives in the areas of

Compliance, Finance, Risk and Treasury.

Website: www.avantagereply.com

Oscar McCarthy is an associate partner at Avantage Reply. He has sixteen years of

professional experience in commercial and investment banking, covering all major risk

types (credit, market, operational, liquidity and strategic) and the associated prudential

regulations. His areas of expertise include both the setting of the risk governance,

strategy and appetite as well as their implementation in policy, methodology and

reporting. He has a Ph.D. in Mathematics, and is certified as a Professional Risk Manager.

Oscar serves pro-bono on the Board of the Professional Risk Manager’s International

Association, and is the editor of the Professional Risk Manager’s Handbook (market risk).

Oscar McCarthy

Rob Konowalchuk joined Avantage Reply UK in September 2016 as an associate partner,

having spent his career in various advisory roles within financial services risk and regulation.

With 16 years of experience in the financial services sector (primarily banking and capital

markets), Rob has become an expert in a broad range of issues facing financial services

firms, particularly in prudential risk and regulation. With a background in accounting and

auditing, Rob applies expertise in governance, controls, systems and data to design and

deliver change and remediation programmes, primarily driven by prudential regulation

(with a focus on capital and liquidity management, regulatory reporting, capital planning

and stress testing, and recovery and resolution planning). Rob has a degree in Business

Administration and is qualified as a chartered accountant in the UK and Canada.

Rob Konowalchuk

TABLE OF CONTENTS

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1

Abstract

Overview

National Central Credit Registers as a starting point

The new approach to expanded statistical and supervisory reporting within the SSM

How Avantage Reply can help

Target Architecture

Organisational aspects and data governance

Data gap analysis and remediation

Re-engineering processes and procedures

Key take-aways

Appendix - case studies

Abstract Availability of sufficiently granular and reliable

data is a major priority of the Single Supervisory

Mechanism (‘SSM’). To this end, the ECB is

demanding additional and more granular

reporting from banks under its supervisory remit

by introducing its new reporting requirement:

the Analytical Credit Dataset – also known as

AnaCredit. This reporting will form a detailed

eurozone bank dataset on credit risk and is seen

as a critical enabler of effective European banking

supervision. Its implementation represents the first

step towards establishing a harmonised statistical

credit reporting framework within the eurozone.

AnaCreditAbstract

2

“The ECB has every interest to facilitate and promote integration and standardisation also on the ‘input side’, in the internal systems of the banks, for only this will ensure coherent information.”Mario Draghi, Seventh ECB Statistics Conference

on 15 October 2014

AnaCreditOverview

3

OverviewIn the SSM Framework Regulation, AnaCredit

is placed in the middle of a roadmap for further

developing micro and macro prudential supervision in

the euro system based on granular credit data within

the context of a harmonised supervision approach.

Its implementation is a key challenge for banks that

needs to be addressed in a short timeframe.

On 4 December 2015, the ECB released the Draft

Regulation on the collection of granular credit and

credit risk data, setting out the statistical reporting

requirements, the reporting population and the

reporting thresholds. The consultation period

ended on 29 January 2016. The ECB assessed the

consultation responses received by National Central

Banks (NCBs) and, as a result, issued an amended

version of the draft regulation on 18th May 2016. The

regulation has been approved by Governing Council

on 1st June 20161.

The objective of AnaCredit is to establish a

central register of granular data about the credit

exposures of credit institutions within the eurozone.

In addition AnaCredit will reinforce the current

European supervisory and regulatory framework,

in part by supporting the Supervisory Review and

1 Regulation (EU) 2016/867 of the European Central Bank of 18 May 2016 on the collection of

granular credit and credit risk data (ECB/2016/13)

AnaCreditOverview

4

Evaluation Processes (‘SREP’) methodologies. In addition,

AnaCredit will inform statistical analysis and monetary policy

decision-making.

AnaCredit is a first step towards improved statistical data

collection; moving from a silo-based approach to high

granularity risk and finance data from different sources

consolidated into a central repository. Considering the high

level of heterogeneity of the current credit data collection

within the eurozone and the different levels of data

granularity, AnaCredit will be implemented in stages taking

into account the time needed by banks (the ‘reporting

agents’) to be compliant with the data requirements. The

table below illustrates the information required and critical

data elements.

The first stage begins on 1 September 2018 with preliminary

identification of counterparties. Depending on national

discretion, NCBs may require reporting agents to provide

partial or complete counterparty reference data and credit

data in advance of this date. The data will be collected from

participating NCBs, who themselves collect it from credit

institutions. Each credit institution will be required to report

95 data attributes (including seven identifiers for each:

Reporting agent, Observed agent, Counterparty, Contract,

Instrument, Protection identifier and Protection provider)

about their credit exposures, which are grouped into two

prescribed templates containing ten tables.

Some of this data is not currently produced and collected

by banks in a structured way, so the creation of these

templates and tables represents a new level of complexity

depending on the data availability and sources as well

as different national regulations (including rules on data

privacy). The table below illustrates the data attributes,

level of complexity and critical data elements required. To

an extent, this aligns with current harmonised regulatory

reporting in the EU (Common Reporting (‘COREP’) and

Financial Reporting (‘FINREP’)) but is at a much more

granular level. This presents challenges, recalling the

enormous complications that arose during the creation of

the Loan Tape in the Asset Quality Review (‘AQR’) exercise.

1. Counterparty reference data

Template Table # Attributes

2. Instrument data

Level of Complexity

Critical data elements

22 High • Counterparty identification through

Code LEI (Legal Entity Identifier)

• Enterprise size, data of enterprise size

and number of employees, according

to Recommendation 2003/361/EC

23 Medium • Details on interest rate (cap, floor, type)

3. Financial data 11 Medium • Details on interest rate (next interest

rate reset date)

4. Counterparty instrument data 1 Low

5. Joint liabilities data 1 Low

• Status and date of forbearance and

renegotiation

TEM

PLA

TE 1

6. Accounting data 16 Medium

TEM

PLA

TE 2

7. Protection received data 9 Medium • Detail on type of protection and real

estate collateral location

8. Instrument-protection received data 2 Medium • Third party priority claims against the

protection

9. Counterparty risk data 1 Low

10. Counterparty default data 2 Low

Figure 1: AnaCredit structure structure: templates, tables and critical data elements

AnaCreditOverview

The timeline and the main reporting requirements for the first and subsequent phases are showed in the figure below:

• IT solutions involved in the management of credit risk

will need to be adapted to handle the new information and

frequency of reporting;

• Processes that support underwriting, monitoring and

reporting will need to be revisited to ensure complete and

accurate data capture and robust, controlled production of

the new data submissions;

• Credit risk modelling processes may need to changed

based on new data structures and content to the extent

that the data used is currently aligned to information

provided to national CCRs.

More detail on our views on the business and process

impact is included later in this paper (in the section ‘How Avantage Reply can help’ and the accompanying case studies).

5

Amount equal to or larger than EUR 25K on any reporting reference date within the reference period

Amount equal to or larger than EUR 25K on any reporting reference date within the reference period

Instrument by Instrument Instrument by Instrument

Resident credit institutions and resident foreign branches of credit institutions

NCBs’ right to grant derogations to small reporting agents, to be adopted at least two years prior to its introduction to allow sufficient time for implementation

Loans and depositsCredit granted by credit institutions to legal entities on individual basis No personal data

Extension to derivatives, other accounts receivable, off-balance-sheet items Credit extended to persons other than legal persons, including to sole proprietors On consolidated basisPersonal data (ensuring the privacy rights)

To ensure the appropriate identification of counterparties, NCBs shall transmit to the ECB a first set of the counterparty reference data, six months prior to the first transmission

All templates and related tables need to be provided at the same time

Reporting Threshold

Approach

Population

Scope

Submission

FIRST STAGE - 1ST SEPTEMBER 2018 SUBSEQUENT STAGES

Figure 2: AnaCredit reporting requirements

AnaCredit replaces the current local Central Credit

Registers (‘CCRs’), ensuring a standard level of granularity

on common data among different EU countries. The main

advantages will be realised over a longer term because

AnaCredit will contribute to a convergence of existing

European CCRs and the creation of CCRs in the countries

where they are absent. In this context, the CCRs appear to

be the starting point to evaluating the incremental efforts

required in each country.

Impact on banks

The transition has several implications both for regulators

and banks in respect of business processes and underlying

infrastructure. The main areas that will be affected are as

follows:

AnaCreditNational Central Credit Registers as a starting point

6

From lenders’ perspective, CCRs represent granular

databases with three main purposes:

• Accurately assessing the credit quality of potential

borrowers in supervised financial institutions;

• Supporting financial transactions through the

evaluation of risk by credit institutions; and

• Enabling economic analysis.

These databases exist and operate in 14 EU countries2

(Austria, Belgium, Bulgaria, Czech Republic, France,

Germany, Italy, Latvia, Lithuania, Portugal, Romania,

Slovenia, Slovakia and Spain), under the supervision of

NCBs, to monitor and manage credit risk information and

provide an overview of the credit exposure concentrations

and indebtedness levels of resident and non-resident

borrowers.

Unfortunately, harmonisation across CCRs in some EU

countries is limited. Data is collected at different levels

of granularity, which can be seen in more detail in the

following table in terms of:

• Reporting threshold and frequency;

• Population and perimeter; and

• Lack of detailed information on asset, collateral and

valuation.

National Central Credit Registers (CCRs) as a starting point

Figure 3: Main differences between European CCRs

Reporting variables Italy3 Austria Belgium Czech Replublic

Germany4 Spain France Portugal Romania

Threshold

Frequency

National Central Banks

Credit Institutions

Insurance companies

Investment companies

Foreign bank branches

Branches of the “Caisse des depots”

Resident private entities

Resident institutions

Resident public administrations

Resident non-financial companies

Collateral

Loan purpose

Maturity

REP

OR

TIN

G P

OP

ULA

TIO

NR

EPO

RTI

NG

AG

ENTS

REP

OR

TIN

G

REQ

UIR

EMEN

TS

30,000 350,000 25,000 n/a 1,000,000 6,000 76,00045,0005

50 5,000

monthly monthly monthly monthly quarterly monthly monthly monthly monthly

AnaCreditNational Central Credit Registers as a starting point

2 Memorandum of understanding on the exchange of information among national central credit

registers for the purpose of passing it on to reporting institutions (Source: https://www.bancaditalia.

it/statistiche/raccolta-dati/centrale-rischi/Memorandum_of_Understanding_10.pdf ).

NCBs in every EU country in the scope of SSM will be

responsible for evaluating the timing and convergence

methods between AnaCredit and local CCRs; moving

towards the instrument-by-instrument basis required by

AnaCredit.

3 Bank of Italy recently provided the following updates:

• Anticipation of the collection on counterparty data attributes by 3 months;

• Postponement of the integration between CCR (Italian Central Credit Register) and AnaCredit until

not before 2020, mandating an extended period of parallel running. As thus, institutions must consider

the need to introduce means of ensuring consistency between the two activities.

4 The German authorities (Ministry of Finance, Bundesbank and BaFin) agreed to delay the

intended reform of the local credit register until January 1, 2019 to decide about the convergence

of the LCR and AnaCredit or the abolition of the LCR. In addition, the authorities are considering the

option that AnaCredit could replace other existing statistical reports.

5 France uses two different thresholds based on the geographical limits: EUR 76,000 for reporting

institutions located in metropolitan France and the French overseas territories. EUR 45,000 for

reporting institutions located in the French overseas departments (Guadeloupe, Martinique, Guyana

and Reunion) and in the territorial units of St. Pierre and Miquelon and the departmental unit of Mayotte.

AnaCreditThe new approach to expanded statistical and supervisory

reporting within the SSM

8

The new approach to expanded statistical and supervisory reporting within the SSMAnaCredit gives banks an opportunity to improve their

data management, but poses some important challenges.

Current monetary policy, supervisory and other reporting

standards require data, which are collected in a large

number of reports with different submission frequencies

and different levels of aggregation. When a reporting

framework is updated or a new one is created, banks

must interpret it, extract the data from their IT systems

and transform it appropriately to produce the final data

submission in accordance with the relevant regulation.

These processes are often highly complex, involving

multiple systems, manual interventions and judgements

and can therefore produce unintentionally inconsistent

results between submissions. A common reporting

framework is helpful in order to avoid overlap, duplication

and inconsistency. The proliferation of reporting

requirements that demand more granularity and complexity

has motivated the ECB to begin building a joint European

Information System based on three main components:

1. A single, comprehensive and harmonised primary

European Reporting Framework (ERF), or “output layer”

for regular data transmission. This model aims to ensure

precise, simple and unambiguous definitions of information

prescribed by regulatory or statistical reports.

2. The Banks’ Integrated Reporting Data Dictionary(BIRD), an “input layer” that describes data elements

on their granular level and defines them in an accurate,

standardised and unique way. It will be a common

language for data within the European banking sector,

aiming to provide a standardised model for organising

banks’ internal data warehouses in an integrated way,

and the transformations to the data that the banks need

perform. The BIRD consists of documentation. It is not an IT

tool and does not add reporting requirements. The BIRD’s

main advantages are:

• Greater consistency and better quality data at source,

eliminating the need to manage each mandatory data

collection in a separate way;

• Increased efficiency, consistency and harmonisation

of data, lower costs of report production; and

• Consistent interpretation and clarity of requirements.

The first version of the BIRD addresses the new

requirements related to the collection of AnaCredit data.

The initial creation of a stable glossary covering (at least)

AnaCredit has been the subject of ECB workshops since

autumn 2015 and some volunteer NCBs have started

working on a the pilot, with implementation expected by

the first quarter of 20176.

The future BIRD extensions, are still under evaluation

and should be able to cover also the following statistical

and supervisory reporting requirements: ECB’s Monetary

Financial Institutions’ Balance Sheet Items Statistics

(BSI), ECB’s Monetary Financial Institutions’ Interest Rate

Statistics (MIR), ECB’s Securities Holdings Statistics (SHS),

and EBA’s Implementing Technical Standards (ITS), which

encompass COREP and FINREP.

This will require a long implementation period and it

is crucial to understand the role of BIRD in the SSM

Regulation Framework.

3. A single data dictionary (SDD), a methodological

and semantic integration of existing European reporting

frameworks through the creation of clear and non-

overlapping definitions of the data (reconciled across

several regulatory frameworks) for all reports that are

generated from the data submitted by credit institutions (as

opposed to the common language established under BIRD

for the data reported by banks).

6 Banks’ Integrated Reporting Dictionary, available at: http://www.banks-integrated-reporting-

dictionary.eu/documents:birdproject

9

AnaCreditThe new approach to expanded statistical and supervisory

reporting within the SSM

ECB initiatives in the area of integration

Institutions NCBs ECB

sourcing

internal mapping

Pri

mar

y da

ta (s

ourc

e)

Rep

ortin

g da

ta w

areh

ouse

Reporting granular and micro data

Feedback loop

Manipulating data from data warehouse to the regulatory data model

Pri

mar

y R

epor

ts (E

RF)

Sec

onda

ry R

epor

ts

TRANSFORMATION

Transformation rules specified through NCBs

and ECB

BIRD (Bank’s Integrated Reporting Dictionary)

SDD (Single Data Dictionary)

ERF (European Reporting Framework)

Figure 4: The Role of BIRD, ERF and SDD (from ECB initiatives in the area of integration)

The AnaCredit regulation will need to be assessed and

implemented in conjunction with the developments in the

ERF and BIRD in order to achieve a harmonised framework.

To implement AnaCredit with BIRD, a complex reconciliation

with the current structured reporting framework will be

necessary for local CCRs.

There are various processes and instruments adopted

by national competent authorities (NCAs) in the different

countries that govern the production of harmonised and non-

harmonised reporting. Both within banks and regulators, a

range of well-structured and less prescriptive approaches

are in place governing the end-to-end regulatory reporting

production process.

For example, in Italy the whole production process of

regulatory reporting is governed by the protocol PUMA2 (Unified Business Matrix Procedure), an feature of Italian

banking system since 1974. The PUMA2 is an integrated

process that develops reference documentation for the

production of data on financial intermediaries (e.g. the matrix

report forms for bank’s balance sheet information, statistical

and supervisory reports of financial companies that are on

the special register, reports of the CCRs, payment system

investigation, etc.). In detail PUMA2 provides:

• Extensive coverage of regulatory reporting indicators,

extended to Basel III, derived from a combination

of financial / regulatory reporting systems as well

as data from other functions (e.g. risk management

departments);

• A well-defined reporting framework including the

input data dictionary, output data dictionary and data

transformation rules (data lineage) through the decision

table; and

• Wider cooperation through collaboration between

representatives of Bank of Italy, Italian banks, and

market players in the evolution of PUMA2 to address

any new regulatory reporting. This aspect ensures

sharing and reducing investment especially for small

and medium-sized banks to promptly address the new

regulatory requirements.

In Italy, the PUMA2 protocol will ensure a transition

consistent with the BIRD ECB initiative. The main goal

is the achievement of standardisation, uniformity and

regulatory compliance in view of the adoption of a pan-

European data model. The German Bundesbank envisages

a standardisation of the IT systems in the context of the

ERF and awaits the results of the discussion at the level of

the statistics committee of the European System of Central

Banks.

Source: European Central Bank

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AnaCreditHow Avantage Reply can help

How Avantage Reply can helpWith extensive experience and expertise in risk

management, risk data and risk and regulatory reporting,

Avantage Reply is well placed to assist our clients in the

implementation of AnaCredit. Having already assisted

clients with end-to-end solutions, we have experience

in developing infrastructure (e.g. systems architecture,

process and control design, data management) that

meets ECB and EBA requirements. Avantage Reply also

provides services across other core elements of credit

risk, SSM regulatory reporting and compliance.

Avantage Reply offers a proven approach that

addresses the key challenges required by the new

reporting requirements, helping clients accelerate

the transformation needed in terms of architecture,

organisational aspects and data collection. These

aspects are essential to the successful implementation

of AnaCredit, as illustrated below.

Target architectureMoving system architecture from silo-based,

fragmented regulatory reporting capability towards

an integrated platform, enabling adherence to

multiple reporting requirements, with more

granular drill-down capability.

Re-engineering processes and proceduresRevision, remediation and optimisation of

internal processes for collecting and processing data

to align to the new reporting requirements.

Organisational aspects and data governanceMultidisciplinary approach to reporting production,

review, challenge and validation, involving integrated

management of the dataset by risk, finance,

data and IT through either a centralised or

decentralised operating model.

Due diligence for requested data setStructured gap analysis (of ‘stock’ data as well as

new lending data produced) will be necessary to

identify data issues (gaps in availability, quality

and processes), their criticality, and appropriate

remediation of these issues.

ANACREDITAnalytical

Credit Data Set

Figure 5: Challenges and solutions for AnaCredit

Target Architecture

The SSM approach is designed to evaluate the banking

group as a whole and requires a drill-down approach to

data collection and analysis with loan / instrument level

granularity. Therefore, it is necessary to design and

implement a systems architecture that features an analytical

group database, ensuring consistency between different

reporting submissions (harmonised and not harmonised)

and consistency of customer classifications. This must

also adhere to the BCBS principles for effective risk data

aggregation and reporting (‘BCBS 239’).

To achieve this, in order to enforce a better architecture to

store and process data, banks are implementing different

solutions that leverage innovative technological enablers.

In some cases, banks are focusing on system architectures

based on effective interaction between risk and finance data.

These solutions leverage the accounting and regulatory

reporting systems at group level. This approach facilitates

better compliance with BCBS 239, but requires investment

in local data warehouse and other solutions to address the

requirements of local subsidiaries and business lines.

AnaCreditHow Avantage Reply can help

Alternatively, “Data Lake” solutions involve a more

innovative rethinking of data management. Here, the

architecture provides:

• A data hub that includes all the data (structured, semi-

structured, and unstructured) of the bank, with simple

interfaces with existing systems and calculation engines,

allowing easier data interrogation; and

• A common financial and risk metric layer that makes

available the most relevant metrics and simplifies

data reconciliation. This solution can provide a better

understanding of risk data from input to final measures.

Organisational aspects and data governance

In parallel with architectural upgrades, more

stringent regulatory constraints and onerous

reporting requirements require a thorough review of

organisational aspects, culture and data governance;

focusing on these main aspects:

• Data management organisational structure: A

centralised structure can be employed in which the

Chief Data Officer (CDO) is the main responsible

function for data quality; while in a distributed

structure, “data stewards” have this responsibility

and a committee is established to monitor and report

on data quality to top management;

• Processes and relationships between thevarious roles and functions: Clear definition of

roles, responsibilities, dependencies and hand-

overs in either a centralised or distributed operating

model;

• Governance policy on data: Harmonisation and

extension of internal policies on data governance to

accommodate the more stringent requirements; and

• Reporting Model: Adequate processes established

to enable review, challenge, issue escalation,

remediation and final review of data prior to

submission.

Data gap analysis and remediation

Many banks’ current processes and data stores do not

facilitate data collection of the mandated granularity or

the required data may be unreliable (either because

of data quality issues or the absence of a controlled

extraction mechanism). Therefore, as a starting point

to implementing AnaCredit, a gap analysis will be

necessary to identify gaps in availability, quality

and processes and appropriate remediation of

these issues. As there will likely be numerous

gaps identified, an approach to assessing criticality

of data elements and prioritising remediation

must be adopted.

Re-engineering processes and procedures

In order to ensure reliable and timely data collection on

loans, it may be necessary to enhance credit workflow

tools starting from the origination phase, through to

monitoring, collections, provisioning and recovery.

This will ensure that the data is captured, flagged

and stored in a way that enables compliance with the

AnaCredit reporting specifications.

11

AnaCreditKey take-aways

Key take-awaysWith AnaCredit now in an operative phase, the main task of the

NCAs is to define the steps of the implementation process. All

EU countries within the SSM have adopted the regulations at the

NCA level and initiated implementation activities based on their

national discretions. As such, institutions have launched specific

projects but many of these institutions are expressing concerns

about the level of costs and complexity in achieving compliance

with the new regulations. These concerns are not unfounded as

the procurement of the required attributes, the reconsideration

of processes, organisational aspects and technical implementation

all pose difficult challenges.

For example, in Italy only significant banks have started dedicated

projects and are now assessing the main impacts. From the German

point of view, it is important that the new regime puts less burden on

the reporting by smaller banks. The results of a recent Luxembourg

banking industry study expected that the AnaCredit project

could cost smaller banks millions of euros for full compliance.

The same study noted that larger banks on the other hand might

need to completely rethink reporting systems, credit systems,

finance systems and processes to efficiently and effectively comply.

In all cases, it is clear that potential synergies and shared

dependencies with ongoing projects in regulatory reporting

must be leveraged to limit the impact on institutions’ bottom

line. A good starting point to these considerations would be

the implementation of BCBS 239 risk data aggregation techniques,

the evolution of COREP/FINREP and the implementation of IFRS 9.

The overall AnaCredit framework requires a close dialogue and

exchange of information between ECB and NCB/NCAs for efficient

implementation.

Despite these challenges, the efficient and effective implementation

of AnaCredit and the accompanying regulatory framework should

bring significant benefits as well. The overall regulatory environment

will make it easier for banks to streamline regulatory reporting

processes and focus more on value creation. As such, the direct

benefits may be estimated not only with respect to greater efficiency

of the internal systems of reporting and monitoring but also through

increasing the efficiency of lending processes making good

credit decisions guided by reliable data such as those provided

by AnaCredit. Indeed, clear and detailed information is needed

to maintain a healthy and transparent financial system, with great

advantages for both supervisory authorities and institutions.

AnaCreditAppendix

13

Appendix

Case Study: Enhancing the quality of risk reporting through the introduction of BCBS 239

The following case describes a project we undertook for

one of the largest Globally Important Systemic Banks (GSIBs)

in Europe to implement a new single reporting architecture.

The project, which had the main objective of aligning risk and

finance data streams, was key to earning a passing grade from

the regulator on initial implementation of BCBS 239.

The project required a new approach to dealing with the

organisation of data, both in the local IT systems and at the

group level. The solution revolved around the effective

interaction between risk and financial reporting streams and

the creation of a unified, single reporting stream. This had

three main areas of focus:

1) Source data: Review and enhancement of localoperational systems. Data ownership is defined at the

level of the relevant primary operational systems (e.g.

source or transactional systems) and includes responsibility

for the quality of the information that is produced. Based on

this concept, the operational system flows were enhanced

to provide a new group architecture with both risk and

financial data from the source.

2) Group architecture: A single architecture to handle bothrisk and finance needs. A new architecture at the group level

was put in place to ensure the consistent treatment of both

accounting/finance and risk data. This in turn enhanced the

quality of information to be used in reporting streams.

3) Single point of reference for regulatory reporting: Groupand local needs. The constant evolution of regulatory reporting

and regulatory information/data requests required numerous

resources at both the group level and NCA level to adapt

and adjust, proving costly and difficult to maintain quality.

With the introduction of a single point of reference for regulatory

reporting in Europe, the client has begun a natural alignment to

the SSM with a single stream of reporting.

Focus Area

Gro

up a

nd

Loca

l Rep

ortin

gN

ew G

roup

Arc

hite

ctur

eLe

gal E

ntity

Systems architecture

Local Operational/Source Systems

Figure 6: Group Level Architecture

Group Exchange Layer

1

2

Group Accounting

Platform3

Group data warehouse

6

Single Flow

Accounting Engines

4 5Risk

Engines

BI Tools / User Interface

7RegulatoryReporting

Regulator Requests, SSM Enhancements

Internal Reporting and

Monitoring

KEY POINTSDescription BCBS Principle

1. High priority is placed on specifications for the sourcing of Accounting and Extra-Accounting data from the Legacy

2. An Exchange Layer has the dual role of formatting data and performing controls (consistency and coherence)

3. Data is integrated into the Group Accounting Platform where it is made available to Data Consumers

4. Accounting Engines determine key figures, such as Debit and Credit classes

5. Risk Engines (feed only after Accounting figures have been established) calculate Key Risk Indicators, such as RWA and Liquidity

6. A single DWH collects data after all calculations have been performed and is made accessible to the User through BI tools

7. Reporting Systems, both Internal (ex. surveillance) and External (ex. Corep and Finrep) are fed from a single entity

4. Completeness5. Timeliness

3. Accuracy and Integrity

3. Accuracy and Integrity4. Completeness8. Comprehensiveness

6. Adaptability7. Accuracy of Reporting9. Clarity and Usefulness

6. Adaptability7. Accuracy of Reporting9. Clarity and Usefulness

3. Accuracy and Integrity4. Completeness8. Comprehensiveness

10. Frequency11. Distribution

AnaCreditAppendix

14

Case Study: Recovery data on NPL positions

The following case study illustrates the approach followed during

the due diligence activities on non-performing loans (’NPL’)

positions (managed by the work-out department) in respect

of recovery information on collateral, assets, valuation, with a

particular focus on credit risk.

The scope of the work focused on positions with a lack of

information or unclear articulation of the links between credit

line, collateral and assets. Additionally, the work ensured

that all NPL positions secured by a real estate property were

appraised by qualified valuation expert in order to realise the

benefits of such valuations and the transparency required in

the reporting to regulators.

Our team was comprised of legal experts, consultants and

loan work-out managers, and performed the following

activities:

1) Detailed investigation of available data/informationA careful examination of the documentation available on

paper files or data housed in IT systems was performed in

order to ascertain the consistency and validity of the credit

lines secured by collateral (real estate and financial).

2) Enhancement of the data set within IT systemsFollowing the analysis, a data room was established to

facilitate data cleansing within IT systems to make them

consistent with those present in the dossier. The purpose of

this step was to align the IT system and ensure data accuracy,

quality and completeness with the statistical and supervisory

reporting framework.

Moreover, to support the activities of the data room, tracking

and monitoring tools were prepared, with the aim of creating

periodic reports on the progress of work.

The arrangement of the data thus prepared, however, is

relevant not only on the information pertaining to the stock

of existing loans; but also to ensure the correct acquisition of

information on new loans. This was also necessary to improve

the on-going processes and procedures.

Figure 7: Action plan on data collection

Recoveries data set• Identification of the perimeter• Deploy approach (due diligence or automatic

interventions)• Integrity and data quality checks

Main areas affected• Collateral (Performing and Non Performing)• Assets• Valuations

1 2 3 4Set up working team Due Diligenceactivities

IT systems update Quality check

Recovery data on stock

Data collection on-going

Structural rethinking of end-to-end credit process for the correct acquisition of the data to the new reporting system

Main areas affected• Preliminary phase and Loan deliberation• Collateral Acqusition• Workout actions

1 2 3 4Credit Risk Policies

Loan Granting Monitoring Workout

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