The use and adoption of consumer consented data

The role of Open Banking

Government and lenders want the credit industry to help people when they are looking for, or using credit, whether it be getting on the housing ladder, buying or leasing a car, or supporting customers when they need it throughout the credit lifecycle. Lenders want and need to meet this challenge but in a responsible way.

One core objective is to have the majority of decisions made automatically, only adding friction into the journey where necessary, for example for high-risk affordability assessment or risk of fraud. Lenders predominantly use a customer’s behavioural and external payment performance data, coupled with a small amount of captured data volunteered by a consumer, to make their credit decisions. Captured data is less desirable as it adds friction to the customer journey and often requires validation which can add to the time taken for decisioning.

Customers who want new or additional lending, or further support during the lending cycle, are often prepared to go through extra steps providing the value exchange is right. For example, in new lending, customers need credit to buy what they want or need and are prepared to provide more information, including the sharing of current account data, if it helps them achieve their goal. Customers that require support or interact online may be happy to provide information digitally, including sharing bank account information, if this saves them time or leads to more sustainable credit agreements. Recent examples have also seen some lenders incentivising customers to share their data in return for a better deal on their loan.

Open Banking is of course a primary source of consumer consented data and can prove invaluable across various stages of the customer lifecycle:

• Open Banking in Originations
• Open Banking in Customer Management
• Open Banking in Predelinquency and Collections

However, there are still challenges to overcome when implementing Open Banking technology.

Barriers and challenges to use Open Banking

12 months ago, we reviewed the various barriers which need lifting before lenders and consumers can whole-heartedly embrace Open Banking. Today, it’s clear that some of these barriers are higher concerns than others.

The lender view

There are two key challenges that may be holding lenders back from fully adopting Open Banking:

• Accuracy of categorisation

When considering income, it can sometimes be difficult to understand the intent of the bank transfer, but inferences can be made when the same occurs multiple times. If a consumer changes jobs after a long period of time, is the next credit a salary payment?  For outgoings, some transactions are difficult to classify as the payment description is poor. But perhaps this should be tackled at the source, rather than causing a categorisation issue.

When categorising transactions, some lender solutions have confidence levels attached to each transaction to help with use in decisioning. Despite potential issues with categorisation, this granular information provides a much better view than high level aggregated data sources for cases warranting further assessment.

Suppliers of Open Banking categorisation are also providing greater transparency to lenders on the methodology they use to categorise transaction data to enable accurate monitoring and auditing of their performance.

Some Open Banking solutions use a combination of machine learning – a rules-based approach – coupled with manual review and update, to enhance and monitor the performance to their transaction categorisation tools. Regular release of new versions can help maintain accuracy of data.

• Getting the complete picture

Another challenge is “how do we know we’re looking at a complete picture of the customer’s accounts?” and that they’re not hiding some behaviours in a different account they don’t share.

There are a couple of ways to tackle this both with pros and cons. Use bureau data to understand if they have other accounts (only accounts with credit facility will be shown), but also Account Usage insights allow us to identify whether we have everything we’d expect to see, for example, can we see groceries, mortgage, utilities, at least 500 transactions a year. Neither of these solutions would identify someone with a current account without an overdraft that they use, for example, solely for gambling!

The consumer view

Awareness and customer adoption of Open Banking is still quite low but has continued to grow, with 10-11% of digitally-enabled consumers now estimated to be active users of at least one Open Banking service, up from 6-7% in March 2021^[1]. Six million plus customers (businesses and consumers) have used Open Banking.

The use case and user journey can make quite a difference to adoption rates.

• • Reauthentication

Prior to October 2022 the 90-day reauthentication requirement meant that consumers needed to log into their bank account to reauthorise their permission to share the data with a lender. This created frustration amongst lenders with many consumers simply dropping out of the Open Banking experience.  The latest changes mean that consumers will no longer be required to log onto their bank account and reauthorise their bank to share data with a lender. This can be done by a simple text or email reconsent that the lender captures.

• • Granularity of data

Returning too much data during the Open Banking process has also caused issues for both consumers and lenders.  Consumers are often worried about the depth of data revealed and what lenders need to review to make their decision and often don’t want others or themselves to know what they spend in certain categories. Proportionality is the key. For example, for higher value credit decisions such as mortgages or asset finance, understanding the pattern of a consumer or businesses behaviour revealed by months of transactional behaviour could be essential for qualifying risk. For lower value, unsecured loans that depth of granularity is perhaps not as essential.

From a lender perspective returning too much information can cause delays to processing and underwriter review. For example, an underwriter may only be required to validate income but as more information is displayed, they examine the case further to make a manual decision which can have an adverse impact on the journey and potentially the decision. As lenders use and experience of Open Banking grows, automation and targeted manual review have become more the norm.

Suppliers are also adapting their solutions to be more targeted and considering what summary data and insights to show to advisors.  This could include identified incomes and disposable incomes (split by compulsory and discretionary spend), pay dates, details of benefits payments, gambling insight etc.  The objective being to return a valuable summary of key factors and insights without returning too much information to cause too much disruption to the journey.

Making Open Banking easier to consume

Experian provides the ability for a consumer to boost their credit score for free by sharing bank account data.  Launched in November 2020, Boost has proved to be one of the UK’s most popular Open Banking services, and Experian’s Open Banking platform which supports this service now accounts for 20% of the Account Information Services API calls in the UK ecosystem.  Whilst open to everyone, Boost is targeted predominantly at younger and thin file demographics who may ordinarily struggle to get credit due to a limited footprint on the bureau.

The customer can sign up to Boost through the Experian website and app or through affiliate links, outside of lending application processes; the data is then extracted through Open Banking and used to assess if an uplift can be applied to the consumers credit score. When an uplift is applied the data will be shared with lenders. Lenders can receive this data without any changes to lender journeys. Scores and data fields are returned to the lender for use in credit worthiness assessments. We have observed Boost customers having a 4 times lower bad rate compared to other applicants, with the bad rate correlating negatively to the size of the Boost adjustment.

Some consumer credit lenders have partnered with Experian Boost to enable users to access more competitive rates by launching boosted offers. Including Boost data in lenders credit decisioning processes provides consumers with more favourable credit options, allowing Boost users to improve their credit worthiness and access the right financial products for them.

Let’s consider consumers wanting to get on the housing ladder and buy their own home. Experian’s vision is to help consumers get “mortgage ready” and find them the best rates.  Just under a quarter of to Experian’s website are wanting to prepare themselves for home buying. We want to help customers understand the journey they need to go on. Homebuying and savings propositions can help customers save for a deposit and improve their credit score. Once a customer is “mortgage ready” Experian will educate and support them to obtain the most favourable rates in the market.

The Boost ecosystem vision allows consumers to sign-up to Boost through multiple channels and for lenders to use the data through a selection of integrations.

Moving on from Open Banking into Open Finance

The roadmap for extending the sharing of personal financial information beyond Open Banking is now already in place. The government’s Pensions Dashboard which relies on sourcing and consolidating a customer’s pension policy data looks set to follow. This may be the precursor to the sharing of savings and investment data to improve the comparison of and access to services that can help consumers manage their financial lives.

Offerings now exist for income and employment verification – or Open Payroll.   Some providers use screen scraping techniques to facilitate this, but Experian has created an ecosystem of payroll software providers and employers that enables a consumer consented journey to access payroll information directly from their employer. The big difference to Open Banking is that the customer is only being asked to share payroll information to verify their income and employment which may be preferable to sharing their Open Banking data.  If the objective is purely income or employment verification, Open Payroll is a simpler, lower-friction, and less intrusive way to access straight through processing, quicker time to decision and enhanced customer experience. Experian’s analysis has shown that verified income and employment data can be an important discriminator of risk and a facilitator for greater financial inclusion. Lenders benefit from more automation, lighter manual review, improved risk differentiation and reduced regulatory risk.

Where’s the future heading?

Open Banking adoption, whilst slower than anticipated, is starting to play a role in many lender decisioning processes, with lenders automating processes following initial manual adoption. Automation provides a slicker journey with less drop out. Whilst many lenders using Open Banking are reviewing a consumer’s current position, the future will include an understanding of a future view.

Across Banking and Financial Service providers, Open Banking is mostly used at origination, with more using than not. As expected, there is less use in customer management, but it is starting to be used for the management of revolving products. There is less use in collections / pre collections, but lenders are starting to explore further in this area.

Whilst Open Banking adoption grows, Open Finance including Open Payroll is being mentioned more. The next phase is to have fuller data sources including savings, pensions and other accounts, for example, credit cards. The use of savings data requires some consideration given the range of different types of account and complexity of products particularly regarding access to deposited amounts.

The roll-out of Open Finance is dependent on the government’s appetite to legislate data to share information and on the governance and commercial frameworks put in place to bring this data to market securely. Progress has already been made through initiatives such as The Investment and Savings Association’s (TISA) Open Investment, Savings and Pensions initiative (OISP).

The provision of Open Payroll is already underway with APIs and the commercial framework for the sharing of data with an employee’s consent in place. The Pension Dashboard programme once live will enable individuals to access their pensions information online, securely, and all in one place.

Moving beyond just credit

Consumer consented data can also help potentially vulnerable consumers share their support needs with multiple organisations in minutes. There are over 27 million potentially vulnerable consumers in the UK but disclosure to firms is low. Despite regulatory and commercial pressures, until consumer disclosure at scale is solved, firms will struggle to avoid foreseeable harms.

Experian has collaborated with consumers, lenders and charities to design and test Support Hub to help consumers get the support they need, developing a multi sector “tell me once” vulnerability support solution. Support Hub is a market-leading service that allows consumers to share their support needs across multiple organisations in a transparent, standardised, and consented way.  It’s under-pinned by an industry standard data taxonomy of support needs.

There are three easy steps for consumers to share their support needs with multiple organisations:

1. Set up support needs
2. Set up an account
3. Select and consent the organisations they want to share with

Support Hub is currently offering support for sight, hearing, communication, mental health and dementia needs. This will quickly role out to the full taxonomy. This solution is consumer led and relevant to consumer needs and avoids cumulative harm. It’s a good example where consumer consented data is used outside of the direct access to and management of credit.