In today’s interconnected world, there is a practically limitless amount of client data available to businesses. What businesses do with that data, however, makes all the difference. If AI and ML are used to collect and analyze data ethically, with emphasis on consumer satisfaction instead of profitability, banks can tweak every aspect of their structure to best serve their client base. This, in turn, extends the lifetime customer value of each individual.
7 min read
AI and machine learning changing the banking and fintech landscape
VP Sales, Financial Services
We’ve reached a point where AI and machine learning (ML) are full of promises and high expectations. The development of learning algorithms has been all the buzz in the tech industry for some time now. Many areas of banking and fintech have tons of potential to benefit from AI and ML. When these applications are taken together, we see how AI and ML can significantly improve the consumer experience.
A fountain of data
Trading for the masses
Until recently, AI and ML trading platforms were built for large institutions such as top-tier investors and bankers. The platforms were not made available to general audiences. However, recent increased interest from the general public in trading has resulted in more and more consumers dipping their toes in the field. With that, affordable apps are being developed for the everyday consumer to start trading using AI and ML. The entire investment industry will change thanks to consumers’ ability to trade and invest on their own terms.
The personalized bank
Instead of developing applications for the masses as a one size fits all solution, banks can personalize the user experience through AI and ML for each individual. Essentially, these banking apps would have virtual assistants that would learn about consumer habits and use this information to personalize the experience.
Aspects like answering frequently asked questions would help reduce the time clients spend on hold with human representatives, as well as analyzing spending habits to provide financial tips and money management strategies. The virtual assistant could also be linked to smart speakers like Alexa, providing a fluid user experience.
A new level of targeted advertising
No one likes to wonder why they are receiving advertisements that are not relevant to them. Add to this the extremely high level of competition in the banking industry, and the result is a need for highly accurate ads that are specific to the individual.
Developing AI and ML as a sales tool could drastically increase revenue for banks by delivering advertisements that fit the needs of every person on a case-by-case basis. The algorithm analyzes consumer habits and delivers ads that best suit them. When consumers know that there is a technology works for their benefit, they feel more confident than seeing mass offers sent out to all clients.
AI fraud police
Fraud and scams are still issues, which occur every day and cost people great deals of money. While banking insurance plans protect clients after money has been stolen, AI has the ability to prevent such situations from happening. AI is able to analyze suspicious activity, distinguish between people and bots, and even detect compromised login credentials. As such, consumers will feel safer with their institutions, and banks will not spend as much on reimbursing clients. Everybody wins.
Machine learning and AI will continue to push the boundaries of modern-day industries. As the technology is developed, new ways of integrating it into existing models are surfacing. If businesses focus on the customer experience, they will be able to add value to their clients and build a positive brand image.