The GFCI provides ratings for financial centres calculated by a ‘factor assessment model’ built using two distinct sets of input:

• Instrumental factors (external indices that contribute to competitiveness): Objective evidence of competitiveness was sought from a wide variety of comparable sources. For example, evidence about the infrastructure competitiveness of a financial centre is drawn from a survey of property and an index of occupancy costs. Evidence about a fair and just business environment is drawn from a corruption perception index and an opacity index. A total of 64 external sources were used in GFCI 7. Not all financial centres are represented in all the external sources, and the statistical model takes account of these gaps;

• Financial centre assessments: By means of an online questionnaire, running continuously since 2007, we now have 32,174 financial centre assessments drawn from 1,690 respondents. Respondents assess the competitiveness of financial centres that they know. The online questionnaire is ongoing to keep the GFCI up-to-date with people’s changing assessments.

The 64 instrumental factors were selected because the features they measure contribute in various ways to the fourteen competitiveness factors identified in previous research. These are shown below:

Table A: Competitiveness Factors and their relative importance

At the outset of the GFCI, a number of guidelines were set out.  These guidelines are to ensure that centre assessments and instrumental factors were selected and used in a way that will generate a credible, dynamic rating of centre competitiveness for financial services institutions.

The guidelines for independent indices used as instrumental factors are:

• indices should come from a reputable body and be derived by a sound methodology;

• indices should be readily available (ideally in the public domain) and ideally be regularly updated;

• relevant indices can be added to the GFCI model at any time;

• updates to the indices are collected and collated at the end of each quarter;

• no weightings are applied to indices;

• indices are entered into the GFCI model as directly as possible, whether this is a rank, a derived score, a value, a distribution around a mean or a distribution around a benchmark;

• if a factor is at a national level, the score will be used for all centres in that country – nation based factors will be avoided if financial centre (city) based factors are available;

• if an index has multiple values for a city or nation, the most relevant value is used (and the method for judging relevance is noted);

• if an index is at a regional level, the most relevant allocation of scores to each centre is made (and the method for judging relevance is noted);

• if an index does not contain a value for a particular city, a blank is entered against that centre (no average or mean is used). Only indices which have values for at least ten centres will be included.

Creating the GFCI does not involve totaling or averaging instrumental factors.  An approach involving totaling and averaging would involve a number of difficulties:

• indices are published in a variety of different forms: an average or base point of 100 with scores above and below this; a simple ranking; actual values (e.g. $ per square foot of occupancy costs); a composite ‘score’;

• indices would have to be normalised, e.g. in some indices a high score is positive while in others a low score is positive;

• not all centres are included in all indices;

• the indices would have to be weighted.

The guidelines for financial centre assessments by respondents are:

• Responses are collected via an online questionnaire which runs continuously. A link to this questionnaire is emailed to the target list of respondents at regular intervals and other interested parties can fill this in by following the link given in the GFCI publications;

• Financial centre assessments will be included in the GFCI model for 24 months after they have been received;

• Respondents rating fewer than 3 or more than half of the centres are excluded from the model;

• Financial centre assessments from the month when the GFCI is created are given full weighting and earlier responses are given a reduced weighting on a log scale:

Chart A: Log Scale for time weightings
 

The financial centre assessments and instrumental factors are used to build a predictive model of centre competitiveness using a support vector machine (SVM). The SVM used for the building of the GFCI is PropheZy – Z/Yen’s proprietary system.  SVMs are based upon statistical techniques that classify and model complex historic data in order to make predictions on new data.  SVMs work well on discrete, categorical data but also handle continuous numerical or time series data.  The SVM used for the GFCI provides information about the confidence with which each specific classification is made and the likelihood of other possible classifications.

A factor assessment model is built using the centre assessments from responses to the online questionnaire.  Assessments from respondents’ home centres are excluded from the factor assessment model to remove home bias. The model then predicts how respondents would have assessed centres they are not familiar with by answering questions such as:

If an investment banker gives Singapore and Sydney certain assessments then, based on the instrumental factors for Singapore, Sydney and Paris, how would that person assess Paris?

Or

If a pension fund manager gives Edinburgh and Munich a certain assessment then, based on the instrumental factors for Edinburgh, Munich and Zurich, how would that person assess Zurich?

Financial centre predictions from the SVM are re-combined with actual financial centre assessments (but not those from the respondents’ home centres) to produce the GFCI – a set of financial centre ratings. The GFCI is dynamically updated either by updating and adding to the instrumental factors or through new financial centre assessments. These updates permit, for instance, a recently changed index of rental costs to affect the competitiveness rating of the centres.

The process of creating the GFCI is outlined diagrammatically below:

Chart B: The GFCI Process

It is worth drawing attention to a few consequences of basing the GFCI on instrumental factors and questionnaire responses:

• Several indices can be used for each competitive factor and there are likely to be alternatives available once the GFCI is established.
• A strong international group of ‘raters’ can be developed as the GFCI progresses.
• Sector-specific ratings are being developed by using the business sectors represented by questionnaire respondents. This could make it possible to rate London as competitive in Insurance (for instance) while less competitive in Asset Management (for instance).
• Over time, as confidence in the GFCI increases, the factor assessment model can be queried in a ‘what if’ mode - “how much would London rental costs need to fall in order to increase London’s ranking against New York?”

Part of the process of building the GFCI was extensive sensitivity testing to changes in factors of competitiveness and financial centre assessments. The accuracy of predictions given by the SVM was tested against actual assessments. Over 85% of the predictions made were accurate.