Statistics. Analysis of revisions - General Insurance Institution-level Statistics. 10 June 2015

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1 Statistics Analysis of revisions - General Insurance Institution-level Statistics 10 June Australian Prudential Regulation Authority

2 Analysis of revisions - General Insurance Institution-level Statistics This paper provides an analysis of the revisions to the General Insurance Institution-level Statistics (GIILS) publication and notes the intention to improve the identification of any future revisions. Revisions analysis APRA publishes revisions to its statistics to improve the usefulness of its publications. APRA publishes revised statistics when better source data becomes available or if compilation errors are uncovered. Better source data typically become available from resubmission of data by insurers. APRA lists significant revisions to statistics and aims to explain the circumstances under which they were revised. Significant revisions currently include those revisions more than $50 million and over five per cent of the original value. These significant revisions are listed in the revisions section of the GIILS publication. To minimise the frequency of revisions, APRA analyses revisions to identify potential improvements to source data. Such analysis is considered good practice. The International Monetary Fund s (IMF s) Data Quality Assessment Framework (DQAF), for example, states that statistical agencies should ensure that studies and analyses of revisions and/or updates are carried out and used internally to inform statistical processes. 1 The DQAF also recommends that studies and analyses of revisions are made public. Accordingly, APRA has analysed revisions to some of its statistical publications and released the analysis to improve the usefulness of APRA s statistics. APRA s analysis of revisions in GIILS shows that, in the five editions from June 2012 to June 2014: 2 there were 116 individual insurers, an average 2,034 new data items published each edition of GIILS, for a total of over 37,000 data items in the database version of GIILS as at 30 June 2014; there were 339 revisions to statistics (an average of 68 data items revised per edition). This means that the likelihood of a data item being revised within a year of publication was approximately two per cent; revised statistics in each edition of GIILS were due to resubmissions of data by nine per cent of insurers on average; some 15 revisions (about four per cent of all revisions) were more than $50 million and five per cent of the original value ( significant revisions ); and revisions to capital adequacy information accounted for 42 per cent of all revisions. Following the analysis of GIILS revisions, APRA intends to improve the usefulness of GIILS by individually listing revisions of more than $1 million and ten per cent of the original value in future editions of the publication. 1 IMF - Data Quality Assessment Framework, 2 The level 2 data and Lloyds data revisions were not included as part of this analysis due to the limited number of revisions to be analysed. The June 2012 edition contained revised data due to a change in compilation technique that were not included as part of this analysis; Australian Prudential Regulation Authority 1

3 Number of revisions General Insurance Institution-level Statistics (GIILS) publication The GIILS publication contains individual insurer and insurance group information about financial performance, financial position and capital adequacy. The publication is available on APRA s website at Insurance-Institution-Level-Statistics.aspx. GIILS is published semi-annually. The published data cover the financial years that ended in the 12 months prior to the reference period of the publication. GIILS is available in three versions: an Adobe PDF version for printing, a Microsoft Excel version, and a database version (in a Microsoft Excel file). The PDF and Excel versions contain data for the past 12 months, while the database version contains a full time series as well as additional statistics that can be used for further analysis. Revisions typically impact the database version of GIILS. Data in GIILS are sourced from audited annual returns reported by insurers. As at 30 June 2014, 116 individual insurers appeared in GIILS. Analysis Frequency of revisions in GIILS In the two years between June 2012 and June 2014, there were a total of 339 data items revised in GIILS, an average of 68 data items revised per edition. Figure A shows the number of revisions for each edition during this period. For context, there are approximately 2,034 new data items published in each edition of GIILS and as at June 2014 there were over 37,000 data items in the database version of GIILS. This means that the likelihood of a data item being revised within a year from its publication was approximately two per cent. Figure A Number of revised statistics in GIILS Jun-12 Dec-12 Jun-13 Dec-13 Jun-14 GIILS edition All revisions published in the past five editions of GIILS were due to resubmissions of data by insurers. The number of insurers that resubmitted data varied over this period, as shown in Figure B. For example, the December 2013 edition of GIILS had the most Australian Prudential Regulation Authority 2

4 Number of revisions Number of insurers revisions (172 revisions), and 15 insurers contributed to these revisions. This compares to the June 2014 edition of GIILS, which contained 34 revisions, the result of resubmissions by ten insurers. On average, ten insurers (nine per cent of all insurers) contributed to revisions in each edition of GIILS between June 2012 and June Figure B Number of insurers contributing to revised statistics in GIILS Jun-12 Dec-12 Jun-13 Dec-13 Jun-14 GIILS edition Scale of revisions in GIILS APRA has listed and quantified revisions over $50 million and five per cent of the original value in each edition of the database version of the GIILS publication. As shown in Figure C, the majority of revisions have fallen below this significance threshold in the past five editions from June 2012 to June Figure C Significant revisions in GIILS Jun-12 Dec-12 Jun-13 Dec-13 Jun-14 GIILS edition Number of revisions not listed and quantified Number of listed and quantified revisions Over the past five editions of GIILS analysed, there were 15 revisions of more than $50 million and five per cent of the original value that were listed and quantified. These accounted for four per cent of the 339 revisions. Australian Prudential Regulation Authority 3

5 Improving the usefulness of GIILS APRA aims to improve the usefulness of GIILS by increasing the range of revisions that would be listed and quantified. From the June 2015 edition of GIILS (to be published 11 November 2015), APRA intends to list and quantify revisions over $1 million and ten per cent of the original value. If this new threshold had been in place for the analysed editions, around 32 per cent of all revisions would have been listed and quantified, compared to the four per cent of all revisions which were listed under the current threshold of $50 million and five per cent. By increasing the range of the revisions that are listed and quantified, users will be able to more easily identify impacts on their analyses of the data. The effect of the current threshold is that only revisions significantly exceeding the average change in statistics from one period to the next are listed and identified. The new threshold however, has been determined to more closely align with average movements from period to period, as shown in Figure D. For example, 54 per cent of all statistics changed by $1 million and ten per cent from the previous period, compared to 13 per cent of the statistics that changed by $50 million and five per cent. 3 As such, listing and quantifying revisions under the new threshold will provide users with insight into those revisions that exceed typical movements in the statistics, and will therefore likely impact users own analysis. Figure D Periodic movements - current threshold versus new threshold $50m and five per cent (current threshold) $1m and 10 per cent (new threshold) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Proportion of all movements Above threshold Below threshold Nature of revisions in GIILS Revisions to capital adequacy data items accounted for 42 per cent of all revisions of GIILS data between June 2012 and June Table 1 shows distribution of data items revisions by subject for both GIILS and, for context, the entire general insurance data collection. Capital adequacy data makes up 63 per cent of the general insurance data collection. About 30 per cent of all revisions in GIILS were components of capital adequacy items: capital base, capital surplus, and prescribed capital amount. As these items are totals that are calculated using other items in the data collection and publication, they are impacted by revisions to the data items that were used in the calculation. 3 Based on the movements in all data items from the June 2014 edition of GIILS Australian Prudential Regulation Authority 4

6 The revisions of financial positon data items were to reflect updated actuarial valuation of outstanding claims liabilities and premium liabilities, which then led to revisions to insurers total liabilities. Table 1: Distribution of data items revisions by subject Data items by subject Capital adequacy of which: Capital base, prescribed capital amount, and capital surplus Data items by subject (per cent) Per cent of all revisions Per cent of the general insurance data collection Other capital adequacy items Financial performance Financial position Summary The number of revisions to GIILS is about one per cent of the total number of statistics published in GIILS. On average, around nine per cent of the insurers resubmit past periods data in each edition of GIILS, which are then published as revised statistics. Revisions to capital adequacy data items were the most common revisions. To improve the usefulness of GIILS, APRA intends to list and quantify revisions to statistics that are at least $1 million and ten per cent of the original value. APRA also intends to work with reporting insurers, and with their auditors, to improve the quality of initial data received, and therefore further reduce the resubmission rate. Australian Prudential Regulation Authority 5

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