The credit decision: adopting a multi-bureau approach


Here at StubbsGazette we pride ourselves on the lengths we go to in order to build the most comprehensive picture possible of an individual or business’ creditworthiness. We believe that creditors – and just as critically those individuals and businesses – deserve nothing less.

This, for example, is why we find something like the decision of the Courts Service to block access to unregistered judgments so frustrating. Any measure that moves – unjustifiably in our view – to reduce transparency in the area of credit, simply ends up having a detrimental effect on the economy as a whole as it ensures that the quality of information available to decision-makers is less than what it might be.

Yet, while we diligently trawl the records for judgments, bankruptcies, Revenue defaults and much more, that is not to say StubbsGazette on its own has the complete picture. In fact, we are stout defenders of a multi-bureau approach to the credit decision.

It is a fact that much of the data sourced by credit information service providers (CISPs) is common (although StubbsGazette is fortunate to have additional proprietary information to call upon, for example our debt collections service feeds in to our bureau data). Three of the typical sources used by CISPs are the electoral roll, provided by local councils; judgment data provided by the Courts Service; and shared credit account data provided by credit providers.

Yet in spite of the large level of commonality of data sources, bureau ratings can differ significantly. Often this is down to loading, storage and retrieval issues around the data. For this reason, combing the results of more than one bureau can result in a significant uplift in information quality. In the UK, for example, it was found that in a study of three bureaus' detection of default information connected with a data sample, just 57% of defaults were common to all three credit information providers.

 Multi Bureau Approach diagram 1











For this reason, a multi-bureau approach, especially where the data of the core provider leads to a marginal credit decision, is recommended. Using this approach, the credit decision is based on the combined results where common items such as overlapping judgments are de-duplicated.

That is why we have long argued that the proposals contained in the Credit Reporting Market Structure Report of 2011, that proposes that there be mandatory reporting for all credit providers to a Central Credit Register (CCR)(and not to approved credit information providers) is a retrograde step.

At best, it places all of the credit providers at a distinct commercial disadvantage to the CCR. At worst, it would mean that all of the current credit information providers in the state would be basing their ratings and decisions on incomplete and misleading data.  It encourages – in fact institutionalizes – a monopolistic environment that stifles competition and innovation. This is recognized in all leading economies with a developed and sophisticated credit culture, for example the UK and US.

 Multi Bureau Approach diagram 2

Credit information service providers should be autonomous commercial businesses that collect and maintain credit data for the mutual benefit of the bureau, the contributing members and the credit industry. The most sophisticated credit information service providers will seek to enhance the lenders’ contributed loan/account performance data with judgment and insolvency data sourced from the courts and public registries.

The Irish credit information industry has evolved into an increasingly sophisticated and vital component of the economy. We can she typical evolution of a credit bureau from inception can be seen in seven distinct phases:

1.    Re-distribution of public record data
2.    Enhancing public record data with contributed negative data
3.    Further enhancements to include both positive and negative data
4.    Improvements in data matching and handling aliases and financial associates
5.    Development and implementation of scoring models
6.    Collection of additional demographic data, such as voter rolls, identity numbers
7.    Collection of additional sources of non-credit data such as: driver/vehicle registrations; property ownership etc.

Marginalising the organizational and intellectual capital that has gone into this evolution is foolish. There are excellent examples of best practice in credit information, such as the Standing Committee on Reciprocity in the UK or the Credit Union Shared Data Association in Ireland. These are governing associations of members, formed to establish and oversee mutual and reciprocal policies and practices of the contributing members to all of the participating credit information service providers.

The governing association typically owns the collective data, although the credit information service providers charge for credit enquiries made against the database and any other aggregated data requested by the Central Bank. All credit information service providers are subject to the country or region's legislative policies, especially pertaining to data privacy and consumer protection. The credit information service providers are independently owned, and act as custodians of contributed data.

The size of the market and market forces should dictate how many credit information service providers operate in any one market and not the imposition of a behemoth with the potential, as things stand, to limit rather than expand the credit perspective.






 
 

Top Judgments Registered

11.11.2020

Urban Green Private Limited
Address: R/o Atkins Hall, River Towers, Lee Road, Cork
Amount: €734,547.90

10.11.2020

Thomas O'Brien
Address: Castlegrace, Clogheen, County Tipperary
Amount: €93,749.13

10.11.2020

Margaret O'Brien
Address: Castlegrace, Clogheen, County Tipperary
Amount: €87,979.01

06.11.2020

Sean Browne
Address: 24 Woodlands Avenue, Arklow, Co Wicklow
Amount: €38,094.60

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