How AI and Machine Learning Are Shaping Fintech

Fintech has evolved radically in the last few years, thanks in no small part to artificial intelligence (AI) and machine learning (ML). Influencing everything from core operations to how we make critical decisions, AI and ML have found their way into practically every crevice of the financial sector. Which is why AI spending within fintech is predicted to have more than trebled between 2019 and the end of this year. But where is this AI investment going? And how are AI and ML shaping the future of fintech?  

Seven ways AI and ML Are Changing Fintech 

Robo-advisors  

The idea of robo-advisors is nothing particularly new. They’ve been knocking around since Wealthfront (formerly known as KaChing) was launched back in 2008. But their capabilities and the way they operate are entirely different to their original incarnation, thanks to AI and ML. Algorithm-driven, robo-advisors have moved from checkbox questionnaires to bona fide digital investment portfolio managers, capable of providing tailored investment advice relating to the unique financial goals and situations of each user. And they can only do this through AI and ML.   

Process optimisation  

Process optimisation is probably what most people think of when it comes to applying both AI and ML. And in fintech, they’ve fast-tracked everything, from report creation to customer service. By automating those repetitive, time-consuming tasks, AI and ML have streamlined processes, resulting in significant time and cost savings while boosting productivity. Rather than replacing staff – as has always been the inherent fear with AI and ML – they free them up to focus on the issues where technology may not be so useful.  

As we move forward, AI and ML are going to continue to increase their value in this arena through deployment in Big Data analytics. Enabling fintech firms to finally maximise the value of the data that they have been able to access but not easily analyse for years. Adding increased intelligence to the speed that AI and ML already bring to fintech.  

Credit scoring  

AI and ML have already made a significant impact on credit scoring. Enabling brands to eschew the traditional – some might say, antiquated – methods used by established credit scoring agencies, AI and ML allow for the analysis of many personal data points, providing a far more accurate and personalised assessment of creditworthiness. And opening financial doors to people and businesses who may previously have found all credit avenues to be closed and bringing new, lower-risk customers to financial institutions. Which has, of course, meant faster, more efficient loan approvals.  

Security  

Security has been the paramount consideration for all fintechs for decades, and with the battle against fraud intensifying, AI and ML are providing some of the most innovative solutions. From document analysis to monitoring transaction patterns, AI and ML empower fintechs to rapidly identify and respond to fraudulent activity, creating a safer financial environment for everyone.  

Customer service  

Customer service is an ongoing focus for most businesses, and AI and ML are working to transform how it is delivered within the financial services sector. Advanced chatbots offer personalised and immediate replies to customer queries. The rapid processing of data enables chatbots and customer service operatives to offer tailored services and advice on products suited to each customer’s needs, and solutions that could answer individual problems. Allowing fintechs to take a proactive approach to customer service removes the need for firefighting and replaces it with a dynamic, personalised, satisfying customer experience.  

Personalised marketing  

GDPR changed the way that most businesses approach digital marketing. Gone are the days of blanket emailing, instead we are seeing a more nuanced approach, and AI and ML are expediting and enhancing this with a degree of personalisation previously unattainable. We’ve discussed the roles of chatbots and virtual assistants, but with AI able to utilise customer data, such as past transactions, search histories, and social media activities, to craft personalised marketing strategies and recommendations, marketing instantly becomes more interesting and effective.  

Predictive analytics  

With AI and ML, analytics has become so much faster, easier, and precise, which has meant several things for fintechs. As mentioned above, it brings the ability to accurately segment customers for marketing. It enables fintech firms to analyse vast customer data, making predictions of future behaviours and preferences more accurate. And it allows the tailoring of services and products to meet customer needs on an individual and group level, enabling the anticipation of market demands and allowing businesses to stay at the forefront of their industry.  

Integrating AI and ML into fintech has resulted in an almost complete paradigm shift for the industry across all levels. From customer service to product planning and core administration, the fintech landscape is being fundamentally reshaped, with improved efficiency, experiences, services, and personalisation, bringing benefits to customers and businesses in equal measure. And the journey is far from over. Both AI and ML are still in their early years, and the surface of the potential they can bring to fintech has barely been scratched.