FinanceTech

The union of AI and embedded finance

Nima Montazeri, CPO of the embedded finance solutions provider Liberis, talks about how AI and embedded finance will transform the financial services industry.

The rapid use of embedded banking and the ongoing buzz surrounding artificial intelligence (AI) appear to be revolutionising the way we approach financial services.

Bloomberg is attempting to replicate ChatGPT, but this is not the kind of generative AI that responds to commands by producing graphics or other types of media. Instead, the power of machine learning is driving the shift by enabling financial services to quickly learn from client data and take action. AI can assist financial services in better understanding the demands of their clients and enabling them to offer distinctive solutions – all in one streamlined experience – by studying enormous volumes of data.

Presenting embedded finance

You probably have a good understanding of embedded finance and are aware that you use it frequently.

To be clear, embedded finance is the incorporation of financial services into non-financial apps like Uber, Deliveroo, or retail. The idea is straightforward, and more people utilise it every day. Customers can have a seamless experience in which all of their activity (from ordering to making payment) takes place in one journey by embedding the financial service we require within an application or website, which will increase revenue for businesses.

Due to its ability to enable and speed up real-time processing of payments and transactions, AI is currently playing an increasingly important role in embedded finance.

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To the delight of business owners, AI-powered payment processing solutions are able to process payments effectively and securely, lower the risk of fraud, and ensure that transactions are completed considerably more quickly.

As a result of their creative collaboration, AI and embedded finance are revolutionising the financial services industry and streamlining business operations. How else, though, is it causing a stir?

Allowing AI to assume the risk

Financial services contain a significant amount of risk, which can have serious repercussions if not handled correctly. By 2025, it is predicted that the yearly cost of cybercrime will be $10.5 trillion, necessitating the development of an intelligent and machine-powered solution.

The ability of AI to examine massive volumes of data, quickly create risk assessments that are more accurate, and spot patterns and trends that human error could miss. By using AI to analyse this data, they can predict credit risk and fraud with greater accuracy, protecting both clients and financial institutions from losses. In addition, AI’s participation in risk assessments reduces layers of complexity and is a valuable tool for Fintechs because there are over 185 banking regulatory changes that could have an impact on them every day.

Better client service

Chatbots and virtual assistants powered by AI can help businesses by giving clients quick answers and lightening the strain on customer service agents. While AI can’t do everything, it can handle lower-level problems and guide clients to their destinations or escalate problems when necessary to a human person. Employees who are pressed for time will value its integration into the workforce for promptly resolving consumer inquiries. As long as it’s focused on support rather than replacement, this collaboration between real-world people and AI will help to increase productivity. A 3,150% increase in successful chatbot engagements between 2019 and 2023 makes this a game-changing service that Fintechs should employ.

Why AI is becoming more personal?

When a company or brand makes recommendations to us that feel pertinent to us, we are more inclined to make a purchase from them. Personalised experiences are important. By successfully aggregating and analysing data and making it simpler to provide customised services to a customer’s wants and preferences, AI plays a crucial role in offering personalised experiences in embedded finance.

These insights improve customer journeys by predicting their needs and supplying them at the appropriate time with AI, which promotes growth and increases client loyalty. The market for personalization software is anticipated to reach $2.2 billion by the end of 2026, demonstrating the growing demand for AI innovation.

It only requires four clicks.

AI makes personal customer experiences faster, which enhances them. By providing a 4-click journey, for instance, participants in the financial services ecosystem can provide tailored funding solutions to potential consumers, speeding up the embedded lending process. This straightforward journey is convenient and transparent thanks to AI and machine learning, and it is designed primarily with the customer’s experience in mind.

The future of embedded finance and AI

AI is demonstrating its ability to propel the growth of embedded finance. AI is addressing the demand from enterprises to develop embedded financial capabilities to promote consumer engagement and happiness, with the market expected to reach $248.4 billion by 2032.

AI is added to embedded finance to enhance it, creating a customer-focused, frictionless financial solution. We may anticipate seeing a beneficial change in the embedded finance industry as financial institutions continue to incorporate the cutting-edge capabilities of AI-powered technologies.

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