Is your AI strategy designed to provide the best possible banking experience for your customers? Our financial services sector experts explore how the application of generative AI in banking personalizes experiences, drives targeted customer acquisition, and empowers data-driven risk management strategies for profitable growth.
Generative Artificial Intelligence is often synonymous with cost-cutting opportunities and operational efficiency improvements. However, the potential of generative AI extends far beyond streamlining processes. It's a powerful driver of commercial growth, especially when aligned with a client-focused approach. With access to vast troves of customer data, banking institutions are in a unique position to leverage generative AI in tailoring their offerings to individual needs and preferences.
Our recent poll on generative AI aimed at industry experts revealed the top use cases for commercial growth in retail and business banking over the next two years. These use cases can be clustered into three key themes:
- Generative AI-powered customer acquisition and retention,
- Enhanced customer experience and cross-selling opportunities, and
- Generative AI-powered risk management for growth.
As financial institutions contemplate where to invest, it will be crucial for them to consider generative AI capabilities as an integral part of the organization’s commercial strategy to propel growth.
Generative AI-powered customer acquisition and retention
By analyzing personal financial data, purchasing data, as well as social media and browsing activity, generative AI can perform dynamic customer segmentation in real-time. With a segmentation approach of this caliber, new possibilities arise for campaign content customization and personalized offers at individualized prices.
Generative AI in banking not only reduces customer acquisition costs but also accelerates acquisition speed. Using generative AI models, fueled by data like flow of funds and interaction metrics, has the potential to revolutionize the retention playbook in retail banking. For example, identifying individual clients who are at risk of churning provides customer success teams enough time to engage and retain them.
A recent example comes from the UK digital challenger bank Monzo that just secured a 5 billion US dollars valuation and is preparing a second attempt to re-enter the US market1. At Monzo, marketing campaigns are being optimized by the power of AI. The challenger bank has built models to estimate customer willingness to take advantage of additional offers (e.g., opening a savings account) if they receive a specific message from the bank. The model informs which individual customer should receive which promotional message to maximize the outcome. This leads to significantly better results as compared to mass, non-personalized communication. The bank reports an improved campaign effectiveness by up to 200 percent, compared to traditional broad targeting.
Enhanced customer experience and cross-selling opportunities
Digital-first customers today expect banks to provide tech-driven, customer-centric services akin to those offered by other industries. Generative AI acts as an enabler in fulfilling these expectations by personalizing the customer experience, ensuring 24/7 availability, and delivering proactive customer service.
Virtual chatbots serve as a prime example, offering continuous support and fostering meaningful interactions tailored to each client's needs. Unlike traditional methods, integrating generative AI within these chatbots helps you discern valuable insights from customers' digital interactions. This, in turn, enables you to anticipate their needs, offer proactive advisory services, and provide insights for ideal product matches and cross-selling opportunities.
Klarna's AI assistant powered by OpenAI, launched this year, serves as an example. Within a month of its global launch, the AI assistant took over two-thirds of Klarna's customer service chats, performing the workload of 700 full-time agents. Klarna's utilization of machine-readable customer interaction data enabled a comprehensive understanding of customer motivations and pain points. The goal was to provide targeted responses through customer support, service, and product placements.
Generative AI-powered risk management for growth
Beyond its role in assessing credit qualifications and limits in near-real-time, generative AI substantially reduces default risks to bolster a bank’s overall performance. Moreover, its role in cybersecurity, a domain expected to expand significantly in the foreseeable future, cannot be overstated.
With damages from cybercrime projected to surpass 13 trillion USD annually by 20282, the banking sector remains highly vulnerable. Generative AI’s capability to analyze vast datasets in real-time and detect patterns or anomalies aids proactive defense against potential cyber threats or fraud.
The British startup bank, OakNorth, serves as a prime example of risk management utilizing this technology. The bank's innovative generative AI-driven lending approach resulted in remarkably low default rates for small and medium-sized businesses (0.07 percent compared to the sector average of 0.32 percent in 2021). This involved providing a detailed analysis for each borrower by integrating large volumes of external data with the borrower's own data.
Determine generative AI as part of your commercial strategy with Simon-Kucher
The applications of generative AI in banking are constantly expanding. Simon-Kucher’s research shows this technology has far-reaching impacts, including driving product innovation through product roadmap ideation and providing business insights by anticipating market trends.
The cost of waiting to leverage generative AI in banking will be significant, given its rapid adoption by industry leaders. When conceptualizing its capabilities for your organization, its crucial to ensure a strategic match between your commercial strategy and generative AI vision and ambitions. At Simon-Kucher, we help to unlock these lucrative opportunities through a combination of our deep experience in financial services and our proprietary digital capabilities.
We are passionate about growth. Ready to discover how generative AI can fuel yours? Contact us today.
Keep an eye out for the next article in this series, where we delve into the use cases of generative AI in other financial services sectors, such as payments and wealth and asset management.
Explore all the Generative AI Insights here
See how Simon-Kucher supports organizations on integrating Generative AI into their commercial strategy here
