Personal Bank Lending Data at a local level


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In December 2013 major lenders in the UK published details of borrowing to individuals and businesses at a local 
level for the first time.  This voluntary move by select institutions provides details of more than £1 trillion of 
lending  across  Britain  comprised  of  residential  mortgage  balances,  loans  to small  and  medium‐sized 
enterprises (SMEs) and unsecured loans to personal customers. 
The industry‐wide data has been compiled jointly by the British Bankers’ Association (BBA) and the Council 
for Mortgage Lenders (CML). 

This presentation outlines what the data shows in Birmingham.

The full report can be downloaded from here:

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Personal Bank Lending Data at a local level

  1. 1. Personal lending data at neighbourhood level in Birmingham Richard Browne Partnership Manager Birmingham City Council Twitter: @richardbrowne80 @fairbrum #fairbrum 20th March 2014
  2. 2. Background • Long campaign by the likes of the Community Investment Coalition, and Centre for Responsible Credit • Announced by Treasury in July last year, finally released in December • Danny Alexander: ‘enable smaller lenders identify gaps in the market and allow businesses to hold their local bank to account where they aren’t lending’.
  3. 3. So what has been released? • Participating Lenders - Barclays, Lloyds, HSBC, RBS, Santander, Clydesdale & Yorkshire and Nationwide. • Data released in December for loans at end of June on: – Personal Loans – Residential Mortgages – Loans to SMEs • Postcode sector level • Level of outstanding balances based on BoE reporting classifications • Does not show the number of loans in each postcode sector – just the outstanding balances
  4. 4. What is a postcode sector? • 9,000 sectors in UK • Not uniform in size or population • Not coterminous with other boundaries • “Birmingham” postcode area there are 228 sectors, but for Birmingham Local Authority boundary there is 126
  5. 5. Birmingham Totals • £463 million loans • Per capita less than England as a whole • Difficult to get a true picture of average lending
  6. 6. Lending Vs Deprivation • Some correlation between lending and deprivation although not statistically significant
  7. 7. Citysave Comparison • Compared credit union loan data with the banking data • Responsible correlation that there were lending in the same areas
  8. 8. Conclusions • Data release welcome but limited • Useful for Credit Unions and LAs • Be even more useful to have high interest lenders data • Need more attributes to really begin look at the complexities of how banks lend • Could look at the HDMA dataset in the United States • Additional information includes: number of transactions, individual loans amounts, and markers of level of interests
  9. 9. Richard Browne uk Twitter: @richardbrowne80
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