The banking industry is undergoing a rapid transformation as artificial intelligence (AI) technologies are being deployed to enhance customer engagement, optimize operations, and improve decision making. AI innovation is not only a competitive advantage for banks, but also a strategic necessity to survive and thrive in the digital age.
The Benefits of AI Innovation in Banking
AI innovation offers a multitude of benefits that are critical for financial institutions to remain competitive, satisfy customers, maximize efficiency, and optimize revenue. Building AI maturity needs to be a strategic priority to ensure future success. Some of the benefits of AI innovation in banking are:
- Personalization: AI can help banks deliver hyper-personalized products, services, and communication to customers based on their preferences, behavior, context, and goals. AI can also enable banks to segment customers more effectively and offer tailored recommendations and advice.
- Efficiency: AI can help banks automate manual and repetitive tasks, streamline workflows, and reduce errors and costs. AI can also enhance the speed and accuracy of data processing, analysis, and reporting, enabling banks to generate insights faster and make better decisions.
- Risk management: AI can help banks identify and mitigate risks such as fraud, cyberattacks, compliance breaches, credit defaults, and operational failures. AI can also help banks monitor and predict market trends, customer behavior, and regulatory changes, and adjust their strategies accordingly.
- Innovation: AI can help banks create new products, services, and business models that meet the evolving needs and expectations of customers. AI can also help banks explore new markets, channels, and partnerships, and leverage the opportunities offered by the digital ecosystem.
The Key Elements of AI Innovation in Banking
To achieve AI maturity and realize the benefits of AI innovation in banking, financial institutions need to focus on three key elements:
- Intelligent propositions: Banks need to design and deliver intelligent propositions that solve customer problems, add value, and create differentiation. Intelligent propositions are powered by AI technologies such as natural language processing (NLP), computer vision, machine learning (ML), and deep learning (DL), that enable banks to understand customer needs, preferences, behavior, and feedback, and provide solutions that are relevant, timely, convenient, and engaging.
- Seamless embedding: Banks need to embed their intelligent propositions within partner ecosystems that offer complementary products, services, and experiences to customers. Seamless embedding enables banks to reach more customers, expand their offerings, and create synergies with other players in the digital ecosystem. Seamless embedding also requires banks to adopt open banking standards that facilitate data sharing and interoperability among different platforms and providers.
- Smart servicing and experiences: Banks need to provide smart servicing and experiences that enhance customer satisfaction, loyalty, and advocacy. Smart servicing and experiences are enabled by AI technologies such as chatbots, voice assistants, biometrics, facial recognition, sentiment analysis, and emotion detection that enable banks to interact with customers in natural and human-like ways across multiple channels and touchpoints. Smart servicing and experiences also require banks to leverage data analytics and behavioral science to understand customer emotions, motivations, and pain points, and deliver solutions that are empathetic, personalized, and proactive.
The Integrated Supporting Capabilities for AI Innovation in Banking
As banks rethink and rebuild their engagement capabilities with an AI-first approach, they need to leverage critical enablers that cut across all four layers of the capability stack: engagement layer (where customers interact with the bank), decision layer (where data is processed into insights), technology layer (where systems are built and integrated), and data layer (where data is collected and stored). Some of the integrated supporting capabilities for AI innovation in banking are:
- AI talent: Banks need to attract, develop, retain, and empower AI talent that can design, build, deploy, monitor, and improve AI solutions. AI talent includes not only data scientists, engineers, and developers, but also business analysts, product managers, and domain experts who can bridge the gap between technology and business.
- AI governance: Banks need to establish and enforce AI governance frameworks that define the principles, policies, standards, and processes for developing and using AI solutions in a responsible, ethical, and transparent manner. AI governance frameworks should also address the challenges and risks associated with AI such as bias, privacy, security, accountability, and explainability.
- AI culture: Banks need to foster an AI culture that encourages experimentation, collaboration, and learning among all stakeholders involved in AI innovation. An AI culture should also promote customer-centricity, agility, and innovation as core values for delivering AI solutions that create value for customers and the bank.
AI innovation is transforming the banking industry by enabling financial institutions to reimagine customer engagement with intelligent propositions, seamless embedding, and smart servicing and experiences. To succeed in this transformation, banks need to build AI maturity across their entire organization, leveraging integrated supporting capabilities such as AI talent, AI governance, and AI culture. By doing so, banks can unlock new value through better efficiency, expanded market access, and greater customer lifetime value.
