Aug 2018 | Credit Decisions
By Posted by Jon Roughley

There’s a big opportunity around real-time exchange and aggregation of bank statements in association with other complementary data such as credit information. Part of the opportunity lies in automatically categorising bank statements using data science and machine learning to inform income and expenditure. One of the pieces of work we’ve been doing to help bring open banking to market is to automate and simplify the interpretation of bank-statement data. Work carried out by our DataLabs team means we can now analyse up to 12 months of bank statements in under a second, categorising transactions, identifying income, and qualifying committed and discretionary expenditure.

We’ve done this primarily to inform a customer’s affordability. But it’s the fact that we can do it quickly, and return it to a third party to inform a decision that is generating so much excitement. We’re starting to develop techniques that enable organisations to look at transfers between different accounts, plus credit-card payments to generate a more in-depth understanding of a customer’s financial behaviour. People often have complex financial lives. Being able to aggregate data from different types of payment accounts and observe where money is flowing between accounts means we can help you make sense of your customer’s financial life. You can use the understanding of the ‘peaks’ and ‘troughs’ in their income and expenditure to help them manage the everyday spending, get better deals on products or avoid getting over-drawn. This is particularly important for those customers who are ‘cash strapped’ at the end of each month.

Data science and machine learning underpin a lot of what we’re bringing to market, because we believe this level of detail on a person’s financial behaviours is extremely valuable when making a decision. It can quickly help determine someone’s ability to afford credit, as well as enabling financial inclusion for those who struggle to manage their finances. Other use cases include helping you confirm your eligibility to rent a property or to save for a holiday or pension.

Data-aggregation platform

To help you access this information we’ve built a data aggregation platform. This takes the leg-work out of sourcing data from banks and consolidates the information into a single customer view making it easy to access. Our infrastructure is operational and data can be accessed through our APIs or from a web hosted service with a dashboard that helps you interpret the information. The data we’re making available includes:

  • information from open banking (transactional data) for a consumer or business – 12 months for consumers, 3 years for a business
  • credit scores, as well as business information and consumer demographics
  • Third-party data, such as house-price information, car valuations, and management accounts for small businesses

We can source all of this for an individual or an address, and aggregate it into a single data view of a consumer or business. We can categorise this data ‘on-the-fly’ and, supply back to you via our APIs or web hosted service. In the next few months we’ll be helping clients bring a variety of propositions to market. For example, lenders are looking at this data to inform affordability checks for credit applications or to facilitate a digital mortgage application while others include:

  • promoting fair and responsible gambling in the gambling industry
  • providing personalised credit limits for home shopping
  • automating income and payment history checks for the rental market – this could be done by analysing open banking data and serving that up in real time to inform a letting decision.

As data from open banking starts to flow, and consumer confidence to share data builds we anticipate the emergence of many more use cases.

What’s important for right now is for your organisation to understand the potential of open banking and how you can capitalise on this. Aligning the opportunity to your objectives is important, otherwise it’s easy to lose sight of the purpose and intent.

If you want to personalise a journey, make risk adverse decisions quickly, and use more accurate information to inform an automated decision – then this presents an opportunity – It has particular significance for consumers who have a limited credit history, such as young people, or those who are new-to-country.

For consumers or businesses whose credit history restricts them from getting access to credit it can be used by a lender to provide more detailed understanding and greater assurance of their ability to pay-off the loan.

In an era where value is everything, whether that be for new or existing customers, having the right tools to deliver positive outcomes for you and your customers that enable you to bring new propositions, new thinking and a better more personalised service to life, is important. Open banking exists to bring more value, more competition and better outcomes for consumers and businesses.


Read more about open banking and the new era of data sharing in our whitepaper. You can also read more about the architecture that’s required to service open banking in our guide – here. Important to also be aware of, and to clarify too, is what’s changed and what’s reinforced.