Conversational interfaces and chatbots are becoming more and more common. There are many universal chatbot solutions that can be used by companies from different niches, but companies like Kasisto are already developing industry-specific software intended for banks and other financial organizations. Such software will help customers make the necessary calculations and evaluate their budgets quickly.
Besides, voice recognition enables banks to provide assistance in the most convenient way possible. Such solutions will inevitably become a huge competitive advantage because banks that offer quick interaction and querying will be able to attract customers of traditional banks that require their users to log onto banking portals, look for the necessary functions, and search for the necessary information themselves.
New Standards of Security
Passwords, usernames, and security questions may disappear from the financial industry in the next few years. Security is especially important in the financial industry because most people would rather have their social media accounts hacked than become victims of hackers who want to steal their credit card information.
Therefore, the financial industry is most likely to use AI-backed security solutions to make sure that no one can access their customers’ data.
We’ve already mentioned that AI can detect unusual and suspicious behavior. Thanks to speech recognition and facial recognition, as well as the analysis of other biometric data, banks might add new layers of security or even replace traditional passwords with more effective approaches.
Automated solutions for financial sales already exist, but not all of them involve machine learning. Most often, these are rule-based systems. However, virtual assistants can also provide recommendations in a smarter way. For instance, they are already capable of making suggestions on possible changes to the portfolio, but they can also analyze various websites with recommendations on insurance services and help you choose a plan that meets your objectives.
AI-driven apps are becoming more and more personalized, and personalized recommendations are no longer used exclusively by companies like Netflix and Spotify. For instance, insurance companies already start to rely on big data, and virtual assistants capable of providing personalized recommendations might replace personal financial assistants.
Chatbots and automation software are not the only advances in financial machine learning associated with AI. Machine learning enables financial organizations to simplify numerous time-consuming tasks and to cut costs significantly, so there’s no surprise that the financial industry is already using AI in various areas.
For instance, AI can help minimize risks, fight fraud, and assist banks in making credit decisions.
Another great advantage of AI is that it provides countless personalization opportunities. Mobile banking will continue to evolve, and financial companies that fail to adopt the latest tech trends will likely lose their customers. Given that AI can work with massive amounts of data and make predictions based on the necessary set of factors, the role of machine learning in trading will also grow.
Artificial intelligence has already changed many industries forever, and its tremendous potential is unquestionable. Therefore, it makes sense to expect wider adoption of AI in finance and to prepare for the new opportunities that it offers.