Financial Services
Real-time data activation for hyper-personalised retail banking
Banks and financial institutions are undergoing a seismic shift, with retail banking digital transformation leading the charge in revolutionising operational efficiency and customer experience. 73% of customers today expect financial institutions to know them, anticipate their needs, and deliver hyper-personalisation in banking as the technology evolves. As a result, banks are also focusing on predictive analytics and AI in retail banking, with 86% of financial institutions prioritising personalisation in their digital strategy and 92% planning further investment. Real-time data activation can help financial institutions deliver tailored experiences at scale, unlocking deeper customer relationships, enhancing engagement, and driving customer loyalty.
Supporting personalisation with retail banking digital transformation
Retail banking digital transformation is more than just adopting new technologies; but about how banks interact with their customers. The key elements that can help financial institutions drive personalisation and create meaningful, customer-centric experiences include:
Smart customer segmentation for precise targeting
Banks today are leveraging AI-driven segmentation strategies that factor in not only the traditional demographic parameters but also behavioural patterns, preferences, and real-time interactions. This approach to hyper-personalisation in banking can help craft tailored experiences that align with individual customer needs.
Behaviour analysis for predictive insights
Advancements in predictive analytics in banking are enabling banks to anticipate customer needs and expectations by analysing transaction histories and digital interactions. This allows them to offer relevant services to the right customers at the right time.
Intelligent cross-selling and personalised recommendations
With the integration of AI in retail banking, the days of generic product promotions are long gone. Whether it is a personalised mortgage offer or an investment plan tailored to individual spending habits, AI and predictive analytics in banking are transforming sales strategies. By analysing individual customer profiles, these technologies are enhancing cross-selling and up-selling strategies with personalised recommendations.
Customer feedback and sentiment analysis
Retail banking's digital transformation has changed how banks interact with customers and understand their feedback. Advanced sentiment analysis tools can help financial institutions extract actionable insights from feedback surveys, chatbot interactions, and social media mentions to ensure they remain responsive to evolving customer expectations.
Enhanced customer support with real-time communication
Real-time data activation and AI in retail banking are enabling banks to offer proactive and contextual customer support. Tools like chatbots, real-time messaging, and voice assistants ensure that customers receive instant and accurate assistance, fostering trust and engagement.
Challenges and benefits of predictive analytics and AI in retail banking
Although AI in retail banking offers significant potential, it is not without challenges, especially when it comes to integrating predictive analytics capabilities in banking operations. The key challenges financial institutions must overcome include:
- Siloed data: Managing data scattered across multiple systems can make real-time insights difficult.
- Multi-channel communication complexity: Ensuring seamless personalisation across mobile, web, app, and in-person interactions can be challenging.
- Privacy and security concerns: Striking a balance between personalisation and privacy is critical.
- Technology integration: Managing legacy system modernisation to integrate AI in retail banking can be challenging.
- Resistance to change: A data-driven culture across organisations – from customer-facing roles to strategic decision-makers – is essential.
- Lack of skills and resources: Many financial institutions may face a shortage of AI and analytics expertise.
However, despite the challenges, hyper-personalisation in banking offers a host of advantages for banks and financial institutions, including:
- Enhanced competitive advantage: Personalised experiences and engagement can differentiate banks in a crowded market.
- Better targeting and segmentation: AI in retail banking can help refine customer segmentation for precise engagement.
- Higher conversion rates: Contextual recommendations can encourage spending and investments.
- Improved customer retention: Proactive engagement can reduce churn and re-engage inactive users.
- Increased customer loyalty: Banks that know their customers and anticipate their needs foster stronger customer relationships.
- Optimised ROI: Data-driven insights can reduce customer acquisition costs while boosting lifetime value.
- Enhanced digital engagement: AI-driven interactions can elevate customer experience across digital channels.
- Strategic cross-promotion: AI in retail banking can help map out customer lifecycle effectively and offer relevant products at the right time.
Bringing deep domain expertise in retail digital transformation, Infosys BPM is helping financial institutions unlock the full potential of hyper-personalisation in banking and offer enhanced customer experience. From strategic workforce and workflow management and process excellence to advanced analytics, AI-driven knowledge management, and robotic process automation, Infosys BPM helps transform banking operations. By leveraging real-time data and next-gen AI in retail banking, financial institutions can create personalised experiences at scale, improve operational efficiency, and drive long-term customer loyalty.
Conclusion
The future of retail banking lies in hyper-personalisation in banking, with AI and predictive analytics in banking driving the change. As customers demand seamless, intuitive experiences, financial institutions must embrace retail banking digital transformation to stay ahead. By leveraging real-time data to deliver personalised and meaningful interactions, banks can strengthen customer loyalty and gain sustainable competitive advantage.
