Leveraging XBRL for Basel II

Leveraging XBRL for Basel II

Daniel D’Amico, IBM Business Consulting Services, UK

Agenda Basel II background Basel II is an opportunity The data management challenge XBRL and Basel II

A couple of quotes “Regulators and customers are demanding greater focus

on risk management. …This call for transparency will challenge traditional business practices and will require more auditable processes throughout the business” Morgan Stanley analyst (on market timing), FT 11/03

“US regulators expect Basel II will apply to a total of around 20 large US banks. All US banks operating under Basel II will be obliged to use only the most advanced Basel II approaches for assessing banking risks, which means the IRB approaches in the case of credit risk.” Global Risk Regulator 10/03

Basel II BackgroundWhat is Basel II Accord?

Commercial imperative

When does it happen?

The publication of the Basel II Accord will mark the end of long process that will have effectively re-written the rules of banking. Basel II will affect the conduct of monetary policy and the stability of financial institutions all over the world

What is it trying to achieve?

To promote safety and soundness in the financial system To align regulatory capital requirements more closely with underlying risks To offer incentives for institutions to pursue more sophisticated & effective risk management

Basel II will significantly impact FS institutions and the change is such that preparation needs to begin now to ensure readiness for a parallel run starting 1st Jan 2006

Key strategic decisions need to be taken now on the approach to be taken and the benefit that should be achieved over and above compliance

QIS 3

EvaluationQIS 3

Consultationphase

PreparationNew Accord

EU directive

Parallel runBasel I + II

CP 3New

Accord

Full force

Oct 02 May 03 Nov 03Dec 02 July 03 Dec 06Jan 06

Integrate into National law

Basel II Opportunities:• Improve shareholder value• Economic capital savings• Improve/maintain credit rating• Improve risk management strategy • Alignment of Risk & Finance• Cost reduction through organizational

process improvement• Identify potentially dangerous

portfolio positions and other risk sources

Basel II is an Opportunity – not just a Mandate

Data Foundation

Pillar 2: Pillar 1:

Calculation andManagement of:

Credit Risk Operational Risk Market Risk

Ensure sound processes

Ensure adequate capital at all times

Ensure motivation improving risk management practices

Quantitative and qualitative

disclosure ofundertaken risks

and riskmethodologies

Basel II

Pillar 3: Minimum

Capital requirements

Supervisory Review Process

Market Discipline

Basel II Challenges:• Setting up Basel II program• Data management• Systems management• Establishing Risk Framework

Key challenges – Systems & Data Management

Data mgt.

Project mgt.

Impl. of sup. Review process

Adherence to disclosures

Sufficient resources

Mgt buy-in

Other

0% 20% 40% 60% 80% 100%

10 Common signs of unstable data foundation

Data Management is the key challenge in meeting Basel II

Source: IBM Institute for Business Value analysis, Banks and Basel II: How Prepared Are They?, October 2002interviews with 32 Financial institutions worldwide

1. Inability to gather data for new reporting requirements.

2. Difficulty complying with regulatory requirements like Basel II Accord

3. Senior management questions quality, timeliness, reliability of information used to make multi-million dollar decisions

4. Inability to consolidate data from multiple diverse sources

5. Senior Management requests for information require intensive manual effort to respond, and far longer than desired.

6. Difficulty in building a single architecture to address both data consolidation and data aggregation requirements.

7. Multiple databases or spreadsheets storing similar data; no common data “dictionary” across the enterprise

8. No ownership of data9. There’s no single enterprise view of data10. Difficulty answering questions about the

origins and business processes performed against data

Common definition of LGD, PD, EADCommon customer identifier

Cross Modelling Solution

A complex International banking group

Group

Personal FinanceWholesale Banking CorporatePrivate Banking and Asset Management Credit Cards

Discretionary Portfolio

Management

Fixed Income, Equity and derivatives

UK retail North America

Asia Pacific

Singapore Hong Kong Japan

• Capital allocation• Capital Calculation

• Risk Strategy• External Reporting

Enterprise

Data Warehouse

Data store

IBM’s Basel II Architecture

Core Banking Products

Credit

Collaterals

Customer

Loss Data

Data sourceMetadata

Warehouse Administration

Transformation& calculation

Basel II CreditRisk Engine

Basel II Op. Risk Engine

Basel II MarketRisk Engine

Non-Basel IIRisk Engines

Extr

actio

n,

Valid

atio

n

Extraction Data Marts

ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience

Rating, PD, LGD,CCF Models

Enterprise

Data Warehouse

Data store

Where does XBRL fit?


Credit

Collaterals

Customer

Loss Data

Data sourceMetadata







Extr

actio

n,

Valid

atio

n


ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience


XBRLXBRL

XBRL

1 2

3

XBRL for Basel II analytics

Many Analytics requirements

• Credit Risk Profile• Credit Risk Assessment • Credit Risk Mitigation

Assessment• Operational Risk Assessment• Portfolio Credit Exposure• Security Analysis• Liquidity Risk• Collections Analysis• Involved Party Exposure• Location Exposure• Non Performing Loan Aggregate data for analytics

• Multiple Sources• Different periods• Different rules

Enterprise

Data Warehouse

Data store


Credit

Collaterals

Customer

Loss Data

Data sourceMetadata







Extr

actio

n,

Valid

atio

n


ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience


XBRL1

Enterprise

Data Warehouse

Data storeEnterprise

Data Warehouse

Data store


Credit

Collaterals

Customer

Loss Data

Data sourceMetadata
















Non-Basel IIRisk EnginesNon-Basel IIRisk Engines

Extr

actio

n,

Valid

atio

n

Extraction

Extr

actio

n,

Valid

atio

n


ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience


XBRL1

XBRL for Basel II reporting

Enterprise

Data Warehouse

Data store


Credit

Collaterals

Customer

Loss Data

Data sourceMetadata







Extr

actio

n,

Valid

atio

n


ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience


XBRL2

Enterprise

Data Warehouse


Data Warehouse

Data store


Credit

Collaterals

Customer

Loss Data

Data sourceMetadata

















Extr

actio

n,

Valid

atio

n

Extraction

Extr

actio

n,

Valid

atio

n


ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience


XBRL2

Many reporting requirements

• External• Disclosures• Regulatory

• Internal• Group• Subsidiary• Management reporting

• Integration with other reporting requirements

• IAS

Aggregate data for reporting• Multiple Sources• Different periods• Different rules

Common definition using XBRL

Definition of Internal Basel II taxonomies:

• Define an organizational metadata layer

• Traceability back to transactions

• Common repository for changes and updates to requirements

• Enhance group ability to consolidate data

• Improve data qualityBasel II is an opportunity for banks to force its subsidiaries and business units into following a common understanding of data, driving common standards into the organisation . XBRL can be THE standard

Enterprise

Data Warehouse

Data store


Credit

Collaterals

Customer

Loss Data

Data sourceMetadata







Extr

actio

n,

Valid

atio

n


ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience


XBRL3

Enterprise

Data Warehouse


Data Warehouse

Data store


Credit

Collaterals

Customer

Loss Data

Data sourceMetadata

















Extr

actio

n,

Valid

atio

n

Extraction

Extr

actio

n,

Valid

atio

n


ResultData

ResultData

ResultData

ResultData

Disclosure

Management Data

Reporting

Group

Regulatory

External Audience

Internal Audience


XBRL3

How is XBRL solving some of the data management issues?

1. Inability to gather data for new reporting requirements.

2. Difficulty complying with regulatory requirements like Basel II Accord

3. Senior management questions quality, timeliness, reliability of information used to make multi-million dollar decisions

4. Inability to consolidate data from multiple diverse sources

5. Senior Management requests for information require intensive manual effort to respond, and far longer than desired.

6. Difficulty in building a single architecture to address both data consolidation and data aggregation requirements.

7. Multiple databases or spreadsheets storing similar data; no common data “dictionary” across the enterprise

8. No ownership of data9. There’s no single enterprise view of data10. Difficulty answering questions about the origins

and business processes performed against data

XBRL for Basel II Analytics

XBRL for Basel II reporting

Common definitions using XBRL

Leveraging XBRL for Basel II

Daniel D’Amico, London UKIBM BSC, Financial Services Sector,Risk and [email protected]

Documents

Leveraging XBRL for Basel II