Could new SME lending policies be bad for start-ups?

Paolo Siciliani.

Since the financial crisis a focus for policy has been to increase the flow of lending to small and medium-sized enterprises (SMEs): encouraging lending to SMEs is seen as crucial to economic recovery. One of the more recent proposals is to force large banks to share credit data  on their SME customers with rival lenders. The idea is that, by reducing the informational advantage that large banks currently have over their rivals, this could encourage new entrants and growth in SME lending by smaller lenders, which in turn should improve the diversity and hence resilience of the supply of credit to SMEs. However, this post argues that the kind of sharing of SME credit data being envisaged could squeeze lending to SMEs without a credit history.

A boost to alternative sources of credit to SMEs

In the UK there is a lot of momentum behind proposals to mandate the sharing of SME credit data amongst potential lenders more widely than is currently the case, in order to facilitate greater competition among lenders. SMEs are considered to be important contributors to employment and income, and drivers of productivity improvement and innovation. Accordingly, it is argued that there is a case for regulatory intervention, in particular, in the aftermath of a financial crisis. The idea is that, by sharing SME credit data more widely, other lenders – particularly non-bank lenders – will be able and willing to step in, thus smoothing the supply of credit over the cycle.

In November 2014, the Bank of England published a summary of feedback report to a Discussion Paper that the Bank published in May 2014 on the costs and benefits of sharing UK credit data. The summary of feedback report advocated greater sharing of UK SME credit data.  Greater sharing of UK SME credit data among SME lenders is also encompassed in the Government’s recently enacted Small Business, Enterprise and Employment Act 2015.  Finally, the Bank has spearheaded an initiative to extend sharing of UK SME credit data to boost the provision of trade credit by non-financial firms to their customers.  Trade creditors are not likely to be a competitive threat to banks in the provision of credit to SMEs, rather they are a complementary provider of short-term credit. Accordingly, what follows doesn’t apply to the the sharing of credit information with trade creditors.

The rationales for credit data sharing

The main rationale for sharing credit data is to reduce the information asymmetry faced by rival lenders, which penalises good borrowers in the absence of a credible signal of their creditworthiness. SMEs are said to be particularly dependent on banks for their external finance because they are typically informationally opaque, which makes it difficult for prospective lenders to tell good borrowers from less creditworthy ones, thus leading to credit rationing across the board.

In addition to the possibility of credit rationing caused by this ‘adverse selection’ problem outlined above, a ‘moral hazard’ problem can possibly also be at play. Higher interest rates (i.e., to discount the risk that borrowers are not as good as claimed) reduces borrowers’ expected rewards from commercial success, thus either demotivating them or pushing them to select riskier projects (i.e., with a potentially higher pay-off).

Although the decision to lend to a new SME without a credit history is risky, it may still pay off in the event that the untested borrower turns out to be a good credit risk even though rival lenders will still be unable to tell. In other words, the current lender may enjoy a degree of market power over the ‘locked-in’ borrower. This ‘hold-up problem’ may result in higher loan rates for good borrowers than in the case that the information relied upon by the current lender was shared with rival lenders.

For example, the current lender may benefit from the granular financial data gathered by having provided the SME’s owner with a business current account alongside the loan. In this case, rival lenders, particularly those not offering a current account service (e.g., specialised lenders or peer-to-peer lenders), would be at a competitive disadvantage where the assessment of SMEs’ creditworthiness depended on this type of proprietary information.

Information sharing addresses the asymmetric information problem and so should lead to improvement in credit supply. Rival lenders would find it easier to target good borrowers, which would tend to put downward pressure on lending rates. In turn, borrowers would have strong incentives to do well, in the knowledge that the current lender will not be able to opportunistically engage in rent extraction via uncompetitive lending rates. Moreover, to the extent that information sharing allows unconventional (non-bank) lenders to compete more effectively, the supply of credit may prove more resilient in the event that stressed banks collectively reduced their SME credit exposure.

The risk for an unintended consequence

The impetus to screen out low-quality borrowers is even stronger when competition compresses interest rate margins. The erosion of the informational rents due to increased pricing rivalry enabled by information sharing might be detrimental for prospective good borrowers lacking a credit history. Gehrig and Stenbacka (2007) argued that current lenders, wary of future pricing rivalry, may charge higher rates to untested borrowers. This could deter potentially good borrowers who are uncertain about whether they would be able to afford the loan.

Therefore, under information sharing untested good borrowers might be particularly vulnerable to the ‘adverse selection’ problem. This might be particularly the case given that the time and resources needed to identify revealed good borrowers under information sharing (i.e., thanks to the availability of reliable codified information) ought to be lower than in the case of the initial screening and early monitoring of borrowers without a credit history.

Ultimately, there is a risk that a lending strategy based on screening and early monitoring of untested borrowers might be less preferred to an alternative lending strategy solely based on competing for revealed good borrowers. This may be particularly the case for new and/or smaller lenders whose aim is to quickly grow in scale whilst perhaps lacking the resources and expertise needed to screen and monitor untested borrowers.

In summary, there could be a trade-off between static efficiency under the existing stock of information and dynamic efficiency due to the reduced incentive to generate new information. This may be problematic from a macroeconomic point of view in terms of lost productivity potential over time, to the extent that the flow of credit to new SMEs is important.

The efficiency trade-off has parallels in the debate about the role of Intellectual Property (IP) rights in fostering socially valuable innovation. The basic tenet here is that due to the non-rivalrous nature of information – and, hence, the trivial cost of its reproduction once the information has been developed – static efficiency would be maximised under universal access to the information in question. However, this may prevent the recovery of the initial (fixed) investment needed to develop the information in the first place. Hence dynamic efficiency would suffer as a result of the suboptimal production of new valuable information.

Tweaking the mandatory disclosure of SME credit data

The analogy with IP rights is useful when thinking about a potential solution. To address the inter-temporal trade-off IP law introduces a right to exclude access to (and therefore the commercial exploitation of) the protected information. On the one hand, the creator can be confident that, as long as he can envisage some valuable use for the protected information, the initial fixed investment incurred to produce the information can be recovered without facing fierce competition from opportunistic imitators. On the other hand, this restriction of competition is not absolute, but is mitigated by the temporary duration of the IP protection. Moreover, the IP right owner may also face some competitive restraints exerted by competitors not reliant on the protected information (e.g., Amazon can rely on customer feedback to decide whether to extend a loan to sellers).

By the same token, a case can be made such that the mandatory disclosure of credit data about SME borrowers without a credit history (e.g., without an existing credit scoring record) should only apply after a temporary exemption period needed to incentivise lenders to take risks in discovering whether new borrowers are good or bad. Arguably, this proposal would only affect a small fraction of the entire SME population (i.e., start-ups without a credit history), thus preserving all the important benefits arising from wider credit data sharing outlined above.

This is also particularly interesting from a macroeconomic perspective, given that by varying the length/scope of the temporary exemption (i.e., either mechanically or on a case-by-case basis), policy makers could use this instrument countercyclically (i.e., by lengthening/broadening the exemption during a period of undesired credit rationing), thus in principle contributing to the smoothing of the credit supply over the cycle.

In practical terms, the main challenge would be one of calibration. The higher the proportion of untalented entrepreneurs (i.e., the probability of default is high) and the stronger is competitive rivalry among lenders (i.e., the risk of poaching is high), the longer should be the exemption period.

In conclusion, there is a lot to be gained from the mandatory sharing of SME credit data, in particular, in favour of non-bank lenders. However, we should be mindful of the risk that improved competition for existing good SME borrowers may come at the detriment of unrevealed good ones. Hence it may be argued that there should be a temporary carve-out for the latter in order to preserve lenders’ incentives to do their job, that is, to (prudently) take risks by lending to start-ups.

Paolo Siciliani works in the Bank’s Prudential Policy Division.

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