For Banking and Finance, adopting a multi-bureau credit data strategy is often dismissed as “too hard to switch”, “too expensive” or “not important enough”, but this is set to change.

The FCA recently set out its interim findings from the credit information market study.

The study found one of the key aspects of the market not working well is “significant differences in the credit information held on individuals across the three large CRAs”.

But if you can’t rely on one CRA, how do you avoid paying three times for access to bureau data? 

In this article, I talk through why you should consider a multi-bureau strategy, key considerations, and how to reduce volumes without increasing costs.

Let’s get into it. 👇

Why multi-bureau is the future of credit information 

Credit bureaux provide lenders with insight into potential and existing customers. Yet, so much of the value of what they offer depends on the quality and coverage of the information they hold on individuals.

While the FCA wouldn’t expect the CRAs to hold identical information on all individuals, they found “significant differences in the credit information held by the three large CRAs” – information that is particularly important to a lending decision.

The chart below illustrates the differences in the underlying data held by the three large CRAs.

👉As you can see, it is clear from the chart where the bureaux all identify the same individual and the information they hold is different in a proportion of cases.

The bureaux are also not necessarily able to match the individual to a file, and the varying levels of data and scoring methods all lead to different decision outcomes and coverage. 

The good news is: A multi-bureau approach can ensure fintechs are able to utilise additional sources of data and scoring methods available to make better informed decisions. 

However, the FCA found that most lenders (91%) use only one CRA for each application. At the same time, the FCA said a multi-bureau approach could be a key way to mitigate the impact of insufficiently comprehensive and/or inaccurate data.

With this in mind, let’s take a closer look at the key benefits. 

Key benefits of a multi-bureau approach 

There are a range of benefits of adopting a multi-bureau approach. The first obvious benefit is how the use of a wider variety of data can improve financial inclusion, particularly for those with ‘thin’ files. 

This means you can reduce declined lending decisions to those consumers that are in fact creditworthy. This often happens when a lender uses a bureau that doesn’t have the depth and coverage  to make the correct decision.

A multi-bureau approach will also ensure the lenders are seeing the full picture in terms of affordability, as each bureau has access to uneven sources of affordability data.

Another key benefit of Bank and Finance companies using a multi bureau approach is the ability to achieve best in market pricing. For instance, when a bureau knows a customer has the ability to easily use a secondary provider, they tend to price more keenly, and over time, the competitive element to become primary drives the price down.

Additionally, a multi-bureau approach enables access to a wider variety of better quality credit information and encourages the Bureaux to offer searches at a lower cost.

It’s clear to see the benefits of a multi-bureau approach. But how do you adopt this strategy without paying full price for two-three bureaux? 

Key considerations for a multi-bureau data strategy

The truth is, typically, the bureaux will try to increase prices if a lender reduces volumes so that they can work with a secondary or tertiary supplier.

This shouldn’t be the case. 

But we know that other lenders are already receiving lower pricing for lower volumes, therefore you too can get fair market rates by benchmarking and challenging the bureaux to replicate the discounts they are offering others.

In fact, you’ll find that some of the bureaux provide packages that are actually designed for lenders who require a multi bureau approach. The difference in these packages includes flexible usage between contract years, lower minimum commitments, and graduated pricing dependent on volume.

As an interesting side note, larger lenders who have high volumes of business are not aware that smaller volume users are benefiting from much better pricing. Some have already adopted multi-bureau, however, different bureaux are being used in different divisions on different platforms within the company and the lender is unable to switch usage easily, hence pricing has remained high.

The key takeaway is: There is a huge opportunity for fintechs large and small to negotiate better rates. You just need to improve your buying power.

Improve your buyer power

It’s clear to see that today’s credit industry plays out against a new economic and regulatory backdrop. And as all lenders grapple with the challenges in 2023, they’ll need to respond with increased buyer power.

If you take one key point from this blog, it’s this. Bank and Finance companies should optimise their waterfall (which order of bureau/products should be called when onboarding a customer). Conducting retro’s with the bureaux will determine which bureau will deliver more accurate accepts and declines more of the time. The results will drive which bureau to call first in the waterfall and which other bureau should be secondary/tertiary.

And it is not all about coverage and data content where the differences in the bureaux lie. It’s also about the method that the bureau uses to score the data.

In fact, the FCA showed that where the bureaus were all scoring an individual, there was up to a 57% difference in the score (two or more deciles apart).

All the more reason to use the best combination of bureaux, which will benefit the lender and, more importantly, the consumer.

Optimising the type of searches used in the waterfall will reduce costs and can fund the multi bureau approach.

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• Source: https://www.finextra.com/blogposting/23621/have-it-all-how-are-banking-and-finance-unlocking-multi-bureau-data-strategies?utm_medium=rssfinextra&utm_source=finextrablogs