In financial services, the competition for customer share is intense with corporations searching for any marketing advantage while countering fraud, money laundering and other challenges. Increased customer satisfaction and loyalty, reduced fraud, and reduced regulatory fines benefit businesses that make successful use of AI. For a variety of situations, including fraud detection and credit risk scoring companies use AI.
Some clients of financial services are becoming very valuable as they produce transaction fees and build a business portfolio over the years, including banking fees, credit cards, home loans, personal loans, and more. To recognize possible churn threats, basic churn analysis uses rules based on known habits. However, rules-based systems are inflexible and lack many clients that do churn and genetic processing. That ends up offering costly benefits to clients who are not at risk of leaving the bank.
As the issue includes nuanced data over time and interactions between various consumer behaviors that can be hard for individuals to recognize, AI is a great solution for customer churn prediction. In order to assess risk, AI may look at a variety of data, including new data sources, and at relatively complex interactions between behaviors and comparisons with individual background.It is also possible to use AI to recommend the best deal that will most likely keep a valuable client. Furthermore, AI will recognize the reasons why a client is at risk and allow the financial institution to act for the individual client and more globally against those fields.
At Cyber Chasse Inc., the goal is to democratize AI for everyone so that more individuals across sectors can use AI’s power to solve business and social problems. With strong alliances with leading brands, the financial services market is a key focus for the company.
Cyber Chasse enables teams in data science to scale by significantly increasing the pace of building highly precise predictive models. Innovative features of special interest to financial services are integrated including machine learning interpretability, reason codes for individual predictions, automatic modeling of time series etc.