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Focus on: Basel II and Data Management

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Basel II and its requirements for measuring operational and credit risk is one of the key drivers behind the need to accurate and timely reference data. The following is an edited extract of an article written by Dr Urs Bischof, head of VDF engineering at Telekurs Financial and featured in Telekurs’ realtime customer magazine

The New Basel Capital Accord – known as “Basel II” – covers all currently identifiable sources of risk that might jeopardize the security and reliability of the financial system. Financial institutions are being given a degree of freedom in determining the risk management models they adopt subject to approval by the national supervisory authority, and set for final implementation by the end of 2006. All models place high demands on data availability, particularly in respect of credit risk and operational risk.

The new capital standards laid down by Basel II rest on three “pillars”. The minimum capital requirements (Pillar 1) specify the capital ratio to be calculated. The minimum capital ratio of 8% remains, but the definitions of the risk-weighted assets have been changed. In particular, operational risk will be measured for the first time, and there are changes to the treatment of credit risk. The supervisory review process (Pillar 2) ensures that the capital requirements calculated are sufficiently robust by requiring banks to subject their risk management models to regular stress tests and to present the detailed results. Market discipline (Pillar 3) obliges banks to disclose their risk profile and capital adequacy to all market players, thus helping to promote the stability of the financial system.

Of these three pillars, it is the first one that has the most impact on data requirements, given the new requirements for measuring credit and operational risk.

Credit risk: assessment methods and relevant parameters

Credit risks are assessed on the basis of the identifiable characteristics of loans. Under Basel II there are three different approaches to rating borrowers and hence determining the capital required as a cushion against risk. The ratings – an assessment of a company’s ability to repay creditors upon loan maturity – accorded by external rating agencies such as Standard & Poor’s, Moody’s and Fitch are a fundamental consideration in all cases.

The simplest approach – known as the standardized approach – is based purely on external ratings and on the borrower category: governments and public sector entities are given a lower risk weight than banks and other companies. The minimum capital requirement varies according to the rating of these borrower categories. If the S&P rating is BB+/B, for example, the risk weight is precisely 8% of the loan. The higher the rating, the lower this percentage becomes, and vice versa; and the degree of deviation varies according to the borrower category. Claims on unrated borrowers are generally risk-weighted at 8% in the case of sovereigns or companies, 4% in the case of banks and 6% in the case of private individuals. The relevance of these standardized values will emerge in particular when assessing borrowers outside of the American market, as a relatively large number of companies active on the capital market do not have a rating.

The second, somewhat more complex approach is known as the IRB (Internal Ratings Based) approach, where internally developed risk measures take the place of external ratings, though agency ratings may be used for reference purposes. The banks calculate their own ratings on the basis of quantitative factors – especially data obtained from the analysis of balance sheets of loan applicants – and from qualitative factors such as management assessments or a company’s market position. The internal rating is supplemented by the loss rate. This indicates how great the loss of a credit is if the borrower is unable to repay the loan at the due date. A low loss rate is achieved when sufficient collateral is lodged to compensate the lender in the event of default. Conversely, the loss rate is high when unsecured credit is granted. Other factors that determine the overall risk weighting are the remaining maturity of the loan and the actual loan amount outstanding. The latter reduces the risk weight if a loan has already been repaid. Aside from ratings they have calculated themselves, banks also base their IRB approach on the parameters set out by the supervisory authorities. The third approach is known as the “advanced IRB approach”. It is based on the second method but the bank calculates virtually all the risk assessment parameters itself.

Mitigation of credit risk by collateralized transactions

Under Basel II, there are a number of ways of reducing the original credit risk from the levels initially stated in the books. One of the most innovative options is the principle of substituting credit risk by collateral, where the borrower’s risk weighting is replaced by a risk weight corresponding to the collateral securing the loan (“simple approach”). An extended version (“comprehensive approach”) enables instead the value of the collateral to be subtracted from the outstanding value of the loan so as to reduce the total credit volume outstanding.

With both of these risk-reduction approaches, acceptable collateral includes cash deposits, securities or real estate, which the borrower supplies to the bank to secure its repayment. Securities are particularly suitable as they can easily be classified, but a number of conditions must be met for securities to be acceptable for securing all or part of a loan and hence to be recognized as risk-reducing.

As it largely supports these criteria, Valordata Feed permits evaluations for characterising financial instruments as securities eligible as “Basel II collateral” in the context of risk reduction measures.

Operational risk: reduction of risk by active data management

Basel II introduces the term “operational risk” to describe all risks associated with the failure of internal processes and systems, human error and with external events. Two sources of risk in particular that arise in connection with the trading and administration of securities have been highlighted as: business interruptions and system failures that can arise from hardware or software errors and from telecommunications and network problems; and errors in process management or in the execution and transmission of transactions which, for example, can be caused by incorrect data input or unsupervised access to systems.

As with credit risk, Basel II sets out three different methods for calculating the capital charges for operational risk. The banks are largely free to choose and implement the method that they deem most suitable, but they cannot revert to a simpler method after adopting a more sophisticated one without prior consent.

The first and simplest method, the Basic Indicator Approach, requires the bank to hold capital equivalent to a percentage (15%) of average annual gross income over the last three years. The Standardized Approach segments the bank into different business areas, each of which has a capital requirement equivalent to a certain percentage of that area’s gross income. The highest requirements are for Corporate Finance, Trading & Sales and Payment & Settlement (18% each), which are thus implicitly ranked as the areas with the greatest operational risk.

At the other end of the scale are areas like asset management, for which a capital charge of just 12% is required. The Advanced Measurement Approaches (AMA) constitute the third and most complex method. Here, supervisory authorities ascertain whether the bank is able to estimate unexpected losses through a combination of internal and external loss data, scenario analyses, checks and controls, and sets the regulatory capital requirements individually.

In the management of securities information, Valordata Feed offers a number of features that help banks to mitigate operational risk. The high content of machine-readable data elements helps to minimize interruptions in data flows across the entire securities transaction chain (i.e. from trading through to settlement and corporate actions management). In particular, the wealth of reference data facilitates the operation of a descriptive data management system that is compatible with other data sources and permits automated processing: as Valordata Feed maintains more than eight million securities identification numbers and trading symbols, a security can be unambiguously identified at any time and the required descriptive data fed through to other systems. Valordata Feed offers a sophisticated data controlling feature: its daily updating mechanism allows users to identify which individual data elements have changed, and when the change took place. If, for instance, a bank has generated faulty instructions relating to a payment settlement (e.g. for an interest payment, stock dividend, etc.), Valordata Feed will indicate the last status of the corresponding message along with the time of the change and the previous message content.

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