AI is a very important and fascinating topic right now. We’ve been discussing it at our different events lately. According to Accenture’s research report “Top 10 banking trends for 2024”, the rise of Generative AI is expected to bring substantial benefits to banks, including projected productivity gains of 20-30% and a 6% increase in revenue.
Yesterday, during the dedicated webinar, Nick Nickolovski from CHILDISH.AI talked about the implication of Artificial Intelligence on personalized interactions and really personalized offers for banking customers.
Traditional banks face several challenges in the modern banking landscape. These challenges arise due to the changing expectations of customers and the rapid advancements in technology.
To address these, banks must embrace innovation, invest in technology and talent, prioritize cybersecurity, and maintain a customer-centric approach while navigating regulatory requirements.
All-encompassing strategy formulation and adaptable, coherent execution are key to thriving in the dynamic banking landscape.
With AI tools banks can benefit when implementing:
· In the credit and risk part: implemented in scoring systems in credit qualification, limit assessment, pricing optimization, fraud prevention;
· Customer acquisition, hyper-personalized offers, propensity-to-buy, channel mapping
· Operations: early-warning signals, probability of default, customer segmentation, Intelligent offers, churn reduction, channel propensity, servicing personas, dynamic customer routing, near real-time recommendations, intelligent monitoring and alerting with early warnings.
How is it done?
· Next Best Action algorithm is used to predict the best ways and times to deliver enhanced customer satisfaction resulting in higher campaign response rates and deal closures. As an additional step, algorithms for personalized offerings can be incorporated into the system.
· Next Best Offer increases revenue by predicting the most relevant products or services and up-sell/co-sell opportunities to the individual customers.
· The models maximize the Net Financial Impact obtainable from the customers while considering the applicable risk limits.
· PtB (Probability of Default) models enable the expansion and optimization of credit portfolios in competitive and saturated markets by calculating the likelihood, that customers will buy a product or a service. The solution takes into consideration further inputs and constraints.
With AI Targeting by the risk-adjusted expected profit of the communication becomes possible
What does it give?
· Higher Net Financial Impact (NFI) for the bank
· Prolonged Customer Lifetime Value (CLV)
· Enhanced Customer Experience
· Improved Efficiency and Productivity
· Data-Driven Insights and Decision Making
· Regulatory Compliance
· Personalized Marketing
· Automatization of Loan Application & Approval Process.
To learn more, watch the webinar’s recording below:
