1. Introduction

In recent years, the Office for National Statistics (ONS) and the Bank of England (BoE) have been working to transform the financial account statistics, including those of the banking sector (central bank, banks and building societies). This collaboration has resulted in improvements to the quality and granularity of banking statistics available within the UK financial accounts, including the ability to produce statistics on a whom-to-whom or flow of funds (FoF) basis, to meet evolving user needs.

This article gives an initial insight into the main improvements made available by the new data for the banking sector ahead of their inclusion in the enhanced financial accounts FoF experimental statistics release later this year.

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2. Background

The Office for National Statistics (ONS) has an ambitious programme to transform its statistics, informed by our Economic Statistics and Analysis Strategy and with the aim of increasing the robustness and quality of UK economic statistics. Working in partnership with the Bank of England (BoE), one element of our transformation work is the development of the banking sector statistics for enhanced financial accounts (EFA) – in particular, more detailed “flow of funds” (FoF) statistics – to meet evolving user needs.

The main aims of the EFA initiative are to improve the coverage, quality and granularity of financial statistics. This includes producing whom-to-whom statistics for the UK National Accounts – identifying the counterparty information for each financial transaction rather than the total asset and/or liability position for each institutional sector in isolation. Whilst data on the banking sector have always been a reliable source and constitute over half the value of the UK balance sheet, a collaborative effort was needed to produce these data on a FoF basis. This provides an opportunity to implement many improvements including:

  • granular, sector-based statistics more consistent with the European System of Accounts 2010: ESA 2010, the legislative framework within the European Statistical System

  • greater granularity of transaction breakdown, providing additional economic insight that was previously invisible in some areas

  • a clear split of sterling and foreign currency transactions involving UK building societies across all financial instruments

  • new metadata and structure resulting in a more user-friendly resource

As announced in the Transformation of Economic Statistics summary, the ONS will publish experimental FoF statistics in Quarter 4 (Oct to Dec) 2019. This article provides an initial overview of experimental balance sheet statistics for the banking sector, otherwise known as “monetary financial institutions” (MFIs). The ESA 2010 sub-sectors that are included in MFIs are:

  • S.121 Central bank

  • S.122 Deposit-taking corporations except central bank

This article will highlight some of the main successes and improvements made by the ONS and BoE, as well as new insights made available as a result. However, it should be noted that these data will not form part of the upcoming UK National Accounts, The Blue Book. This is because of the continuing work being undertaken to fully establish the impact these improved data will have across the national accounts.

For this reason, the EFA MFI data published in this article are deemed Experimental Statistics, and as such, they will differ from UK National Accounts data. They are being published now to provide an update on the joint ONS and BoE “flow of funds” initiative. The first indication of the impact of the data will be the EFA FoF experimental statistics, to be published on 26 November 2019, with the ambition of incorporating these Experimental Statistics into the UK National Accounts in the future.

The EFA MFI data will be one of several sources contributing to the EFA FoF experimental statistics. Final estimates for the MFI sector in EFA FoF may incorporate additional data sources and therefore could differ from the data presented in this article.

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3. Impacts of changes

Overall position of banking sector

Figures 1 and 2 show the asset and liability holdings of monetary financial institutions (MFI) for Quarter 4 (Oct to Dec) 2015, 2016 and 2017 from the enhanced financial account (EFA) MFI data compared with figures currently published in the UK National Accounts (Blue Book 2018). For each year shown in the chart the left bar represents Blue Book 2018 (BB) and the right bar represents the new EFA data.

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Overall, the EFA MFI data show lower levels, noticeably in liabilities. This is because they are presented here as raw data from the Bank of England (BoE), whereas the Blue Book data are final aggregates including all current data sources in the financial account.

The absence of additional sources is particularly evident in bonds, which is partly because of a market rate adjustment applied to Blue Book figures. However, this does not explain the entire difference. At the time of writing, the Office for National Statistics (ONS) is awaiting additional data from commercial sources to address this in addition to ongoing quality assurance by the BoE.

Despite these differences, the comparison between EFA MFI data and Blue Book data is useful as it illustrates some of the important changes made.

The biggest changes by magnitude occur between transferable deposits and other deposits and between short-term loans and long-term loans. The context for this difference is in the classification changes within overall deposits and loans respectively. The EFA MFI dataset more accurately separates all deposits into transferable and other deposits, and all loans into short-term and long-term, which is in line with the ESA classifications. However, overall the deposit and loans data are consistent with current national accounts figures when aggregated to deposits and loans, as shown in Figures 3 and 4, and therefore will not change the overall position of MFI assets and liabilities. These changes will be further expanded on in the next section.

One other change worth noting here is the increased figure for “other accounts receivable/payable”. For MFIs this consists of items in suspense and transmission. Functionally this classification is applied to credits or debits relating to customers’ accounts but not yet assigned to a specific customer. More information can be found at the page detailing Further details about other banks’ balance sheet data on the BoE website. The increase is because of improved coverage of this financial instrument and will account for a small decrease in deposit and loan positions.


A clear split of transferable and other deposits has been made. Transferable deposits are deposits exchangeable for currency on demand. Other deposits with MFIs comprise time deposits that cannot be used to make payments except on maturity and also include repurchase agreements made by MFIs. This new split can be seen in Figure 5.

Overall, this split does not affect the total deposit liabilities of MFIs. The levels are near identical; allowing for the slight change because of improved coverage of other accounts receivable/payable and deposits held by building societies in foreign currency.

With this new split a clearer picture can be seen allowing better analysis of trends within individual sectors. For example, the increasing preference of more liquid transferable deposits held by the household sector (S.14) can be seen starting in 2012 (Figure 6) – a reaction to lower interest rates following the financial crash of 2008. This analysis is currently invisible in the UK National Accounts.

Loans – reclassification

There are two changes to MFI asset positions in loans. The most significant change is the reclassification of some short-term loans to long-term loans. This is illustrated in Figure 7, this time focusing on MFI assets.

In the Blue Book data, long-term loan assets of MFIs consist mainly of mortgages with the remaining loans classified as short-term. However, because of more granular data, we are now better able to distinguish the other loans into short- and long-term loans.

Again, this increase in granularity allows us greater ability to analyse these data in ways that are currently not possible in the national accounts. For example, Figure 8 demonstrates the debt of private non-financial corporations (S.1100P) to UK MFIs. The EFA MFI data allow us to see that most of this debt is long-term liability.

Loans – rest of the world

The second change to loans is the slight increase in the EFA MFI data, mirrored by a decrease in the deposits. This is visible in Figure 7, titled “Comparison of deposit and loan asset positions: Blue Book versus enhanced financial accounts.”

This is because of a new sector split available to us in deposits and loans data to the rest of the world (S.2), which distinguishes between banks and non-banks. Within national accounts, this is currently all recorded as being with rest of the world (RoW) MFIs. As a national accounts convention, all loans between banks are reclassified as short-term deposits.

However, with a new series for UK MFI loan assets with RoW non-banks, we have reclassified a small amount of MFI deposit assets with RoW to MFI loan assets with RoW. This change, while small in magnitude relative to the total assets, has formed part of the effort within the ONS to ensure the EFA MFI data are more compliant with the European System of Accounts.

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4. Other notable improvements

Increase in sector, transaction and currency granularity

In this article, we have focused on the data at a granularity that will be visible in the upcoming 2019 experimental matrix release. However, the Office for National Statistics (ONS) and Bank of England (BoE) have taken the opportunity to introduce further granularity improvements where they could be made available.

These include separate coverage of sterling and foreign currency transactions for UK building societies – to match that already available for banks, further granular definition of some transactions – for example, the ability to view short-term debt securities (bonds) as commercial paper or certificates of deposit – and, as previously mentioned, the ability to separate rest of the world banks from non-bank sectors for some financial instruments.

Improvements like this not only allow more insight into the financial accounts but also enable us to provide valuable information to our stakeholders, including other projects and publications within the ONS.

Metadata and internal structure

To be able to make best use of data, it is essential to assign clear metadata. According to Eurostat, metadata is defined as “information that is needed to be able to use and interpret statistics.” Depending on the presentation of data, this is not always visible to end-users, but the specification of unique, clear and efficient metadata to each time series in the enhanced financial account monetary financial institutions (EFA MFI) data allow us to make the most of this resource.

The metadata applied to the MFI time series are based on the European System of Accounts 2010: ESA 2010, classifying each time series based on the financial instrument, asset sector, liability sector, and currency to name a few. For example, a time series denoting UK deposit-taking corporations’ asset holdings of short-term loans to UK households in pounds sterling would be defined by:

  • instrument - F41
  • asset sector - S122
  • liability sector - S14
  • element - BAL
  • currency - GBP

(Short-term loans, deposit-taking corporations, households, holdings, pounds sterling)

In the explanatory notes, you can see the primary classifications we use for each sector and financial instrument.

In this example, each element of metadata describes one aspect of the time series only, meaning it is easily read by both human users as well as metadata-driven systems within the ONS. This aspect of the work on banking sector statistics allows us to easily filter, analyse and present data from the thousands of time series supplied by the BoE and makes this dataset compatible with the emerging technology platforms. These are critical to transforming data capability as detailed in the ONS business plan and as such, this is regarded as an important outcome of this project.

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5. Summary and next steps

In this article, we have analysed the enhanced financial account (EFA) monetary financial institutions (MFI) data and highlighted the overall positions, shown the increases in granularity available with these data and highlighted examples of economic stories previously invisible in the national accounts.

We have approached the new dataset with a bottom-up development of a new system to maximise the information it offers to the national accounts. As explained previously, these experimental data have not been aggregated with additional sources from national accounts as some of these areas are also undergoing transformation within the wider EFA project. However, we have used the comparison with Blue Book as an indication of changes and improvements available from the EFA MFI data.

Our next steps for banking sector statistics will be to ingest and implement other data sources made available to us by the Bank of England that will further enhance the national accounts. These will include:

  • new Bank for International Settlements (BIS) data, reported to BIS by participating central banks; these data will be used to improve the data on the counterparty relationships between UK non-banks and the rest of the world in the deposit and loan financial instruments

  • enhanced UK industrial breakdown of deposits and loans, allowing more granular insight into UK sectors, particularly those within other financial institutions (OFI – S.124, S.125, S.126 and S.127)

  • bank holding companies, bank-owned financial vehicle corporations and specialist mortgage lenders’ balance sheet data; this, again, will allow greater insight into the OFI sector

In Quarter 4 (Oct to Dec) 2019, we will publish experimental flow of funds (FoF) statistics to provide an up-to-date picture of the EFA initiative as part of the annual update to the flow of funds matrices, which will see the EFA MFI data used alongside other new data sources.

We welcome feedback on our plans and work to date. Please email FlowOfFundsDevelopment@ons.gov.uk with any feedback or questions regarding this article.

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6. Author and acknowledgements

Scott Kilbey, Economics Statistics Development

The author would like to acknowledge the following ONS contributors to this article: Daniel Wisniewski, Grant Symons, Jeremy Heaven, Keith Miller, Sarah Adams, Alaa Al-Hamad, Phillip Davies, Pete Lee, Darren Morgan; and colleagues at the Bank of England: Perry Francis, Matt Davies and Zeeshan Akhtar for their valuable inputs to this article.

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Contact details for this Article

Daniel Wisniewski and Scott Kilbey
Telephone: +44 (0)1633456621