Generative artificial intelligence (AI) tools, like the popular ChatGPT and Midjourney, are cropping up across countless industries, with experts touting the potential they have to revolutionize the way we work. The banking industry, in particular, stands to gain a huge lift, with McKinsey estimating anywhere from $200 billion to $340 billion in value generated from increased productivity.
But that doesn’t mean financial institutions can create their own chatbot and expect to make bank. An effective implementation requires strategic thinking and an expert solutions partner.
To understand how banks can benefit from the AI boom, let’s briefly examine the tech powering these transformative tools: generative AI and large language models (LLMs).
Generative AI and LLMs — What’s the difference?
Generative AI and LLMs are closely related, but they serve different purposes in the world of AI and banking. Whereas generative AI is trained on data to synthesize new content — such as text, images, video or audio — based on learned patterns, LLMs are a specific subset of generative AI, focusing on understanding, generating and predicting text.
While not all generative AI tools are built on LLMs, all LLMs are a form of generative AI.
Emerging applications of AI in banking
Voice-enabled virtual assistants are quickly becoming a customer service standard in the banking industry. However, they aren’t the only application. With foundational LLMs trained on proprietary knowledge, banking data and real-world interactions, these AI solutions can help financial service providers streamline customer support and capture even more value.
Here are a few use cases to be on the lookout for:
1. Elevate the customer experience
Voice and text chatbots with natural language processing enhance customer interactions and improve their overall experience by providing real-time assistance and information.
2. Simplify self-service and agent hand-offs
Digital assistants enable convenient self-service and staff assistance, offering a seamless transition of information to a live agent when necessary.
3. Automate repetitive support tasks
AI knowledge assistants streamline operations by automating frontline customer service tasks, saving agents time to focus on higher-value tasks.
4. Improve accuracy
AI-powered platforms can help eliminate human error and detect fraud thanks to their impeccable pattern-recognition capabilities.
5. Maintain compliance
AI solutions can automate documentation and customer ID verification to maintain regulatory compliance while boosting efficiency.
The dangers of DIY AI
While many of these applications for generative AI and LLMs have been tried, tested and proven, designing these solutions in-house presents significant challenges — often with little reward. Not only is developing proprietary AI systems highly resource-intensive and time-consuming, but it also requires a substantial up-front investment in research and development (not to mention ongoing maintenance and upgrades).
Instead, established AI providers like Posh offer ready-made, easy-to-use, scalable solutions designed by experts in both AI and financial services. These cutting-edge tools offer seamless integrations with core banking systems and rapid deployment to keep pace with the industry and the rapid evolution of generative AI.
Crucial considerations for integrating AI with banking systems
While AI systems have been used in banking for some time, generative AI and LLMs are innovations that require a strategic approach to ensure their success. When looking to integrate these cutting-edge solutions, banks should consider the following factors:
- Maintaining compliance with regulations: Banking is highly regulated in some areas, such as scoring credit risk, but other processes, like customer service, aren’t. AI must align with these regulations to meet legal and ethical standards.
- Training the end user: Whether agents or customers, banks must consider how they will inform and train their end users to leverage new AI technologies.
- Establishing the level of automation: Banks must also decide the extent to which they will use AI assistants. Some may choose to have them act autonomously, while others will use them in conjunction with live agents.
- Ensuring data privacy and security: Protecting sensitive information is non-negotiable. Any AI solution needs robust security measures and encryption protocols to safeguard customer data.
- Keeping up with technology: Banks should also choose an AI solution that will remain up-to-date, helping them remain competitive and stay on the cutting edge of the ever-evolving AI landscape.
- Upgrading storage and IT infrastructure: As generative AI solutions use and create vast amounts of data, banks must also ensure their storage and IT infrastructure can handle the increased load.
To learn more about the work Posh is mitigating these risks for our financial services partners, feel free to read our full article on the topic.
Empower customers and teams with Posh’s AI banking solutions
Looking for an AI solutions partner for your financial institution?
Posh is making the world of banking more flexible, accessible and efficient with our state-of-the-art suite of AI-powered solutions:
Voice Assistant
Our Voice Assistant is revolutionizing customer service for financial institutions by delivering intelligent, natural interactions around the clock. With a 24/7 automated agent capable of handling routine inquiries, your customers get the answers they need without draining resources.
Digital Assistant
Posh’s Digital Assistant empowers your banking operations with an automated solution for customer service. Digital Assistant lives on your website or within your online and mobile banking platform, efficiently addressing questions without the need for human intervention.
Knowledge Assistant
Lastly, our Knowledge Assistant is a game-changer for frontline staff, empowering them to address complex customer queries with a centralized knowledge platform to democratize access to information. When all employees have what they need, you can eliminate inaccuracies, unsuccessful searches and all the downstream impacts that come with it.
Want to see Posh in action? Request a demo today!
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Generative Al and Large Language Models: Applications Shaping the Banking Industry
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October 31, 2023
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