In our last article we mentioned the famous 1980s movie The Terminator which created a world where machines had taken over, threatening to cause the extinction of humankind. As you likely know, The Terminator is just one of many movies that have been produced about machines fighting to take over the world. For decades, Hollywood has been fascinated with the implications of artificial intelligence. Imaginations have run wild considering the question, what would the world look like if AI became the norm?
In the realm of entertainment, AI generally moves toward negative results. It becomes the controversial and shocking source for destroying humanity as we know it to be: robots take the place of human relationships and machines seek to take over the world. Yet the actual use cases for AI we see most prevalent today are very far from the AI-dominated worlds dreamed up in movies. In this article we’ll look at how AI is actually being used right now, particularly in the fintech sector, and consider how fintech is better as a result.
In the previous article, we defined artificial intelligence as “a machine’s ability to perform the cognitive functions we usually associate with human minds.” How does a machine do that? Let’s look at a few sub-terms to explain.
First, big data. According to Oracle, big data refers to large, complex data sets, especially from new data sources. Data has always been around, but technological advances in the past few decades have produced more of it, from more diverse sources, and with greater access to it (you can read more about the three Vs of big data – variety, volume, and velocity – here).
With access to so much more data today, we have a need to be able to manage, understand, and utilize it, thus our second term, machine learning. Machine learning is when computers learn how to do things without needing to be explicitly programmed for them. This learning requires large sets of data to be run through them. Following a specific model or set of directions, programmers can run specific data sets through a computer and ask it to identify patterns or make predictions. The more data there is, the more the computer can “learn” over time in order to make conclusions about current realities and projections about future data (you can read more about machine learning from IBM here).
Lastly, a quick review on the term fintech. We know that fintech stands for “finance technology,” but what do those two words actually mean? Oxford defines finance as “the management of large sums of money, especially by governments or large companies,” and technology refers to tools that make our lives easier, or as Oxford defines it, “the application of scientific knowledge for practical purposes, especially in industry.” So fintech essentially is, tools that help people or companies to practically manage money. It revolves around the goal of creating or building resources that assist consumers (B2C) and businesses (B2B) in accumulating and managing wealth. Let’s look at how AI is currently helping to make those things happen.
We would argue that basically every fintech company that currently exists has incorporated AI into their business models, to at least some degree. In the rest of the article, we’re going to discuss three main ways we see fintech companies using AI right now.
In many ways, AI is powering the improvement of customer experience and customer service across many fintech platforms. AI software programs collect and analyze customer data (things like a person’s browsing history, purchases made, demographics, etc.) in order to customize content to fit the customer’s profile. These programs are constantly working to gain real-time customer data that can be instantly applied to make their experience with a fintech company more relevant and personalized.
Many fintech companies are also utilizing AI-powered chatbots to provide 24-7 customer service to their customers. These chatbots can answer questions, provide recommendations, and help complete transactions customers may need help with. Similarly, many companies also are utilizing voice-activated AI assistants to provide additional support to customers (think Siri or Alexa).
Another major way fintech companies are utilizing AI right now is with financial advising. Instead of financial advisors being human experts in the field, financial advising has largely moved to become an automated service. Today when a customer fills out a financial profile in terms of their assets, debts, investments, goals, etc. it will most likely be run through a series of AI-powered algorithms that can instantaneously analyze and predict the customer’s future. These algorithms, built through machine learning, can provide personalized advice for how a customer should manage and build their financial portfolios. They have access to more real-time market information that will help not only customers but also companies assess risks, make predictions, and constantly monitor what’s going on. AI has not only made financial advising more readily available to all sorts of customers but has also made it more reliable and applicable to a diverse range of consumers.
Additionally, we see fintech utilizing AI in fraud detection and prevention, topics which are extremely important in fintech to protect both companies and customers’ financial assets, protect customer identities, to ensure compliance standards are met, and build customer trust and loyalty.
Back to the idea of machine learning, fraud detection programs powered by AI use advanced algorithms to identify anomalies or abnormalities in data sets that would indicate something isn’t right. These algorithms are running all the time as data is continually accumulated so that if a data point deviates from the usual patterns, it can be immediately identified and dealt with in order to protect customers and the companies they’re interacting with.
Without a doubt, artificial intelligence is helping fintech expand and become more meaningful for customers. In this article we briefly explained three areas of fintech that are improving because of AI: customer experience, financial advising, and fraud detection. Of course there are many other ways fintech is currently using AI besides these things (including APIs), and you can read more about them here or here. In the next article we’ll consider the future and how we might continue to see AI develop in the fintech sector and beyond. Stay tuned.