The race to harness artificial intelligence (AI) in banking is heating up, and the possibilities it brings are transforming the industry. Imagine a technology that can elevate customer experiences, optimise your bank’s operations, and adapt swiftly to shifting market conditions with unprecedented agility. Ambitious? Absolutely. Achievable? More than ever! All thanks to the evolving capabilities of Composite AI and Generative AI (GenAI), two of the most talked-about technologies in today’s banking industry.

Even though Composite AI and GenAI each bring unique strengths to the table, the path to integrating AI is not without its challenges. Addressing these challenges is key to unlocking the full potential of AI. After understanding the challenges of implementing AI, it is crucial to dive deeper into the unique roles and key differences between Composite AI and GenAI so that banks can strategically leverage them to drive long-term success in the banking industry.

What is Composite AI in Banking?

Composite AI in banking refers to a sophisticated approach that integrates multiple AI models and capabilities to create a versatile and highly customisable system tailored to the needs and objectives of banks. By combining machine learning (ML), deep learning, natural language processing (NLP), decision automation and more, Composite AI is designed to solve complex, multi-layered problems.

Key Benefits for Banks:

• Operational Efficiency: Streamline processes such as loan approvals, fraud detection, and regulatory compliance.
• Holistic Decision-Making: Use both traditional and alternative data sources for accurate and reliable insights.
• Scalability: Easily scale your AI solution to meet growing demands, whether for back-end operations or customer-facing services.

What is Generative AI (GenAI) in Banking?

Generative AI in banking is designed to create new content, data, or models, making it particularly effective for tasks such as generating synthetic data, automating content creation, and delivering hyper-personalised experiences. According to Gartner, while GenAI shines in these creative applications, it is less suited for tasks like prediction, forecasting, planning, autonomous systems and decision intelligence. This highlights that GenAI is a more specialised tool than Composite AI, excelling in creative tasks that involve producing new outputs based on input data.

Key Benefits for Banks:

• Personalised Engagement: Automatically generate customised reports, marketing content, and customer interactions.
• Synthetic Data Creation: Generate synthetic data to train AI models, especially useful in privacy-sensitive environments.
• Dynamic User Experience: Create virtual assistants or chatbots that can engage with customers in personalised and conversational ways.

Key Differences Between Composite AI and GenAI

While both Composite AI and GenAI are highly beneficial, they serve different purposes in banking. In the following table, we delve deeper into the key differences between Composite AI and Generative AI (GenAI) across various features. This comparison highlights how each AI excels in its domain and where they diverge.

Harnessing the Power of Both AI

Banks often face a pivotal decision: should we focus on the operational prowess of Composite AI or the creative potential of GenAI? The real breakthrough might not be about choosing between them, but rather about harnessing their combined strengths. Composite AI offers a comprehensive suite of capabilities that can seamlessly integrate GenAI’s innovative features, creating a solution that not only enhances operational efficiency but also elevates customer engagement to new heights. 

By incorporating GenAI into a Composite AI framework, banks gain access to a full spectrum of AI capabilities, enabling them to deliver exceptional customer experiences without compromising on operational robustness. This integrated approach ensures that banks are not merely adapting to the future—they are shaping it.

Conclusion

So, which is the better choice for banks—Composite AI or GenAI? The answer is that you do not have to choose. Composite AI offers a solid, scalable framework for operational excellence, while Generative AI brings a new level of creativity and personalisation. The most effective strategy is to embrace both, as demonstrated by JurisTech’s Composite AI platform. By integrating a Composite AI platform, banks can create a dynamic, future-ready environment that leverages the best of both AI, ensuring they remain competitive and responsive in a rapidly evolving industry.