Scaling Generative AI for Growth in the Banking Industry

We are currently experiencing a remarkable moment in the realm of artificial intelligence (AI). The advancements in AI, specifically in generative AI, have surpassed human capacities across multiple domains. Accenture’s recent report titled “A New Era of Generative AI for Everyone” delves into the transformative power of generative AI as a collaborative partner to human skills, reshaping work and driving revolutionary changes in the business landscape.

The Banking Industry at the Crossroads: In today’s landscape, it is not a matter of whether generative AI will significantly impact the banking industry, but rather how it will do so and how banks can leverage this immense opportunity to create value. The advent of mainstream technologies such as large language models (LLMs), including tools like ChatGPT, is bringing value creation across all industries at an unprecedented pace. In fact, within just six months, ChatGPT garnered over 100 million monthly active users, establishing itself as the fastest-growing consumer application in history.

The Impact on Banking: The banking sector is already experiencing the effects of AI experimentation and implementation. Lower costs, accelerated revenue growth, and enhanced contact center processes are just a glimpse of the transformations underway. For instance, Goldman Sachs has adopted generative AI tools to support its software developers in coding and testing. Furthermore, Accenture has collaborated with a leading global bank, leveraging generative AI in post-trade processing (intelligent email routing) to improve customer satisfaction and eliminate inefficiencies.

To outpace the competition and tap into incredible growth and productivity gains, banks must act swiftly. Similar to the exponential growth of ChatGPT, the adoption of generative AI in banking is expected to accelerate rapidly, with early adopters reaping substantial benefits. As generative AI presents a myriad of applications for success, banks should embrace the momentum and commence their exploration of its business implications while charting a path forward.

Generative AI has the potential to revolutionize every facet of the banking industry. As banks strive to develop and automate operations spanning the front office to the back office, applications and use cases for generative AI are multiplying daily. Here are some early areas of adoption:

  1. Front Office and Servicing Transformation: Generative AI empowers banks to leverage customer intelligence, accelerate the interpretation of customer needs and preferences, and enhance interactions across digital, phone, and in-person channels. Personalized insights provided by generative AI are supporting financial advisors, enabling them to deliver efficient and tailored advice. Contact centers are also benefiting from automation, allowing agents to provide personalized experiences and real-time insights during customer calls.
  2. Marketing: Generative AI facilitates the scaling of personalized content creation in bank marketing. The vision is to deliver customized experiences for each customer, leveraging generative AI to transform content creation across text, audio, and visual channels. Accenture collaborated with a large international retail bank to maximize customer engagement through personalized messaging, resulting in a 30-fold increase in high-quality creative content delivery without additional time investment.
  3. Operations Transformation: Generative AI solutions can streamline operational processes in areas such as consumer duty, knowledge management, complaints, KYC (Know Your Customer), and controls. By leveraging generative AI, banks can enhance bank supervisory practices, augment KYC/AML efforts, and detect potential cases of fraud with unprecedented speed and accuracy. Streamlining operations and improving user experiences are key focus areas for companies like Stripe.
  4. Data Management: Generative AI has the potential to automate data management tasks, including data product definition, lineage, and metadata. Synthetic data creation methods can be employed to bridge data gaps and generate realistic data models. J.P. Morgan’s AI Research team, for example, has successfully used generative neural networks to generate synthetic data for various purposes.

The impact of generative AI on the banking industry is far reaching. From text and code generation to images, video, speech, and applications, the effects are being felt across the entire business landscape. Generative AI is poised to drive growth, increase productivity, and unlock untapped potential. Banks that explore and experiment with generative AI today will position themselves for future rewards.

While the pace of technological advancement demands quick action, banks must proceed with caution, considering the legal, ethical, and reputational risks associated with generative AI. Concerns such as model hallucinations, difficulties in interpreting model outputs, and biases in training data must be addressed. Challenges related to cost, security, privacy, interpretability, accuracy, and environmental impact also require careful consideration. Banks must leverage existing foundational investments in Responsible AI, data governance, and FinOps to mitigate these risks effectively.

Critical decisions lie ahead for banks as they embrace the opportunities and risks associated with generative AI. Banks must consider partnerships and evaluate open-source solutions like Dolly to tailor generative AI models to their specific needs, ensuring model quality, cost-effectiveness, and safeguarding sensitive data.

Banks can kickstart their generative AI journey by developing a deep understanding of the technology, the relevant ecosystems, and the opportunities within their business and the industry. Banks must act decisively, leveraging generative AI to redefine business processes and unlock new paths to success. While challenges and risks persist, a responsible and strategic approach will enable banks to navigate the complexities of generative AI adoption effectively.

Dive deeper into Accenture’s report titled “A New Era of Generative AI for Everyone”