Does increased credit data sharing really benefit low income consumers? Damon Gibbons

Transcription

1 Does increased credit data sharing really benefit low income consumers? Damon Gibbons February 2013

2 Acknowledgements I wish to place on record my thanks to Mark Waters and Greg Brown from Church Action on Poverty and Thrive for initiating the work with residents in Stockton on Tees that underpins this report, and for their support throughout the project. I am also grateful to Brighthouse, Perfect Home, and Buy as you View for their active participation in the project as well as to the credit reference agencies, Experian, Equifax, and Call Credit. Finally, I am also grateful to Andrew Thompson at Friends Provident Foundation for his helpful comments on an early draft of the report. However, the views expressed are those of the author alone. Page 2

3 Contents Chapter One: Introduction... 4 Chapter Two: How Consumer Credit Data Sharing Works... 9 Overview of the UK credit data sharing system... 9 Credit scoring...15 Affordability assessments...17 Analysis of credit data to inform public policy...20 Chapter Three: Data Sharing and the High Cost Credit Sector...21 The arguments for data sharing in the high cost sector...22 The impact of data sharing in the home credit industry...28 Developments in the rent-to-own market...37 The payday lending sector...41 Chapter Four: Conclusions and Recommendations...54 Bibliography...62 Page 3

4 Chapter One: Introduction This report concerns the UK system of consumer credit data sharing and whether or not this provides benefits for lower income consumers. Much has been made of the potential benefits of increased credit data sharing for low income consumers in recent years, with arguments advanced by the Competition Commission, Office of Fair Trading (OFT) and the Department for Business, Innovation and Skills (BIS), that this: Can increase competition in credit markets and reduce the price paid by consumers with good repayment records; Can help lower income consumers build up a credit record, enabling them to transition from high cost to more mainstream lending, and Assists consumer credit firms to make more responsible lending decisions. However, whilst the sharing of consumer credit repayment histories is long standing amongst mainstream credit providers such as banks and credit card companies, data sharing in the high cost credit markets 1 is a relatively recent development and there has, to date, been little attempt to critically assess the arguments advanced in its favour. There are reasons to be cautious about the extent to which increased data sharing will have positive impacts for lower income consumers, especially in the current economic climate where credit conditions generally remain extremely tight. In these circumstances, although more data sharing could enable high cost credit lenders to better identify the risk profile of customers, this could result in a group of lower income consumers with poorer payment histories finding themselves increasingly excluded from commercial credit markets. Some lenders may also simply not choose to use available information to focus on customers with better repayment histories. In the absence of any cap on prices, firms may prefer to continue to target very high risk customers; accepting a high level of default but compensating for this by charging very high prices. In this case, if firms can make a profit 1 Throughout this report the term high cost credit is used to describe that range of lending products primarily used by lower income consumers, including home credit or door-to-door money lending, payday lending, and rent-to-own. Page 4

5 then they have a financial incentive to ignore requirements to lend responsibly or push these to their limits. In addition, although lenders focusing on lower risk borrowers should experience fewer defaults and lower bad debt, there is no guarantee that these savings will be passed onto remaining good payers because of a more general lack of price competition in these sectors. In these cases the benefits of data sharing are increased profitability for lenders, not lower prices for consumers. Increased data sharing is therefore unlikely to lead to better consumer outcomes unless firms use it to (i) focus on customers with lower risk profiles; (ii) experience a reduction in bad debt levels and increased profitability as a result; and (iii) pass on the benefits of these in the form of cheaper prices to good payers. Finally, the way in which data sharing is undertaken is important. Clearly, the information that is being shared must be sufficient to allow those borrowers who have decent repayment histories and who can afford to take on credit to be distinguished from those with worse records and low levels of disposable income. About this report This report assesses the extent to which the arguments made in support of increased data sharing by high cost lenders are supported by evidence. There is currently a lack of publicly available data to support a detailed empirical analysis of the impacts of increased credit data sharing on low income consumers. As we discuss in chapter two, this information gap arises due to the way in which credit data sharing is governed and conducted in the UK. In the absence of hard data, we draw on alternative sources to critically assess the claims made in favour of increased data sharing. Our primary source of evidence has been qualitative, and has involved detailed discussions concerning the impacts of data sharing with lenders, particularly in relation to the Rent to Own ( RTO ) sector 2, and with other 2 The Rent to Own (RTO) sector of the UK consumer credit market comprises firms providing household goods such as furniture, white goods, and electrical items on rental agreements to lower income households with an option for the consumer to purchase these at the end of the rental Page 5

6 stakeholders including credit reference agencies ( CRAs ). These discussions have taken place as part of a wider project to improve consumer outcomes in the RTO sector led by Thrive - a community organising project established by Church Action on Poverty and operating in Stockton on Tees. Thrive has undertaken several community-based action research projects on issues facing households in the Teesside area, which have highlighted financial exclusion issues in particular. 3 As a result of research conducted in partnership with Durham University, Thrive successfully managed to engage a group of residents in 2010 to discuss their use of RTO firms, and particularly Buy as You View ( BAYV ), which has a strong presence in the region. With financial support from the Friends Provident Foundation, Thrive then brought residents from Stockton on Tees together with the leading RTO lenders 4 throughout 2011 and 2012, resulting in a number of high level commitments from the industry to improve practice. The initial phase of the project was reported in September , with commitments provided by the lenders to: Ensure that the cash prices for goods are competitive with others in the sector; Use mystery shopping exercises to evaluate how prices are explained to their customers; Provide a range of payment options and to price differentiate between these, for example by offering discounts to people who pay by Direct Debit; Limit default charges; period. The households using firms in this sector, which are also sometimes referred to as weekly payment stores, would otherwise have difficulty paying the cash price for these types of goods and are also limited in their ability to obtain what would be a large amount of credit relative to their income to fund these purchases from other sources 2. 3 See Friends Provident Foundation (2010), Flaherty and Banks (2012). 4 These are Brighthouse, PerfectHome and Buy as You View. We estimate that these three firms have a combined total of approximately 350,000 customers. 5 Gibbons, D. (2012). Improving Practice in the Rent to Own Market. London: Centre for Responsible Credit. Page 6

7 Put in place policies and procedures to help people in financial difficulty and to refer customers in arrears to free, independent, debt advice agencies; Develop clear policies for future complaints handling, and Provide clear annual statements of account. Some individual firms have gone further in respect of their own commitments. For example, Brighthouse has committed to ensure that the cash prices of its goods are competitive with high street retailers beyond the RTO sector. However, the residents participating in the project were also keen to discuss pricing issues. In particular, they felt that there was no benefit for customers to maintain payments as a good repayment history did not result in a lower price of credit, and long term customers paid as much as new ones although they posed a lower risk of default. The firms responded to this challenge by indicating that greater analysis of credit data sharing could help. As the three main RTO firms were all actively considering entering into data sharing arrangements a second phase to the project was agreed, which involved ongoing discussions with the RTO firms concerning their plans. Although these discussions were initially focused on the RTO sector it became clear that the issues under consideration were also of relevance to low income borrowers more generally. As a consequence, this phase of the project was subsequently widened to include the home credit 6 and payday lending markets: The home credit market was subject to a Competition Commission inquiry in 2006, which found that there was a lack of effective price competition that was costing consumers at least 75 million per year. To help address this, the Commission has required the major home credit lenders to share repayment data since March However, there has been no formal evaluation of the impact of this. The payday lending market has been heavily criticised for irresponsible lending practices and both the OFT and BIS have identified increased data sharing by firms as 6 The largest home credit lender, Provident Financial Plc, was invited to participate in the project but did not do so. Page 7

8 a potential means of addressing this. Again, there has been little evidence provided by either the OFT or BIS to support this. In addition to direct discussion with RTO lenders, the methods employed in the project have therefore also included the review of published reports and public statements made by leading firms in the home credit and payday sectors and discussion with three CRAs: Experian, Equifax, and Call Credit. We are particularly grateful to the CRAs for their input to the project. However, the views expressed within the report are the author s alone. The remainder of this report is structured as follows: Chapter two provides a brief overview of the rationale for data sharing and of the UK s credit data sharing system. The chapter then proceeds to examine the relationship between the sharing of information and the use of credit scoring to inform lender decision making within the context of regulatory efforts to prevent irresponsible lending. Finally, the chapter highlights how the current governance arrangements for data sharing restrict access to analysis of CRA held data. In chapter three we then proceed to detail and critically assess the specific measures that have been taken forwards within the home credit, rent-to-own and payday lending sectors in recent years. Finally, in chapter four we bring together our conclusions and set out a number of recommendations for future policy and practice. Page 8

9 Chapter Two: How Consumer Credit Data Sharing Works This chapter begins with a basic overview of the rationale for consumer credit data sharing and proceeds to provide a description of the governance and conduct of data sharing in the UK. The chapter then looks at how credit data sharing underpins credit scoring and lending decisions, drawing out some of the implications of the current system for consumer behaviour. It then turns to the work that CRAs have been doing to support affordability assessments, as required by the OFT s Irresponsible Lending Guidance. Finally, the chapter highlights the restrictions that the current system places on access to analysis of CRA held data. Overview of the UK credit data sharing system The rationale for data sharing The fundamental driver for lenders to share information about their customers is to help them address the fact that their knowledge of a borrower s likelihood to repay is incomplete and is affected by the extent to which other credit and financial commitments, beyond the lender s own agreements, are in place and whether or not the required repayments are being maintained. Without data sharing an information asymmetry arises in that the borrower has better information than the lender concerning their ability to repay. As Turner and Varghese (2010) put it: In lending, the problem of asymmetric information stems from the fact that a lender s knowledge of a borrower s likelihood to repay (their "risk profile") is imprecise and must be inferred based upon available information. The lender cannot solely rely on information provided by the applicant but must verify the information. The assessment of risk is crucial as loans involve an agreement to pay in the future. Borrowers have incentives to misrepresent their risk profile, but even when borrowers are truthful, a lender must still evaluate their claims. One common result of information asymmetries is the misallocation of credit, as risk profiles are incorrectly assessed in both directions with high-risk borrowers confused for low-risk ones and vice versa. In the presence of information asymmetry lenders are forced to either: Page 9

10 Charge higher prices than would otherwise be the case, in order to make provision for a potentially high level of bad debt and/or; Ration access to credit for example by providing only a small amount of credit to a new borrower and making further advances conditional on prompt repayment. However, both of these mechanisms create problems of their own. Lower risk customers are charged higher prices than they warrant and subsidise the cost to the lender of missed payments and defaults by others. Higher prices can also lead to adverse selection the prices are off putting to lower risk consumers and so lead to only those borrowers with a high risk of default applying. Credit rationing may mean that people who are otherwise good risks are unable to obtain the quantity of credit that they need. What is more, these consumers have to build up a relationship with a single lender in order to obtain higher amounts of credit and cannot easily switch to other firms in the market without going through this process of step up lending all over again. The lack of data sharing also runs the risk of limiting price competition because: Consumers cannot exert pressure on prices by shopping around, due to the lack of a portable record of payments that they can show to other lenders, and New firms can be reluctant to enter the market due to the amount of time required to build up a reliable customer base and the initially high losses that would be incurred whilst attempting to do so. Both of these types of problem are apparent in the UK s high cost credit markets where data sharing has traditionally been limited. For example, the Competition Commission s 2006 inquiry into price competition in the home credit market concluded (para 7.21) that: a customer without a portable credit record cannot credibly demonstrate creditworthiness to any potential lender with whom he does not have a relationship, without taking the time to build such a relationship and demonstrate creditworthiness through a series of loans over time. This reduces a customer s ability and incentive to seek alternative sources of credit at the point at which the customer might be seeking to Page 10

11 switch (thus erecting a barrier to switching), and inhibits other lenders from competing for the business of a customer of whose creditworthiness they cannot be confident. This inhibition applies to other home credit lenders, to prospective entrants and to providers of other forms of credit. Thus it substantially reduces the competitive pressure on incumbent lenders which might otherwise exist from customers switching, or threatening to switch, to lower-priced alternatives. Conduct and Governance More mainstream lenders have long since recognised the need to address information asymmetries through the creation of data sharing arrangements and these have become progressively more sophisticated over the years. In the UK, data on borrowing patterns and repayment history is shared through commercial credit reference agencies ( CRAs ) which also collate additional information from public registers and other sources, including for example, utility providers. CRAs are regulated by the Consumer Credit Act 1974, which also provides consumers with the right to check the information held about them and ensures that CRAs put in place a procedure to allow consumers to rectify any errors which exist on the record. There are currently four CRAs operating in the UK: Experian 7, Equifax 8, Callcredit 9, and CoreLogic Experian was created in 1996 following the combination of the former TRW Information Systems & Services and the CCN Group by the British conglomerate, GUS plc. In 1982, CCN became the first credit reference agency to operate in the UK and its amalgamation with TRW, the largest credit bureau in the US in 1996 established CCN (renamed as Experian the following year) as a global leader in the industry. Experian subsequently demerged from GUS plc in 2006 and now operates in Latin America, Asia and Eastern Europe as well as the US and UK. Aside from credit referencing the company also provides data and analytical services to clients in a wide range of other sectors including retail, telecommunications and healthcare. 8 Equifax was created in the US as the Retail Credit Company. It changed its name to Equifax in 1975 and is listed on the New York Stock Exchange. Equifax currently employs approximately 7,000 people in 15 countries through North America, Latin America and Europe. Its operating revenue in 2011 was $1.9 billion. 9 Callcredit was founded in 2000 and is headquartered in Leeds. Since beginning its operations the company has focused on developing products to support affordability assessments. 10 CoreLogic is a US based company which has started to provide credit referencing services in the UK. In this respect it focuses on non-traditional markets and, through its Teletrack product, provides real-time transaction processing to support the risk assessment needs of payday loan providers, and other consumer credit lenders which primarily offer products to people with impaired credit histories. Page 11

12 The starting point for all CRAs is to provide access to publicly available data that can be used by lenders to confirm the identity of a prospective borrower and which could provide basic information concerning their creditworthiness. This information includes records of insolvencies, court actions for debt, and electoral register details concerning the address of the borrower. This is then built upon by establishing closed user groups of lenders who share information about their customers on a reciprocal basis. This means that companies wishing to search for information about an applicant s repayment record on the CRA databases must also put the same level of information about their own customers onto the system in return. It is important to note that two different levels of information can be shared within the CRAs closed user groups, and that lenders can elect to supply (and therefore receive): Negative data only this is information concerning agreements that are in default, defined as where the relationship has broken down such that the lender would no longer wish to do business with the borrower if they have the choice. It also requires the agreement to be at least 90 days past due, unless there is fraud; Full or positive data - In addition to the negative data above, this includes monthly updated information on available credit limits and current balances and payment performance showing where they have been paid on time or not. This has been further added to in recent years by the sharing of behavioural data. For example, in 2008 the credit card industry agreed to share information about the amount of a customer s last payment, and whether this was equivalent to the minimum payment; changes to credit limits; and the extent to which customers withdraw cash on their account. The sharing of credit data is governed by a set of principles adopted by the Steering Committee on Reciprocity (SCOR). SCOR is not an organisation in its own right but is a committee comprised of representatives from trade associations and credit industry bodies 11. The Principles of Reciprocity (p.3) state that: 11 The trade associations and industry bodies represented on SCOR are the British Bankers Association (BBA), British Retail Consortium (BRC), Building Societies Association (BSA),Consumer Credit Association UK (CCA), Consumer Credit Trade Association (CCTA), Council of Mortgage Lenders Page 12

13 Data are shared only for the prevention of overcommitment, bad debt, fraud and money laundering, and to support debt recovery and debtor tracing, with the aim of promoting responsible lending. Credit data is therefore not allowed to be used for the generation of marketing offers to customers of other lenders signed up to data sharing, although screening of potential new prospects is allowed, as is an assessment of the likelihood that people will respond positively to offers. In addition, changes in the status of an existing customer s credit records are now often reported by CRAs as part of their services to alert lenders to material events that could affect the running of their accounts and which may cause lenders to revise the credit limits set for their customers or target them for new credit products. For example, Equifax s advertising 12 states that: We can help you: Sort your customers into categories using a wide selection of personal attributes, so you can up-sell, cross-sell, manage risk and collect outstanding debts more efficiently; Identify when separate records should be attributed to one individual, and quickly build up a detailed picture of your business s relationship with that customer; Monitor individuals and businesses for credit limit changes, CCJs and other changes that affect their value as customers. These services can therefore be used by lenders on an ongoing basis to tighten underwriting procedures for new loans to existing customers, as we report appears to be the case in respect of Provident Financial on page 32. The individual CRAs hold separate databases. Experian s data sharing scheme is called Credit Account Information Sharing ( CAIS ); Equifax s system is called Insight; and Callcredit s is called SHARE. CoreLogic s Teletrack product provides users with access to a (CML), Credit Services Association (CSA), Energy Retail Association (ERA), Finance & Leasing Association (FLA), Mobile Telcos and The UK Cards Association. The credit reference agencies represented on SCOR are mainstream credit reference agencies Experian, Equifax and Callcredit, plus niche market credit reference agency CoreLogicTeletrack. The chairmanship of SCOR rotates between member trade associations and industry bodies Page 13

14 database called AWARE which is focused on high cost consumer credit products, as well as to Experian s broader CAIS database through a partnership arrangement between the two companies. Although the databases are distinct to each company, much of the information held on them is the same because this includes public information, and because many lenders often choose to provide information to more than one, or even all, of the CRAs. Nevertheless, there are also some differences in the databases which may be of particular significance to different lending sectors. These can arise because of specific agreements with non consumer credit companies such as mobile phone or utility providers to share information on customer repayment histories with one or other of the CRAs. For example, in July 2012 Equifax announced that it had secured the agreement of Severn Trent Water to share repayment data on its accounts with consumer credit lenders through its Insight product. CRAs have also recently been developing specific products to meet the need of high cost credit providers. This is occurring because traditional CRA databases are based on the provision of monthly credit reports. However, most high cost credit products require payments to be made on a weekly basis. As a consequence, the traditional monthly credit reports generated by CRAs may be of limited value for high cost credit providers for two reasons: Weekly payment records have to be aggregated by lenders and submitted as a monthly report on the customer s repayment record. This is currently done in a way which may flatter some borrowers by ignoring a number of missed payments within the month. We report further on this in the following chapter; and The increasing speed with which offers of credit are made in the high cost sector may mean that some borrowers are able to take out more than one credit agreement in the period before these are included on their monthly credit report. This second point has become a particular concern in respect of the payday lending sector. As a result CoreLogic has developed a real-time database, which includes details of loans as soon as they are originated and which can be consulted by payday lenders whenever a new application is received. Again, we report further on real-time reporting in the following chapter. Page 14

15 Credit scoring Once a lender has provided information to a CRA, they may use information on the database to conduct credit checks and inform their decisions as to whether or not to advance credit; how much to advance; and the price of that offer. To inform their decisions in these respects lenders either use their own credit scoring models or use generic scorecards which have been developed and are provided as an additional service by the CRAs themselves. These are used alongside any existing information about customers available to the lender from prior applications and agreements. The credit scoring models, whether they are bespoke to the lender or have been developed by the CRAs, are commercially sensitive and are not in the public domain. This makes it impossible for consumers to know precisely how their repayment behaviour is affecting their ability to access credit or the terms on which this is being offered, although they are most likely aware that the presence of defaults and/or other adverse information such as late or missed payments, will have a negative overall impact to some degree or another. This lack of certainty has a number of implications for consumer behaviour. Firstly, some consumers may be overly negative about their prospects for accessing mainstream credit and not apply. For example, following a survey of 1,000 social housing tenants, Ellison (2012) reports that 38 per cent of respondents believed that they would find it difficult or impossible to borrow from a mainstream lender although only 23 per cent actually had experience of applying for this and being turned down. Commenting on this, Ellison notes that: There was a sense that credit reference agencies and credit scoring models were designed to identify those in work, higher earners, married couples with the proverbial 2.4 children and active consumers. Essentially the feeling was that the focus of credit scoring models was not on people like me. The sense was that those on low incomes were seen as either invisible or as less desirable customers. Secondly, Japelli & Pagano (1999) propose that sharing information about defaults creates a disciplinary effect (i.e. encouraging people to maintain payments in order to ensure that they retain future access to credit markets): Page 15

16 If creditors are known to inform one another of defaults, borrowers realise that defaulting on their current lender will damage their rating with all other potential sources of credit and thus try harder to avoid default. The impacts of this disciplinary effect are not clear for example it is not known how far some consumers will go in terms of cutting back on other areas of their household budget in order to make repayments for fear of losing access to credit markets in the future. Thirdly, consumers may also be tempted by claims that taking out high cost forms of will enable them to repair their credit scores, even though this may not, in fact, have a significant impact on their overall credit scores given prior repayment problems. For example, the websites of some payday lenders indicate that they share repayment information with CRAs and that maintaining payments is therefore likely to have a positive impact on credit scores. However, the extent to which this will offset any prior credit default history is likely to be limited, and in some cases the appearance of payday loan borrowing on a credit record could be used as a negative indicator regardless of whether or not this was repaid on time. Speaking to The Guardian in November , Experian s Head of Consumer Affairs, James Jones, explained: some high street lenders might see the fact that you've resorted to payday credit as a sign that your finances are under pressure if a particular lender's experience is that customers who take out payday loans are more likely to miss their repayments, this will be reflected in their credit scoring. Whilst the disciplinary effect has benefits for lenders, it may not be entirely positive for consumers, although its impact in terms of generally reducing default levels may be passed on by firms in the form of lower interest rates when the market is assessed as a whole. Finally, the relative impact on credit scores of the different options that consumers could take when they are struggling to afford their repayments is also unknown. In particular, consumers are not able to compare the impacts on their future credit scores of entering into 13 Page 16

17 a debt management plan with the alternative options of using formal insolvency procedures such as bankruptcy. Whilst the ultimate decision to make credit available remains that of the lender the processes underpinning this have become increasingly automated and in many areas of the consumer credit market are heavily reliant on the generic scores that CRAs provide. For example, Experian advertises a suite of Delphi scorecards, which it states can be used in any consumer credit application processing environment to predict the likelihood that a new applicant for credit will become a good payer if accepted. The Experian scorecards are used by over 150 UK financial institutions generating in excess of 70 million scores each year. It could therefore be potentially useful for consumers to know more about their CRA generated score and the likely impacts of changes in that score on their ability to access credit and/or on the prices that they would pay for this. The CRAs have taken some steps in this direction by promoting services that allow consumers to monitor, on an ongoing basis, the details held on their credit record. These services also provide a very basic overall rating as to the likely ability of people to obtain credit, and are promoted on the back of a growing concern about the importance of maintaining a good credit history 14. However, they do not go as far as setting out the precise scores that the CRAs themselves generate for lenders 15 or explaining the relative weight of the different variables that underpin these. Affordability assessments In recent years the CRAs have also developed a range of products designed to make it easier for lenders to assess the affordability of credit. This has been driven by the need to respond to both regulatory and, given the increasing financial pressures faced by 14 For example, Callcredit offers a free monitoring service through their Noddle product, which provides consumers with a credit score out of five (with five being the best). However, this is likely to be significantly below the level of detail of the scores provided to lenders. In addition, it also appears that the monitoring services offered by the CRAs are used an opportunity for the targeted marketing of additional credit products to users, which may conflict with the CRAs traditional role as a trusted source of information. 15 It is unclear as to what rights individual consumers have to access the CRA generated scores; for example whether these could be obtained through a subject access request made under the Data Protection Act. Page 17

18 households, commercial concerns. With respect to consumer credit (as opposed to mortgage) lending, the OFT Irresponsible Lending Guidance, published in 2010, places lenders under an obligation to conduct borrower-focused affordability assessments. In conducting these, lenders should take into consideration the potentially adverse impact that a loan agreement can have on the borrower's financial situation. Further details of the affordability assessment contained in the OFT Guidance (para 4.2) indicate that before granting credit, significantly increasing the amount of credit, or significantly increasing the credit limit under an agreement for running account credit, creditors should take reasonable steps to assess a borrower's likely ability to be able to meet repayments under the credit agreement in a sustainable manner. (emphasis in the original). The concept of sustainability is elaborated further by the OFT (para 4.3) as meaning credit that can be repaid by the borrower: Without undue difficulty in particular without incurring or increasing problem indebtedness; Over the life of the credit agreement or, in the case of open end agreements, within a reasonable period of time; Out of income and/or available savings, without having to realise security or assets. The OFT then provides a definition of without undue difficulty (para 4.4) as meaning the borrower is able to make repayments (in the absence of changes in personal circumstances that were not reasonably foreseeable at the time the credit was granted): While also meeting other debt repayments and other Normal/reasonable outgoings and Without having to borrow further to meet these repayments. It should, however, be noted that the OFT guidance does not specify what constitutes reasonable outgoings and therefore provides only a general framework within which lenders are expected to operate. Individual firms may take very different approaches when Page 18

19 assessing affordability, and there is no clear line in the sand concerning what is, and what is not, acceptable. Nevertheless, CRAs have responded to this regulatory driver by improving their metrics to help lenders with the conduct of affordability assessments. These have built on the traditional approach of credit scoring based on a consumer s propensity to pay (as indicated by their repayment history), by providing a more detailed analysis of people s use of the credit facilities available to them, and the speed with which outstanding debt levels have been accumulated. Further to this, CRAs have been making greater efforts to assess the level of income and non-credit expenditure: the goal being, as Experian put it, to estimate disposable income and true affordability : In respect of income assessment and verification: Experian and Call Credit are both now providing an analysis of the turnover of funds within bank current accounts in order to enable lenders to check stated borrower income against this, and Call Credit and Equifax indicate that they can now also provide shared access to validated salary and income details from loan applications, with Call Credit indicating that approximately 97% of all eligible current account information is now available in our Affordability Universe 16. In respect of expenditure: Experian indicates that lenders can draw upon assumed levels of reasonable day to day expenditure for different household structures and types provided by the Family Spending survey published by the Office for National Statistics. There have also been recent developments to increase the types of information on expenditure being input directly into CRA databases, including in respect of utilities and mobile phone repayment records 17. Whilst these services allow lenders to more accurately determine the level of disposable income available to a borrower, the decision as to how much to lend relative to disposable income currently remains that of the lender itself. We return to this point in chapter three. 16 It should, however, be noted that lower income consumers are less likely to have a current account or, where they have one but are not in employment, to be using this on a regular basis. 17 Consumer Focus reported in 2011 that the largest energy companies were sharing data concerning the payment histories of their accounts through the CRAs. Page 19

20 Analysis of credit data to inform public policy Although the sharing of credit data is facilitated by the CRAs it is important to note that the data itself remains the property of the lenders, and that SCOR has placed a number of restrictions on how information and analysis conducted on the data can be shared. Specifically, the Principles of Reciprocity state that only basic data can be shared with external bodies, including Government and regulatory agencies, without the prior approval of SCOR. Basic data is limited to the volume (number of accounts) and value (outstanding balance) of records by finance sector, product, full or partial data sharing in operation, secured or unsecured lending, and geographical location (but at no greater level of granularity than post town). Analysis of derived credit scores, current performance status or trends, or views expressed as a result of analysis of either individual or combined closed user group records is not allowed to be shared externally except with the prior authorisation of SCOR. As requests to SCOR have to be approved by the main credit trade associations these are unlikely to be successful if the release of analysis is likely to lead to criticism of the credit industry. The restrictions put in place by SCOR therefore clearly limit the extent to which regulators and wider stakeholders are able to determine trends in consumer overindebtedness and affordability and prevents a full empirical analysis of, for example, the extent to which existing data sharing arrangements have helped people transition from high cost credit products towards the financial mainstream. Page 20

21 Chapter Three: Data Sharing and the High Cost Credit Sector In general, the arguments in support of greater data sharing in the high cost sector are the same as for mainstream lending the removal of information asymmetries should have positive implications for lenders in identifying and accurately pricing for risk and result in lower costs, particularly in respect of defaults. However, the assumption that these savings will ultimately be passed onto borrowers with good repayment histories in the form of lower prices is open to challenge. This is both because consumers using high cost credit have been identified as price insensitive (Office of Fair Trading, 2010a) and because there are significant barriers to entry for firms wishing to enter some of the sectors 18 : Price insensitivity means that consumers do not select lenders on the basis of cost - for example prioritising the speed of decisions and delivery of credit instead. In these cases having a portable record of repayment history may be of less significance than it is for consumers in more mainstream markets; Even if consumers are price sensitive there may be a shortage of firms offering lower prices for them to switch to, and new firms may be deterred from entering the market because of the high costs of getting to scale. In addition, there are concerns that lower income consumers with poorer credit records may lose out as a result of greater data sharing because mainstream lenders will find it easier to identify these and be less willing to lend. For example, in its submission to the Competition Commission inquiry into home credit the Royal Bank of Scotland indicated that 19 : It should be acknowledged that better information might highlight customers with poorer credit histories with the attendant consequences this may bring. The counter argument to this is that for lenders, the increase in data would be a further tool to help to identify overindebtedness. 18 For example, Gibbons, 2012, p.5 reports how Brighthouse have identified barriers to market entry in the RTO sector within their most recent annual report cotland.pdf Page 21

22 Although increased data sharing could support more responsible lending decisions, the implications of this, in terms of a greater number of excluded people, need to be considered especially as Social Fund provision, which may otherwise have been expected to meet some of the needs of this group, is currently being localised and is likely to be harder to obtain as a consequence 20. Alternatively, it is possible that some lenders could use the increase in information to identify people with poorer credit records and continue to lend, but at higher prices (see for example, Marron 2007). This chapter therefore examines in further detail the arguments that have been made in support of greater data sharing in high cost credit users in recent years and the specific actions that have been taken forwards in this respect within the home credit, rent-to-own and payday lending sectors. The arguments for data sharing in the high cost sector The Competition Commission and Home Credit Data sharing in the high cost credit sectors is a relatively recent development and, although there were instances of some high cost lenders using CRAs in advance of 2006, was particularly spurred on by the Competition Commission inquiry into the home credit or door to door money lending market in that year. Finding that home credit lenders were making excess profits of at least 75 million per year, the Competition Commission imposed a requirement on lenders to share customer repayment data 21 from March 2008 onwards via CRAs on the basis that (para 9.12) this would: Stimulate price competition between existing home credit lenders for good customers, as these customers would be better able to demonstrate their creditworthiness to all major 22 lenders in the market place; 20 A Centre for Responsible Credit report on the impacts of Social Fund localisation is forthcoming. 21 For further details of the specific requirements placed on lenders in the home credit market see box 2, below. 22 The Competition Commission s requirement for data sharing was imposed only on those home credit companies with more than 59 agents and turnover of at least 2 million. As a consequence some of the smaller companies are not required to share customer repayment information although they may still do so on a voluntary basis. Page 22

23 Reduce the barriers to entry to the market for new firms looking to enter into the home credit market by removing the incumbency advantage held by existing lenders. The Competition Commission found that existing home credit lenders were making significant excess profits 23. However, new firms wishing to enter this market were at a disadvantage to existing ( incumbent ) lenders because they had no access to information about borrower creditworthiness and therefore risked attracting customers with poor repayment records and incurring high levels of bad debt. This could be sufficient to deter firms from entering the market, so limiting the number of firms competing for customers; Enable providers of other (more mainstream) forms of credit to offer credit to home credit customers (in particular those with good payment records) than would have occurred previously. The Competition Commission noted that data sharing could be expected to increase the number and variety of credit offers to home credit customers and impose further competitive pressure on the prices charged by home credit lenders. The overall outcome anticipated from data sharing was that customers with good payment records would enjoy access to a greater number of credit sources, and pay a lower price for credit. How home credit data is shared It is important to note that the data sharing remedy imposed by the Competition Commission requires that home credit customer data be identifiable as such within CRA held records so that other lenders can make their own assessment as to its value in predicting default on their own products. This is particularly important as home credit differs significantly from mainstream credit products by virtue of the fact that it is collected from the customer s home, and repaid on a weekly, as opposed to monthly basis. These two features raise doubts about the extent to which a good repayment record on home credit 23 The Competition Commission s Home Credit inquiry found (para 7.2) that Profits substantially in excess of the typical cost of capital for a large home credit lender have been persistently earned by firms that represent a substantial part of the market. The Commission estimated that these excess profits amounted to approximately 375 million over the period 2000 to Page 23

24 loans can be read across into a predictive score for mainstream products, which are more likely to collected monthly by Direct Debit from a bank account. The imposition of the Competition Commission s data sharing remedy in 2008 required lenders, SCOR, and the CRAs to agree a protocol for the reporting of weekly repayment data. To fit with existing CRA reporting mechanisms this required weekly payments to be aggregated and reported on a monthly basis. CRA databases generally report monthly repayments as missed if they are not paid within two weeks of the due date. However, the home credit product is often offered on the basis that lenders are willing to tolerate occasional missed payments at no charge to the customer. Reporting all late or missed payments to the CRAs would therefore constitute a significant change in the nature of the home credit offer and could result in customers finding it harder to obtain credit from other sources despite being told that occasional missed payments are viewed as acceptable by the home credit lenders themselves 24. To address this issue, the home credit lenders, CRAs and SCOR agreed a protocol which reports home credit payments as missed only if all of the weekly repayments due in any rolling four week period have not been received. Therefore a customer can miss up to three payments in a month and still be reported as up to date with their payments. In fact, because the CRAs require lenders to submit repayment data on a monthly basis and generate monthly reports, a customer could miss up to seven weekly payments in a row before the credit record shows a missed payment. This is illustrated by table 1, on the following page. 24 In addition, it should be noted that it is also possible for payments to be missed because home credit agents fail to call on the borrower s home to collect these. In these circumstances it would clearly be unfair to the borrower for these to be recorded on their credit record. However, we are not aware of any measures that have been put in place within the home credit industry to protect against this. Page 24

25 Table 1: An example of home credit data reporting over an 8 week period Week Payment history Payment received No payment No payment No payment No payment No payment No payment No payment Detail submitted to CRA/ shown on credit file Credit report submitted by lender as no payments missed Credit report submitted by lender showing one month's payment missed Table 1 shows how it is currently possible for a home credit customer who makes a payment at the beginning of the month (week 1) to miss up to seven subsequent payments prior to other lenders being alerted of this fact. This is because the protocol agreed by home credit lenders, SCOR, and the CRAs requires that home credit repayments are reported as missed only if the borrower fails to make all of the payments in a rolling four week period. In the example provided this is not the case due to a payment having been made in week 1. As a consequence the report made by the lender later that month (in week 4) is that the customer is up to date with payments. Although the borrower is then assessed for the purposes of reporting as having missed a payment in the following week (week 5), this is not actually reported until the end of that month, by which time a further three payments may also have been missed. Alternatively, it should be noted that even if all three of the payments due in weeks 6, 7, and 8, had been made then the borrower would still be reported as having missed a payment due to the fact that payments were missed in weeks 2, 3, 4, and 5. As a consequence, the system of home credit data sharing does not distinguish between customers with very different repayment patterns. Page 25

26 The OFT and BIS arguments for data sharing Similar arguments to those presented by the Competition Commission in 2006 have since been advanced in favour of increased data sharing by the OFT following its High Cost Credit Review in That review was launched because of: concerns that consumers of high-cost credit, including many on low incomes, suffer from a lack of options when seeking credit, that the price they pay for credit is too high, and that the recession has limited suppliers' willingness to lend money. The review covered a number of high cost credit sectors, specifically pawnbroking, payday lending, home credit, mail order and rent-to-own, and provided an assessment of competition in each of these markets, finding that (pg. 6): On the demand side, there is relatively low ability and effectiveness of consumers in driving competition between suppliers, given their low levels of financial capability; On the supply side, sources of additional supply such as mainstream financial suppliers seem to be limited, and In such circumstances, competition on price is limited and there appear to be some suppliers charging higher prices than would be expected. As a result, the OFT proposed a number of remedies, including, with respect to the payday lending and rent-to-own markets, a recommendation (pg.7) that: Government works with credit reference agencies to explore ways in which payday lenders and rent-to-buy suppliers could provide suitable information to credit reference agencies about the payment performance of their customers, in turn allowing those with good payment records to use mainstream lenders more easily in the future. This recommendation was considered in further detail by Government during its subsequent Consumer Credit and Personal Insolvency Review conducted by BIS between October 2010 and November In its final report BIS stated (2011, paras 34-35) that The Government wants to explore whether more high cost credit providers could provide information to credit reference agency databases and that it would therefore initiate