In an environment dominated by technological advancements, competition and cyber crime, financial institutions are increasingly motivating themselves to use advanced technologies to ensure security and customer satisfaction. Indeed, the banking customers want to benefit from high quality experience and improved continuous connection to banking services.
With immense analytical power, Machine Learning is one of the technologies used by banking services, but what is machine learning? How does Machine Learning innovate banking systems?
Machine learning is the use of artificial intelligence tools, that is to say the use of complex algorithms for the design and predictive analysis of data, thus allowing a machine to solve difficult tasks. In the banking sector, the data used by machine learning include browsing habits on banks’ online sites, connection habits, transaction habits (bank transfers), etc.
The use of this technology in the banking sector could result in significant cost savings, increased productivity through the automation of repetitive tasks and better data exploitation.
Machine learning is a technology that allows banks to:
- Detect, automate, anticipate and manage responses to real-time fraud scenarios.
- Analyze the profile and behavior of customers in real time.
- Adapt authentication to each user to provide an optimal customer experience for every digital banking transaction.
- Predict the evolution of a customer’s habits, and which products to recommend.
- Authenticate identities.
- Protect data
- Improve customer satisfaction by offering the most relevant offers possible.