Navigating the evolving fintech landscape: embracing AI, ML and cloud migration to gain competitive edge
By Elena Davydova, Senior Director Product Management at Mambu
Artificial Intelligence (AI) has been around for a while. However, its recent development into tools such as ChatGPT has brought the capabilities of generative AI to the forefront. Excitement around the usage and applications of AI appears in the media very often. Financial services will not be an exception from this trend, although there is a lot of scepticism whether we want to trust AI in dealing with such a sensitive topic as an individual’s finances, be it their lifetime savings or mortgage loan. On the other hand, by using AI, banks will be able to offer a whole new scope of products and services for their customers.
The fintech landscape is always changing and with the path to innovation paved by embracing AI, Machine Learning (ML) and cloud adoption – the opportunities are endless. A recent report from Mambu highlights how AI technologies could deliver up to $1 trillion of additional value each year for the global banking industry. These technologies enable personalised services, automation, and data-driven decision-making, empowering fintech companies to stay ahead of the curve.
Fintechs can utilise AI, ML and the cloud to drive innovation, but in what way?
Broad applications of AI and ML in fintech
AI and ML have revolutionised processes for many financial institutions, and fintechs are already discovering its diverse applications. These include everything from personalised financial recommendations to fraud detection and risk assessments, and streamlined workflows and process efficiency.
We’re already seeing financial services institutions guide customers to products rather than leaving them to decide where to get the most competitive rates on a savings account or where to take out a loan. Embracing this hyper personalisation, banks are in a unique position to synthesise all the data they have on product usage and customer segments to better serve end customers.
And the capabilities of AI in fintech aren’t limited to recommending products. Mastercard has started using AI to help banks combat real-time payment scams. In this case, the consumer fraud risk technology uses large scale payment data to help identify scams before the funds leave the victim’s account. We’re already seeing the likes of Lloyds, Halifax, Bank of Scotland, Monzo and TSB tap into this technology for their customers.
The benefits of the above are both for banks and consumers. For banks, it means improved efficiencies and with this, better product offerings and services for their customers. As well as benefiting from the improved services they receive, customers have the peace of mind of knowing that, with AI, their spending insights are more accurate, allowing for improved fraud detection and safeguarding of their funds.
Harnessing cloud migration to gain a competitive advantage
To keep pace with innovations and applications in AI, a modern tech stack becomes all the more important. Our research found that financial institutions that run on a true software-as-a-Service (SaaS) platform recover 2.5x faster than their industry peers.
Increasingly, banks and financial institutions are turning to cloud technology to underpin their services, and with good reason. On cloud-native SaaS platforms, financial institutions can adapt to changing market forces and deliver a better customer experience significantly faster. Cloud technology provides access to complex financial computations that weren’t affordable before. New technologies allow financial institutions to keep a good balance between complexity of financial algorithms and ease of their configuration, crucial to rapidly launch innovative financial products.
The competition in the financial services domain is fully powered by technology, therefore banks and financial institutions that are able to offer new products faster have the competitive advantage. Paired with scenarios where Mastercard is embracing AI to aid banks against well-known payment scams, it goes to show how important it is to utilise both AI and cloud-based infrastructure to improve agility and value to end customers. The faster you launch end services, the faster you can grab market share.
The future of AI and the cloud
So, what does the future hold for AI and the cloud? Although some may have been sceptical of AI’s place in banking, by its nature, the fintech landscape thrives on innovation. It’s obvious that AI and ML need data to make the best use of it. When it comes to banking, the quality of data is crucial. The more complete and correct it is, the better decisions can be made using AI. Cloud solutions and open banking combined with AI will make a significant difference in the industry once regulatory and privacy concerns are addressed.
Utilising AI to anticipate and predict demand for lending products from specific customer profiles, and quickly offer those is invaluable for the end user and provider alike. As we’ve already seen demonstrated by Natwest and others, AI can be used to improve the security of consumer funds. With fraud cases skyrocketing, particularly in times of economic uncertainty, consumers want to know that their funds are safe from the latest scams.
Machine learning and AI are here for financial services and here to stay. Leaders are asking their teams: how can we offer the best products and predictions for customers using the data that we have? The highly regulated nature of the industry risks making this a game of two steps forward, one step back, but the point is that there is a lot of data that can and should be used, within regulatory frameworks, in order to better serve customers. For Mambu, listening to customers will determine what we do instead of what we see others doing to ‘win the race’.
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