In the past few years, blockchain technology has dominated the headlines as shows of how a single disruptive technology can fundamentally shake up the financial services space. Yet, these are mostly soundbites. Much closer to the truth is that the more mature AI technology has already brought fintech to a new level of innovation.
Even before the advent of AI, financial services companies were able to collect a huge amount of data about their clients. Processing swathes of data to derive new products and services has now become standard practice. But the arrival of AI has led to quantum leaps in progress across various areas of the industry that range from enhancing customer experience, facilitating more efficient processes, and enabling the entry into untapped territories such as serving the unbanked.
Fintech versus techfin
Unlike many other sectors, in which startups would seek to unseat the incumbents, new fintech entrants have been willing to be catalysts to traditional financial services players, rather than compete with them. This is partly due to regulations, which have restricted the forms and shapes of products and services that fintech vendors can offer in the market. This gives rise to a different way of how companies in this sector work: operating at “techfin” instead of “fintech.” Whilst there are no standard definitions, some refer fintech to a financial company that explores technologies to come up with a better way of delivering financial services. This includes traditional banks offering mobile banking as well as the so-called challenger banks that only have online presence.
“Techfin,” by contrast, describes a technology company wanting to deliver financial services. Just witness how almost all the tech giants globally are active in the payment space. On the other hand, startups and “scaleups” introduce their technologies to overcome challenges found within existing financial services companies. An example will be vendors helping banks deploy their technologies to automate to a large extent the costly and burdensome “know-your-customer” activities.
Use of AI in techfin
Whereas there is a wide array of technologies that companies can immediately apply to create new propositions for financial services businesses, one that is among the most promising is AI. Generally speaking, digital transformation can bring value for companies in three ways: new business model creation, customer experience enhancement, and back-end operational efficiency improvement. AI-based techfins have recently been very active in the latter two aspects. Indeed, there are a number of fields in which AI companies introduce new propositions in the financial services industry, including:
- Credit/risk management to reduce revenue loss. AI-enabled banks are able to segment huge quantities of data to build a comprehensive customer profile and perform risk assessment. For instance, based in the US, Zest AI automates some loan underwriting processes using machine learning for their clients, helping them make better decisions and better loans. The result: increasing revenue, reducing risk, and automating the compliance process. Allegedly, Zest’s customers see approval rates upped by 15% with no increase in defaults.
- Decision-making processes streamlining. These techfins target the core part of the business that is difficult to automate, given the data silos that exist between the business units of financial services players. An example is South Korea-based AIZEN. Its ABACUS platform provides AI-driven banking as a service, connecting the different players across key value chains in finance. It automates the lending decision-making process with AI predictive models. Such system integration and automation can afford new players speedy entry into as well as new and better offerings in the personal and business loan, credit card, or insurance markets.
- Conversational AI for better customer experience. This is perhaps an earlier failed experiment getting a new lease on life with AI technologies. An interesting development is ChatFlex by Taiwan’s ThinkPower. The once over-hyped chatbot is now armed with advanced natural language processing techniques to better understand customer queries. When holding conversations with customers, if the algorithm judges that the probability of being able answer the customer’s query satisfactorily is low, or if it detects a negative sentimental response, it will transfer the customer handling to the human agents. Such enhanced coordination between human agents and chatbots may finally turn the latter into a source of value and stop being a cause of endless frustrations.
Here is the marvel of technologies: whatever progress we think we’ve achieved; we are still barely scratching the surface. Bigger, better innovations remain ahead of us. At the current AI development trajectory, we are only going to see more enhancements at both the front and back end of financial services value chain. Indeed, as the recent stock exchange listing of Lemonade, a US-based startup that uses AI to sell and process insurance, shows, such technology has the potential of facilitating new business models in this sector. If the AI alone can open up so many new opportunities, when blockchain technology finally matures and becomes reality, the possibilities will be endless. Such is the power of technologies.
Terence Tse is professor of finance at ESCP Business School and co-founder of Nexus FrontierTech. Liz Pellegrini is head of financial services at Salesforce International. Mark Esposito is an economist with appointments at Hult International Business School, Arizona State University, and Harvard University, and co-founder of Nexus FrontierTech.