The marriage of embedded finance and AI

The hype around artificial intelligence (AI) isn’t going to die down any time soon, and coupled with the widespread adoption of embedded finance, looks set to revolutionise the way we approach financial services.

Whilst Bloomberg is looking to create its own version of ChatGPT, this is not about the type of generative AI that produces images, or other media in response to prompts. Instead, the revolution is coming from the power of machine learning in the way that it allows financial services to learn from customer information, and make rapid decisions. By analysing vast amounts of data, AI can support financial services to better understand the needs of their customers and enable them to offer unique solutions - all in one streamlined journey.

Introducing embedded finance

You’re probably pretty familiar with embedded finance and aware that you’re using it regularly.

To confirm, embedded finance refers to the integration of financial services into non-financial applications, such as Uber, Deliveroo, or when shopping. The premise is simple, and more of us are making use of it every day. By embedding the financial service we need into an application or website, customers can have a seamless experience in which all of their activity (from ordering to making payment) takes place in one journey, thereby increasing revenue for companies. 

Now AI is increasingly playing a pivotal role in embedded finance as it enables and speeds up the real-time processing of payments and transactions. AI-powered payment processing systems can efficiently and securely process payments, reduce the risk of fraud and ensure that transactions are completed at a much faster rate - much to the celebration of business owners.

The innovative partnership of AI and embedded finance means that these technologies are having a significant impact on financial services, and making processes more effective. But how else is it making waves?

Letting AI take on the risk

Risk is a huge element of financial services, and when not carried out properly, can have dire consequences. It’s estimated that the cost of cybercrime will reach $10.5trn annually by 2025, and combating this will take an intelligent and machine-powered solution. 

The power of AI can quickly produce more accurate risk assessments, analyse vast amounts of data, and identify patterns and trends that human error might miss. AI’s analysis of this data allows them to make more accurate predictions about credit risk and fraud, saving both financial institutions and customers from losing money. Furthermore, AI’s role in risk assessments removes layers of complexity, and is a powerful resource for Fintechs, given that there’s over 185 banking regulatory changes every day that could affect them.

Better serving the customer

AI-powered chatbots and virtual assistants can support companies by providing instant solutions to customers and reducing the workload for customer-service representatives. Whilst AI can’t do it all, it can solve lower-level enquiries, direct customers to where they need to be, or escalate issues where needed to a real person. Time-crunched employees will appreciate its integration into the workforce in addressing customer queries quickly. This synergy between real life workers and AI will assist in boosting productivity, as long as it’s focused on support over replacement. Between 2019-2023, there was a 3,150% growth rate in terms of successful chatbot interactions, making this a transformational offering for Fintechs to adopt.

How AI is getting personal

Personalised experiences matter, and we’re more likely to buy from a business or brand when their recommendations to us feel relevant. AI has an essential role in delivering personalised experiences in embedded finance, by aggregating and analysing data successfully, and making it easier to deliver personalised services to a customer’s needs and preferences.

These insights enhance customer journeys, with AI anticipating their expectations and giving them what they need at the right point in time - driving growth and boosting customer loyalty. This appetite for AI innovation is only increasing, with the personalisation software market expected to reach $2.2bn by the end of 2026. 

It’s as simple as 4-clicks

AI improves personal customer experiences by making them faster. For example, the embedded lending process can be accelerated by enabling a 4-click journey, allowing partners in the financial services ecosystem to offer personalised funding solutions to potential customers. Through the power of AI and machine learning, this simple journey is both convenient and transparent, and fundamentally has the experience of the customer in mind. 

The future for AI and embedded finance

AI is proving itself to be a driving force in the expansion of embedded finance. With the sector forecasted to reach $248.4 billion by 2032, AI is meeting the demand from organisations to enhance embedded finance capabilities to improve the engagement and satisfaction of their customers. 

By augmenting embedded finance with AI, the result is a customer-centric and frictionless financial service. As financial institutions continue to adopt the innovative powers of AI-powered technologies, we can expect to see a positive  transformation in the embedded finance space.

About the author

Nima Montazeri, the Chief Product Officer for embedded finance solutions at Liberis, has developed impactful products that facilitated affordable healthcare access for millions worldwide. Formerly the Head of Product at BabylonHealth, Nima played a vital role in launching Babylon's products in the US, Canada, and South East Asia. With prior experience as the Head of Technology at ThoughtWorks Ventures, Nima assisted scale-ups and startups with their product and technology strategies. Presently, Nima acts as an advisor to early-stage tech startups in the UK.