5 Incredible AI Innovations Transforming The FinTech Industry
Always an industry known for welcoming innovation, FinTech has been among the earliest and most enthusiastic adopters of Artificial Intelligence (AI). Over the past few years, AI has been steadily transforming how clients and financial institutions interact with one another. More significantly, traditional banks and financial services have been forced to adapt or risk facing obsoletion.
The core system behind AI in FinTech is deep learning. Deep learning is a complex computer function that emulates the human brain’s capacity for ingesting and processing data, recognising patterns, and using this analysis to make well-informed decisions. In FinTech, this is being used to build a deeper understanding of customer needs and find ways for financial institutions to better service their clients.
Here we explore five incredible ways that AI and Deep Learning are transforming the FinTech sector.
AI and deep learning machines are becoming increasingly adept at identifying human faces to an accurate degree. Visual AI is much more powerful than an average human’s ability to recognise faces, to such an extent that AI is now able to recognise faces even when significant changes are made in their appearance. Such alterations could range from growing a beard to a change in hair style. The benefits of such precise face identification processes are two-fold. On the one hand it ensures that data, money, and bank accounts can only be accessed by their owners, minimising fraudulent behaviour. It also means that individuals will face less problems accessing their accounts should they change their appearance.
AI Fraud Detection
Over and above visual recognition, AI and deep learning are also capable of detecting and mapping out an individual’s online/platform behaviour patterns. Through a range of analytical tools, AI collects and analyses data by learning and monitoring a user’s behavioural patterns. This data is subsequently used to implement predictive analytics into fraud detection, which can automatically flag suspicious activities and further safeguard client accounts and money. This trend is already taking hold to great effect among credit card companies. For example, Japanese AI and Fintech company MILIZE Co began offering financial institutions advanced fraud detection and anti-money laundering solutions built using automated machine learning. It is believed that this AI platform has a 90% accuracy rate, which has led to a significant improvement in security and profitability for Japanese credit card companies.
Another major benefit of AI solutions in FinTech is that deep learning machines can streamline customer segmentation and predict customer trends based on many different demographics and variables. AI improves targeting, personalisation, and engagement, giving banks and service providers the data to better interact with consumers based on their specific needs and requirements. This will allow companies to pitch pinpoint accurate messages to audiences who fall under various non-tradition micro-segments, ultimately resulting in higher conversion rates.
Chatbots and similar AI-powered customer service solutions are becoming more ubiquitous across the FinTech industry. The main benefit of a chatbot is its facility to resolve simple questions quickly and efficiently. Consequently, these are able to help businesses save on operational costs while enhancing the customer service experience. AI-driven email assistant platforms can also suggest automatic replies to speed up customer query response times. Through Machine Learning, AI systems first monitor how human agents respond to emails and learn how to better formulate email responses that accurately answer queries. At a later stage, FinTech companies may also look to develop AI telephone voice assistant systems capable of directing people to the information they are requesting through speech analysis.
Arguably the biggest game-changer in the AI and FinTech scene is predictive analysis. Through cutting-edge algorithms, machine learning platforms are beginning to analyse customer patterns and offer predictions on where the market is heading. This invaluable data is designed to boost how accurately financial institutions can predict tomorrow’s business trends and customer wants, helping them make more informed business decisions and optimise their strategies. Furthermore, predictive analysis works on an individual level too, meaning companies can create customer journeys tailored to each client, ensuring enhanced personalisation in their products and services.