What is Basel II?

Basel II is the second Basel Accord and represents recommendations by bank supervisors and central bankers from the 13 countries making up the Basel Committee on Banking Supervision (BCBS) to revise the international standards for measuring the adequacy of a bank's capital. It was created to promote greater consistency in the way banks and banking regulators approach risk management across national borders.

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• Minimum capital requirements - the ability to capture and record risk
• Supervisory review - the use of risk information in running the business
• Market discipline – the statutory reporting of a company’s risk position

Status

Implementation of Basel II is in 2 waves. Wave 1 covered pillars 1 and 3 of the accord stating that financial institutions must comply with the ‘minimum requirements’ by 1st January 2007 for collecting and reporting financial risk. This was not easy:

Many institutions either missed this deadline, or implemented a much simpler risk solution than they had intended. In nearly all cases the technology requirements were underestimated and the processes and people were not adequately prepared.

Wave 2 covers pillar 2 and enforces the banks to prove that they are managing their business appropriately through a close loop implementation of the risk position they have from wave 1. This deadline is 1st January 2008. It is likely that the same problems will apply and that much manual processing will be still be in place long into that year before an automated architecture is deployed effectively.

Data Requirements for Basel II

The main components of data management which are necessary for a successful implementation of a Basel II programme can be summarized as:

• Access: Access to all relevant data sources, internal and external.
• Quality: Completeness, accuracy and appropriateness of data.
• Reconciliation of data across risk management, reporting and accounting systems.
• Auditability: Transparent processes with audit trail on data.
• Delivery: Deliver data when, where, and how needed.
• Availability/Scalability: High availability of data and ability to process large volumes of data.

Typical data issues challenging banks in their efforts to implement their compliance programs include:

• Unreliable aggregate exposure data. Duplication of customer records, errors in customer’s group hierarchies and incomplete data on loan maturity dates raise regulatory concerns on the determination of aggregate exposure amounts – a key requirement for the corporate asset class.
• Disorganised collateral records. Deficiencies in collateral identification and linkages between collateral codes and exposure amounts pose questions on reliability of LGD estimation and risk mitigation calculations in both retail and corporate books
• Incomplete loss data records. Ill-defined business processes and incomplete data recording materially affect LGD calculation and estimation.
• Inaccuracies in rating and scoring data history. Major gaps in this data raise challenges to validation of banks’ PD estimation processes.

How does Exception Engine help?

In many cases the complexities of the data sources and the rules required for capturing and calculating risk mean that it is often impossible for automated technologies – e.g. data quality and data integration products – to fully ensure data is 100% accurate. Consequently manual intervention is necessary, and this is the missing technology component in all existing solutions on the market.

Exception Engine provides workflow, routing, full auditing and approval processes of who changed the data, when, why and who subsequently approved those changes – all of which are essential for compliance with the Accord.