Generative AI is Transforming the Banking Landscape

Generative AI is an innovative technology that allows machines to produce new, original content or data independently. Using complex algorithms, deep learning techniques, and tools like Large Language Models (LLMs) - think of LLMs as highly advanced digital brains that can understand and generate human-like text - generative AI surpasses the capabilities of traditional AI models. This technology can simulate human creativity and generate content that closely resembles human-created output, be it in the form of text, images, or audio. The applications of generative AI span across diverse fields such as art, entertainment, marketing, and research. Importantly, this ground-breaking technology is also making significant waves in the banking sector.

Banking and Generative AI: Adding value, reducing cost
Generative AI is not just a buzzword. The impact to the Banking Sector could translate to an annual revenue increase, due to productivity, of 2.8 to 4.7 percent, equivalent to an additional $200 billion to $340 billion in the sector's revenues. Alongside this financial boon, generative AI's implementation can elevate customer satisfaction, enhance decision-making capabilities, improve employee experiences, and mitigate risks through advanced fraud and risk monitoring.

Banking and Generative AI: A Technological Symbiosis
Banks have seen significant benefits from AI applications in areas like marketing and customer operations. Generative AI, in particular, stands out due to its proficiency in text-related activities, a critical aspect of regulations, programming language, and customer interactions in banking.
There are a few key characteristics that make the banking industry ripe for integrating generative AI:
Digitization and Legacy IT Systems: Banks have been actively digitizing their operations, albeit with a hefty technical debt and a complex IT architecture.
Customer-Facing Workforces: The industry heavily relies on customer service representatives and financial advisors, where AI can make a substantial impact.
Regulatory Environment: With numerous risk, compliance, and legal necessities, AI can provide a valuable tool for navigating the regulatory landscape.
White-Collar Industry: Generative AI can assist all employees across the organization, helping in tasks like email writing, business presentations, and more.

Early Adopters: Banking on Generative AI
In their quest for enhanced service delivery and operations, banks have started recognizing generative AI's potential. The early adopters are leveraging solutions like ChatGPT and industry-specific tools for software and knowledge applications. Here are a few ways in which generative AI can be put into action:

Virtual Expert to Augment Employee Performance: A generative AI bot, trained on proprietary knowledge like policies and research, can provide round-the-clock technical support. With it, frontline workers could offer improved customer experience by having access to data and the latest industry trends. For instance, Morgan Stanley is creating an AI assistant using GPT-4 to help wealth managers quickly locate and synthesize information from a vast internal knowledge base. In Europe, a bank has deployed generative AI to develop an ESG (Environmental, Social, and Governance) virtual expert, which provides answers to complex queries by synthesizing and extracting information from lengthy unstructured documents. Banks can effectively leverage generative AI through products that are already available in the market, like FINaplo.AI, eliminating the need for internal R&D. FINaplo.AI is an AI assistant designed specifically for bankers. Unlike customer-facing AI applications it serves as an internal tool for banks, enabling employees to answer complex queries by interpreting and analyzing the bank's transactions.

Code Acceleration to Reduce Tech Debt and Improve Software Delivery: Generative AI tools can be game-changers for software development. They can draft code based on context, run and review different code tests, optimize legacy frameworks' integration and migration, and review code to identify flaws and inefficiencies. The result? More robust and effective code, delivered faster.

Revolutionizing Customer Operations: Generative AI can revolutionize customer operations by improving customer experience and agent productivity. The technology can automate customer interactions using natural language, improving issue resolution rates, reducing handling times, and decreasing agent attrition. AI assistants can even help less-experienced agents communicate more effectively, mimicking the techniques used by higher-skilled counterparts. Moreover, generative AI can further refine customer service by providing real-time, personalized responses to complex customer inquiries, reducing response times, and suggesting tailored product recommendations based on customer preferences. McKinsey research suggests that generative AI could further reduce human-serviced contacts by up to 50 percent, depending on a company’s existing level of automation. Generative AI's implementation could translate into a productivity increase ranging from 30 to 45 percent of current function costs. Not to mention, the improved customer experience could have a positive knock-on effect on customer satisfaction and retention.

In Conclusion
Generative AI has a significant role to play in shaping the future of the banking sector, potentially increasing annual revenue due to productivity by 2.8-4.7%, translating to an additional $200-$340 billion. This technology is transforming areas such as customer service and software development by leveraging its proficiency in text-related activities. Notably, it serves as a valuable tool for navigating complex regulatory landscapes. The effective implementation of generative AI could boost productivity by 30-45% of current function costs, enhancing customer satisfaction and retention. Tools like FINaplo.AI are going to set the Future of Work in the Banking industry. Generative AI will be seamlessly embedded in daily banking tasks, much like the grammar checker.

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