The main functional destination of ML algorithms is to prominently identify work patterns and correlations among vast amounts of information, events, operations, and sequences. Thus, ML is successfully used today in process automation, security issues, customer support optimization, credit offerings, portfolio optimization, personal finance, and many other sectors.
In reality, you are dealing with the work of machine learning banking use cases if you are a client of a bank, insurance service, or any FinTech company. Some experts ironically call the introduction of AI into the financial market white magic because it's almost invisible, yet it still changes the interaction of the customer and the company for the better.
For example, the leading commercial bank in Ukraine, PrivatBank
, has effectively practiced a technology with chatbot assistants in web platforms and mobile applications. AI-based chatbots optimized the processing time of general query resolution significantly.
The worldwide known company PayPal invests in deep learning in security terms to improve its financial monitoring and fraud detection.
So, if you're looking for technology like the ones mentioned earlier—check Fayrix's technical competence in development
to find out how we can help.