The Fintech industry, with its focus on efficiency and consumer-centricity, is a disruptive force in the traditionally staid and frequently complacent financial services market. In certain areas, the pace of Fintech disruption has been so dramatic it has forced incumbent institutions to scramble to adapt their offerings to meet changing consumer demands.
Increasingly, artificial intelligence and machine learning are the key technologies that enable Fintechs to compete aggressively with legacy players. Below are some of the key ways AI and machine learning are powering continued innovation in the Fintech sphere.
One issue with many financial products and services is the fact that they are often designed to meet the needs of large population groups but fail to address more individualized needs and desires. We’re living in an increasingly personalized world and consumers are coming to expect personalization as a matter of course. When it comes to finances, we don’t want a one-size-fits-all solution. Instead, we want to be offered solutions that are tailored to our specific circumstances and needs.
AI powers personalized experiences and offerings in Fintech. For example, connected devices in cars allow insurtech providers to track safe driving and customize rates based on that data. AI can also deliver better experiences to consumers through more personalized marketing. Rather than blasting a single marketing message to a huge swath of consumers, AI enables Fintechs to target distinct groups based on data about their preferences, habits, and financial circumstances. This means consumers are served more relevant offers and content, making them more likely to find the products or services they need at their precise moment of need.
With its ability to derive useful insights from large datasets, AI is a powerful means of improving the speed of financial products. Given the financial sector’s historical reputation for moving slow and forcing customers to wade through multiple levels of bureaucracy to accomplish most financial tasks, greater speed is key to improved customer satisfaction.
AI allows fintechs to automate many processes that previously had to be carried about by humans. For example, AI powers the automation of risk assessment and insurance claims, bringing greater efficiency to the insurance market. It can also be used for fraud detection, which enables faster transaction approvals and reduces the amount of incorrectly declined transactions.
Conversational interfaces (chatbots) that use natural language processing (NLP) are increasingly used to settle customer issues, which alleviates the heavy burden on call lines and human representatives. As a result, customers are able to resolve their questions faster -- no hold music required.
Humans are fallible by nature, and though machines are only as smart as the data that informs them, they are far less likely to make mistakes than we are. Not only can AI promote speed in fintech, it also brings greater accuracy to a whole host of financial services, products, tasks, and tools. For example, AI can power more accurate risk assessment in Insurtech products. It’s also able to more accurately detect things like fraud and money laundering.
AI in the form of robo-advisors help consumers execute smarter trades and mitigate their risk. The result is better management of investments. Robo-advisors help democratize the investment landscape by making accurate, informed advice more accessible.
An eye toward customer satisfaction
Each of these things -- personalization, accuracy, and speed -- comprises a different piece of an overall push toward greater customer satisfaction. AI has much to offer fintechs in its ability to automate internal processes, allowing them to keep overhead low and operations lean. However, it’s when AI is brought to bear in service of the consumer experience that we really begin to see this technology’s capacity to completely revolutionize the sector.