Finance & Banks
The finance and banking sectors form critical pillars of the world’s economy and are now ripe for the AI revolution. For global banking, McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year. This includes traditional AI solutions such as data analytics and digital banking as well as more advanced solutions for portfolio management, automatic loan approval, risk assessment in investments, and chatbots and conversational AIs to make customer care more efficient and faster.
AI Applications
- Credit Risk Assessment
- Customer Churn Forecast
Financial institutions provide services such as loans and lease. If a consumer defaults on a loan and fails to pay back the loan amount, the financial institution suffers a loss. Hence, it is pivotal for financial institutions to assess the risk of non-payment at the time of application. State-of-the-art AI techniques can help determine the propensity of an applicant to default and make a recommendation to accept or decline an application. This has the potential to enhance the loan approval rates and simultaneously minimize the risk of financial default of the borrowers.
The number of subscribers and product consumers who are dissatisfied with the services provided, and wish to terminate their subscription are referred to as churn. Customer churn is something all companies try to avoid, not only because of the profit loss from the leaving clients, but also the damage it causes to the company’s reputation. It is strongly recommended to prevent churns at the very early stages of dissatisfaction, as even some of the finest marketing strategies and offers fail to win back the customers once they make up their mind. Despite the complex nature of the problem, there is a good level of similarity in how clients respond to different challenges, which artificial intelligence is able to discover and learn.