AI and open banking: what does the future look like?
The 13 January 2018 might seem like a fairly innocuous date, but for those in the know, it’s the day that made open banking possible in the UK. That was the day the EU’s PSD2 (Second Payment Services Directive) came into effect, making it possible for swathes of customer data to be shared (with a customer’s permission) between large banks and authorised third parties in a secure, standardised form via an ‘open banking’ API.
Since its launch, open banking in the UK has grown exponentially. From personal money management apps and price comparisons to cardless payments and business accounting apps, the uses for open banking have proliferated. Over 6 million active users in the UK alone are using it, and that number will continue to grow as use cases extend beyond payments to include sharing financial data for services like mortgages and loans - and open banking extends more broadly into the realm of ‘open finance’.
With this user milestone reached, many are looking to the future of open banking. In this article, we’ll discuss how another nascent technology, Artificial Intelligence (AI), may interact with open banking.
Bringing AI to open banking and open finance
Thanks to the meteoric rise of ChatGPT and other generative AI models, the world’s imagination has been captured by the promises of AI. Sometimes the applications of AI are clearly beneficial; sometimes they’re dangerous; and in many areas we simply don’t yet know. However, in banking and finance, an industry based on the processing and analysis of vast quantities of data, it’s clear that AI will have something to bring.
How is AI impacting open banking and open finance now?
Some finance companies have already started experimenting with the current generation of AI tools. Across many industries, AI is being used to create leaner and faster operations, taking on a lot of the time-consuming, manual work so human teams can focus on more value-added tasks. AI is also able to create more tailored products and services.
It is an invaluable tool in the credit sector, enabling lenders to more accurately assess an individual’s risks and make more informed, faster decisions. AI is additionally helping with portfolio management, and can even provide a real-time analysis of verbal customer content (via speech recognition) for compliance purposes.
In open banking, AI is being used to boost the customer experience, security, and reduce fraud. Personal banking app Cleo, for example, is a money management app that uses an AI chatbot to deliver financial advice and information in a conversational and friendly tone. Depending on a customer’s preference, it can even ‘roast’ its user, providing witty observations about their spending habits.
Morgan Stanley, meanwhile, is using ChatGPT-4 internally to help its staff find and consume information quickly instead of scouring internal repositories for the latest analyst insights.
Looking to the future of AI and open finance
Yet, this is only the tip of the iceberg when it comes to AI in open banking and open finance. The opportunities for improving the customer experience, fraud and security, and adhering to regulations are truly exciting.
Enhancing the customer experience
Open banking has been able to transform the digital experience for banks' customers, making their payments, apps and interactions much more personal and customer-centric. AI will take this a step further by creating hyper-personal experiences that adapt and learn throughout a customer’s lifetime. Take, for example, the ability of open banking to categorise transactions into ‘groceries’, ‘health and wellbeing’, ‘entertainment’ and more. Right now, customers can use this to understand their daily and monthly spending. In the future, AI can offer personalised saving goals recommendations based on this information — for instance, cutting down on clothes shopping to save for a holiday.
AI can identify patterns and relationships in customer data to tailor services to customers. It can predict what a customer may need in the immediate future based on their current spending and financial goals. Mortgages, loans, and credit cards can all be recommended to someone, right when they are most likely to want them.
Facial recognition and ID document verification have made onboarding seamless for many banking customers. In the future, this will also go a step further, with an expansion of live video biometrics and document verification making eCommerce payments and online transactions a lot more secure and easy to complete. False declines can also be reduced as AI compares large swathes of transactional and financial data to establish a risk level for the consumer.
Ultimately, this saves time and hassle for customers, making them more likely to complete transactions and repeatedly return to an online store. With half of financial services customers stating that they walk away from a company after a single bad experience, using open banking and AI in this way can make all the difference to your revenue growth and retention.
Boosting security and fraud detection
Intelligent identity verification is making open banking safer, and advances in AI are making it possible to spot potential fraud in real-time using pattern analysis. AI can recognise patterns in transactions, flagging anything suspicious to human analysts to investigate further. Using AI to reduce fraud and money laundering has been encouraged by regulators in the Netherlands, Germany, France, the U.S and Singapore.
Open banking enables anyone with a bank account to initiate fast and secure payments. With AI, this security gets a boost by understanding how someone historically has spent money in certain seasons and how they are likely to purchase in the future. Anything outside of this pattern can be flagged for review. Information on fraudsters can be shared widely with other banks to prevent widespread fraud. Experian recently launched Aidrian, a fraud detection tool that can classify transactions with 99.9% accuracy.
Supporting regulatory compliance
There are a number of regulations companies need to meet, from EU anti-money laundering (AML) and Combating the Financing of Terrorism (CFT) policies and the UK’s Payment Services Regulations, to industry-specific regulations in iGaming and the Payments Regulations for Money Transmitters. AI can make it easier to meet these regulations by analysing more data, in greater detail, to improve due diligence, understand risk profiles, and identify any fraud and money laundering. It can also improve Strong Customer Authentication (SCA) techniques before a customer makes a payment. Detailed checks on credit history and financial circumstances can improve verification and decision-making around deposits, credit, and withdrawals.
Addressing potential challenges in using AI
AI in open banking cannot advance if we are blind to the challenges of using it. Adoption of AI relies on collaboration between organisations, industries, and eventually, across countries. This in itself creates challenges in standardising the APIs being used and managing the data quality of what’s being shared.
The availability and accessibility of data, the security of data, and addressing potential bias have been identified as challenges by the Euro Banking Association’s (EBA) Open Banking Working Group (OBWG).
Data quality
With more collaboration between organisations and different countries, coming to a common framework for standardising data becomes vital. Consistent standards are needed to ensure data is of good quality and usable by an AI model. Data collected needs to be cleaned and consolidated before it is analysed, and it needs to have the right metadata around it, like the times collected and consent information, to ensure it is timely, relevant, and meets regulations such as GDPR.
Data privacy
Data privacy is a huge concern for customers and organisations. Educating customers on how their data is used and shared with third parties via open banking will help the industry grow and address any concerns they may have. Since they have to provide informed consent for the collection and use of their data, helping customers understand the strong protection and regulation of their data is a critical step for any business using open banking data. It also - and very critically - maintains customer trust.
Regulating AI
Regulation of AI models is on the horizon, but nobody knows what form it’ll take yet. One suggestion is to limit some powerful forms of AI to restricted uses; others recommend licensing, and increasing the transparency around an AI model’s workings.
For now, adhering to best practices and regulations on data privacy and the use of personal data will help organisations stay on regulators’ good sides. Looking at incoming legislation, like the EU’s AI Act, will also give insights into where Governments are likely headed in terms of regulation.
Data and AI bias
There have been many high-profile examples of AI showing biases, including Amazon’s hiring algorithm showing bias against female candidates and Google Photos showing discrimination against people of colour. For open banking to benefit everyone, AI models cannot spread biases across the financial system.
One way to tackle this is to make every AI’s decision as explainable as possible, with clear human oversight. An AI shouldn’t be the final say on a mortgage application, for instance. Training an AI on a broad, large data set can also help to reduce potential bias — and this is where open banking can support, with its huge customer data sets.
How Yaspa is embracing the future of consumer payments
We cannot predict exactly what the future will look like, but looking at today’s open banking, open finance, and AI advances, you can predict that customers will increasingly look for seamless, easy payment experiences. Cardless account-to-account payments may very well become the de facto way of shopping and paying for goods and services online. Coupled with AI, this offers a more secure and better way for consumers and businesses to enjoy eCommerce, iGaming, and more.
Yaspa’s open banking platform streamlines every aspect of an organisation’s payment operations. But our account-to-account payments are just the start. As AI models continue to develop there’s no doubt we will see new features and applications that will transform our business and our customers’ businesses and the way we all interact, as consumers, with our financial services providers. It’s an exciting time, and we’re just at the beginning… .
To start upgrading your payments processes, contact Yaspa today.
