How Banks Can Use Generative AI to Elevate Operations and Customer Experiences
In today’s rapidly evolving world business as usual is out and change is in. Welcome to a dynamic new world of digital finance where financial leaders are futurists initiating change rather than reporting on it. The future of finance is dynamic and the future starts now with Microsoft Dynamics 365.
Introduction
AI is poised to create waves of rapid change across industries. As leaders weigh the advantages of integrating AI into their operations, banks must consider applying those advantages to drive operational efficiency and deliver outstanding customer experiences.
Generative AI goes beyond traditional AI by creating brand new content, helping bypass hours of labor, and freeing teams for more human-centric activities. This e-book will explore the different use cases for these AI capabilities in banking institutions and discuss how AI applications can improve customer service, bolster decision-making agility, and accelerate processes.
How is AI used in banking?
- Summarizing customer engagement conversations
- Empowering advisors with intelligent insights
- Automating business processes
- Generating original tailored content
- Expanding accessibility and language options
What is generative AI and what can it do?
Generative AI differs from traditional AI in its ability to create content or data that didn’t previously exist. While traditional AI technology focuses on pattern recognition and making decisions based on existing data, generative AI goes beyond that by creating new information, such as images, text, and even coding. It’s the difference between a chatbot that can only move along a predetermined path and a virtual assistant who can take the lead and guide conversations based on new data.
For bankers, the rise of new AI capabilities requires figuring out how this kind of technology can add value to your institution and deliver better experiences to your customers—without adding cost, technical complexity, or security concerns.
Innovate to improve customer journeys
From the early stages of awareness to conversion, onboarding, and ongoing customer service and support, banking relationships rely on a strong foundation of trust. Generative AI capabilities can help lay that foundation by providing automated human-like assistance while giving agents more time and mental stamina to provide personal assistance where it’s needed most.
How can AI help improve your customer lifecycle?
- Automate segments of the customer journey. Virtual agents can help guide prospective customers through some of the early stages of learning about your products and services, answering questions and explaining complex ideas in lay terms. Behind the scenes, AI assists by automating follow-up communications, summarizing conversations in your contact center, and creating customized marketing materials that speak directly to specific customers’ pain points.
- Give new customers the gift of clarity. During the signup and onboarding processes, lack of clarity about products, services, and procedures can start the account off on shaky footing. But even seasoned bankers can have difficulty explaining complex banking procedures to new customers. AI helps provide greater transparency by generating clear, concise explanations of complex concepts. This gives new account holders greater confidence that their new bank isn’t keeping them in the dark or skirting hard-to-grasp details.
- Build trust into the fabric of the customer lifecycle. New and old account holders alike want to know they can trust their banking institutions to protect their finances in the long term. AI makes it easier to review your customers’ history and anticipate their most relevant financial needs, so you can be there with the right service at the right time. Plus, by shifting manual processes away from employees, AI gives bankers more time and mental capacity to focus on issues that require a devoted human touch.
Empower advisors with intelligent support
As advanced as AI capabilities are now (and will become in the future), they still can’t replicate human intuition and creativity. Rather than viewing AI as competing for human roles, banks should embrace AI for its potential to automate and expedite the tasks that only require a human-like touch.
For example, advisors typically spend a lot of time searching through extensive documentation to find answers that will help their clients. AI assists in sifting through data quickly and generating visual summaries so advisors have more time to apply their personal skills and attention to the tasks that genuinely require their attention. In this way, AI has the potential to enhance human connections in banking—not replace them.
How does AI empower advisors?
- Gathering relevant information. By gathering information from multiple sources, such as client profiles, financial plans, and previous meetings, AI helps advisors gain a fuller understanding of their clients and their needs while also saving precious hours.
- Generating material for client engagement. AI can help generate customized pitch books and marketing materials for specific clients and can share summarized or detailed information regarding investment inquiries about portfolios and assets under management.
- Generating transparent sales and onboarding content. Summarizing, organizing, and creating curated content makes bringing new clients in easier and helps them become accustomed to your services. With AI, you can generate hyper-personalized scripts and onboarding documents using clear-cut language so new customers begin with a solid understanding of what they need and what they’re agreeing to.
Uncover areas for improvement
Like physical goods, the value of data depreciates over time. This means that the sooner you can search through and analyze your call center data, the more agility you have to make data-based decisions when they’ll have the most impact.
Buried in call transcripts are valuable insights into call center activity. Generative AI tools help you extract and analyze those insights from one-on-one conversations to give you a fuller view of customers’ needs so you can be faster to respond with better strategies and practices.
How can you use AI in your call centers to find opportunities for improvement?
Extract call center insights in real time. Tools like Speech API and Azure OpenAI Service help you extract critical insights from call transcripts, which you can use for coaching in real time, tracking customer sentiment, or partially automating portions of the customer journey until it’s time to loop in a live agent.
Make knowledge more accessible
Generative AI tools make it easier to know (and understand) the ins-and-outs of your product, helping customers, bankers, and advisors access the information they need, extract the most relevant parts, and clearly articulate complicated information.
- Enable multifaceted organizational learning. Quickly retrieve information from your knowledge base in contextualized, natural language to use for training, learning about products, and automatically generating notes and summaries for reference or sharing.
- Improve comprehension at every touchpoint. AI can help give more transparency to customers easily confused by technical terms or complicated procedures. By generating simplified versions of documentation or providing live speech transcription during conversations, AI helps customers receive information in a way that helps them feel more confident in their financial decisions and activities.
- Start meaningful conversations. Sometimes it takes a contextualized, two-way conversation to help guide people to a solution. Generative virtual agents help retrieve information in the context of a two-way conversation, using natural language to answer questions, generate and deliver curated content, and so forth.
Detect fraud with greater visibility
Fraudsters have also noticed generative AI’s potential in creating new content and imitating human conversation. Used with traditional AI, generative AI helps banks add another layer of protection against technologically advanced bad actors.
- Investigative business reporting uses search prompts to create a summary of vulnerabilities, false positives, and other indicators of your bank’s current state of security effectiveness.
- Historical voice and text analysis assists in detecting indicators of fraud—such as impersonation and account takeover—matching voices to known bad actors and identifying fraudulent patterns.
- Fraud detection training and testing models use synthetic data to help improve the accuracy of your fraud detection models.
- Predictive analysis proactively analyzes unstructured data to better understand your customers’ behavior so you can more accurately spot signs of fraudulent activity in their accounts.
Looking forward
For forward-looking banks, AI technology is poised to be a game-changer that helps drive greater efficiency, protect against fraud, and innovate improvements.
Still, some banking decision-makers remain hesitant about incorporating AI too soon—either because they’re unsure of its capabilities or concerned they lack the resources to take advantage of its best features. Before moving forward with integrating AI into your institution’s processes, you need assurance that AI can be managed responsibly so you can preserve the trust your bank has already established.