ING Lease The relationship between Risk and Compliance and Data Quality Owen Francis, Director, Risk and Compliance David Fabia, Senior Manager, Compliance

The relationship between Risk and Compliance and Data Quality

Owen Francis, Director, Risk and Compliance

David Fabia, Senior Manager, Compliance

ING Lease ING Lease is among the top 5 of major leasing companies in Europe ING Lease is part of ING Wholesale Banking ING Lease has a presence in 15 countries: Netherlands United Kingdom Belgium Luxembourg France Spain Italy Germany Russia Poland Czech Republic / Slovakia Hungary Romania Ukraine

ING Lease is among the top 5 of major leasing companies in Europe

ING Lease is part of ING Wholesale Banking

ING Lease has a presence in 15 countries:

Netherlands

United Kingdom

Belgium

Luxembourg

France

Spain

Italy

Germany

Russia

Poland

Czech Republic / Slovakia

Hungary

Romania

Ukraine

ING General Lease: European footprint 2007 ING Lease UK ING Lease Poland ING Lease Germany Moscow Paris Milan Warsaw Bucharest Budapest Brussels Amsterdam Prague Hamburg London Madrid Luxembourg Kiev ING Lease France ING Lease Spain ING Lease Italy ING Lease Eurasia ING Lease Romania ING Lease Ukraine ING Lease Luxembourg ING Lease Belgium ING Lease Netherlands ING Lease Hungary ING Lease Czech Republic / Slovakia

Where we started ING Lease (UK) established in 1989 in Cheapside, London Subsequently, acquired three businesses from Abbey in June 2004 Asset Finance (based in Redhill) Vendor Finance (based in Enfield) Country Finance (based in Harrow) Four offices consolidated into one central office in Redhill in June 2005

ING Lease (UK) established in 1989 in Cheapside, London

Subsequently, acquired three businesses from Abbey in June 2004

Asset Finance (based in Redhill)

Vendor Finance (based in Enfield)

Country Finance (based in Harrow)

Four offices consolidated into one central office in Redhill in June 2005

How our business looks ING Lease UK employs 320 people We aim to process daily volumes of: 400 plus proposals (processed within 2-4 hours) Pay out 200 plus agreements the same day Provide 200 plus settlement quotes At any one time we have 2000 cases in default (over 31 days) Overall portfolio consists of 100,000 plus customers

ING Lease UK employs 320 people

We aim to process daily volumes of:

400 plus proposals (processed within 2-4 hours)

Pay out 200 plus agreements the same day

Provide 200 plus settlement quotes

At any one time we have 2000 cases in default (over 31 days)

Overall portfolio consists of 100,000 plus customers

What we do Lend to UK businesses to buy a wide variety of assets Operate through intermediaries – vendors, dealers, brokers Operate in a number of market segments: Small Ticket - Vendor – point of sale finance for business equipment - General Asset - Agriculture Middle Ticket - Financial Products (Middle Ticket transactions) - Block Discounting Commercial Mortgages (early 2008)

Lend to UK businesses to buy a wide variety of assets

Operate through intermediaries – vendors, dealers, brokers

Operate in a number of market segments:

Small Ticket

- Vendor – point of sale finance for business equipment

- General Asset

- Agriculture

Middle Ticket

- Financial Products (Middle Ticket transactions)

- Block Discounting

Commercial Mortgages (early 2008)

What we finance Industrial assets Packaging, print, processing, manufacturing, engineering, construction Transportation assets Cars, commercial vehicles, buses, coaches, materials handling, rail and shipping Business equipment IT, telecoms, reprographics, audio-visual, security, vending Agricultural equipment Farm machinery, turf care

Industrial assets

Packaging, print, processing, manufacturing, engineering, construction

Transportation assets

Cars, commercial vehicles, buses, coaches, materials handling, rail and shipping

Business equipment

IT, telecoms, reprographics, audio-visual, security, vending

Agricultural equipment

Farm machinery, turf care

Data Quality Ownership Ownership for data quality must reside with the Business Essential that data quality forms an integral part of Operational Risk Management Establish a Executive Committee structure Ensure that CEO and Senior Management are fully engaged Create a set of portfolio reports to firmly embed data quality into the Business Compliance function to oversee progress and report on targets achievement

Ownership for data quality must reside with the Business

Essential that data quality forms an integral part of Operational Risk Management

Establish a Executive Committee structure

Ensure that CEO and Senior Management are fully engaged

Create a set of portfolio reports to firmly embed data quality into the Business

Compliance function to oversee progress and report on targets achievement

ORGANISATIONAL EXECUTIVE COMMITTEE STRUCTURE Managing for Value Meeting Enhancements Meeting Operational Risk Forum Automated Underwriting Steering Committee Middle Ticket Residual Value Strategy Meeting Channels User Group Complaints Meeting Board Meeting Risk Committee Management Meeting Credit Forum Operational Review Meeting Operational Risk Committee

ORGANISATIONAL EXECUTIVE COMMITTEE STRUCTURE The red shading indicates the committees where data quality is discussed. Managing for Value Meeting Enhancements Meeting Operational Risk Forum Automated Underwriting Steering Committee Middle Ticket Residual Value Strategy Meeting Channels User Group Complaints Meeting Board Meeting Risk Committee Management Meeting Credit Forum Operational Review Meeting Operational Risk Committee

Data Quality Management ING Group mission statement: To structurally improve the creation and maintenance of credit risk related data (customers, facilities, outstandings, covers, provisions, repayment schedules) at all levels of ING Bank and in all relevant systems in order to create efficient, consistent and transparent credit risk reporting which is used for decision making purposes both internally and externally

ING Group mission statement:

To structurally improve the creation and maintenance of credit risk related data (customers, facilities, outstandings, covers, provisions, repayment schedules) at all levels of ING Bank and in all relevant systems in order to create efficient, consistent and transparent credit risk reporting which is used for decision making purposes both internally and externally

Data Quality Management Approach - Technical Data Quality: data quality issues can be solved by technical checks in the systems Processes and Procedures: the discipline to follow good processes and procedures creates a work environment where the first input is directly the right one Clean up of current data

Approach -

Technical Data Quality: data quality issues can be solved by technical checks in the systems

Processes and Procedures: the discipline to follow good processes and procedures creates a work environment where the first input is directly the right one

Clean up of current data

Data Quality Management Technical Data Quality: Coverage of data in centralised global database > 99% Reliability of data: number of errors < 0.5% Rating model compliance: Basel II compliant-ratings > 99% Reconciliation between local systems and global database = 100%

Technical Data Quality:

Coverage of data in centralised global database > 99%

Reliability of data: number of errors < 0.5%

Rating model compliance: Basel II compliant-ratings > 99%

Reconciliation between local systems and global database = 100%

Data Quality Management Processes and Procedures: Define the workflows Agree consistent data definitions Agree data entry processes and procedures Set clear job descriptions Ensure that defined processes and procedures are followed Set standards and measure data quality against those standards Continually review and improve processes and procedures

Processes and Procedures:

Define the workflows

Agree consistent data definitions

Agree data entry processes and procedures

Set clear job descriptions

Ensure that defined processes and procedures are followed

Set standards and measure data quality against those standards

Continually review and improve processes and procedures

Data Quality Management Clean up of current data First priority: completeness and correctness of PD, eg, industry code LGD, eg, asset code Exposure / Limit Covers / Guarantees De-duplications

Clean up of current data

First priority: completeness and correctness of

PD, eg, industry code

LGD, eg, asset code

Exposure / Limit

Covers / Guarantees

De-duplications

Risks of Incorrect data Basel II Risk Components PD LGD EAD Maturity Credit Scoring/Acceptance Loan Pricing Regulatory Capital/RWA Performance measurement Loan Loss Provisioning Economic Capital

Risks of Incorrect data Importance of complete and correct Data Provisions Basel 2 – PD/LGD Credit ratings Internal reporting Portfolio management Strategic decisions Group-wide initiative to structurally improve the quality of data

Importance of complete and correct Data

Provisions

Basel 2 – PD/LGD

Credit ratings

Internal reporting

Portfolio management

Strategic decisions

Group-wide initiative to structurally improve the quality of data

Risks of Incorrect data Data Problems are caused by Duplicate data entry Incorrect data entry No data owner (accountable) Indistinct data definitions (talking the same language) Faulty paper forms / dossiers Lack of Reconciliation and Validation

Data Problems are caused by

Duplicate data entry

Incorrect data entry

No data owner (accountable)

Indistinct data definitions (talking the same language)

Faulty paper forms / dossiers

Lack of Reconciliation and Validation

Data Quality Culture Policy Regulatory Process Data Quality Basel II/ Solvency II Workflow management Country Risk Sarbanes-Oxley Loan Loss Provisioning Straight-through processing First time right One time data entry Ownership/ Authorisation Standardised Process Definitions/ Standards Economic Capital IFRS Expected Loss Customer Profitability

Data Quality Culture DATA COMPLETENESS : All the input fields are populated DATA CORRECTNESS Correct limit and/or product types Correct ratings entered Covers delivered and entered correctly Correct asset code Global Database information correct

DATA COMPLETENESS :

All the input fields are populated

DATA CORRECTNESS

Correct limit and/or product types

Correct ratings entered

Covers delivered and entered correctly

Correct asset code

Global Database information correct

Data Quality Culture Single integrated (business) environment One global customer database One credit risk process tool One consolidated risk data warehouse One credit risk engine and reporting tool One time data entry Each data element should be input once, in the most logical place This helps to improve data quality and consistency Lower operational risk

Single integrated (business) environment

One global customer database

One credit risk process tool

One consolidated risk data warehouse

One credit risk engine and reporting tool

One time data entry

Each data element should be input once, in the most logical place

This helps to improve data quality and consistency

Lower operational risk

Recommendations Establish Steering Committee to oversee progress Data Management Chapter in the Credit Policy Data Quality is an issue in Business Unit visits Audit reports Credit Inspection reports General awareness of the importance of Data Quality throughout the whole Business Unit is of paramount importance Increasingly businesses are being judged on data quality

Establish Steering Committee to oversee progress

Data Management Chapter in the Credit Policy

Data Quality is an issue in

Business Unit visits

Audit reports

Credit Inspection reports

General awareness of the importance of Data Quality throughout the whole Business Unit is of paramount importance

Increasingly businesses are being judged on data quality

Questions?