CEO and Co-Founder of Posh AI.
New risks accompany every emerging technology, and this reality is particularly evident with generative AI.
Businesses that successfully harness AI will establish a competitive advantage. The benefits have been proven: writing automation, question-answering, content generation and more. A recent study from Stanford and MIT has even quantified the benefits with data, showing that tech support agents who utilize AI have experienced a 14% increase in productivity and could even get their work done 35% faster than those operating without AI assistance.
AI For The Financial Industry
To go one level deeper, AI technology has established benefits for the financial services industry, especially when it comes to improving customer service. Banks and credit unions have unique issues that require unique solutions. Key advantages include:
• Enhanced Customer Service: Helps banks provide personalized customer service by understanding the context of customer queries and providing accurate responses.
• Extracting Insights From Unstructured Data: Allows banks to identify actionable insights by analyzing customer data at scale. Many banks today don’t have the human bandwidth to maximize the potential of their data. AI can provide a meaningful lift here.
• Empowering Staff With Knowledge Assistance: Gives frontline employees, like call center agents, access to accurate information faster to help them serve their customers more efficiently. These types of solutions are also valuable for training new hires, who often take over six months to ramp up.
The Risks Of AI Technology For Banking
While there are certainly opportunities for AI technology like ChatGPT in the banking industry, there are also potential hazards that need to be considered.
• Inaccurate Results (Hallucinations): One of the primary risks of using generative AI technology in financial services is the potential for data analysis errors or responses, resulting in frustrated customers and nonoptimal business decisions or, worse, regulatory penalties.
• Data Privacy: Generative AI requires access to large amounts of data to generate new content or recommendations. This data can be personal or sensitive, raising concerns about privacy and security. When using generative AI, ensuring your data is secure and protected is essential. Off-the-shelf LLM technology is not secure by default.
• Bias In AI Models: Generative AI models are only as good as the data they are trained on. The AI models will be biased or incomplete if the data is biased or incomplete. This can lead to unintentional discrimination or inaccurate recommendations. It’s crucial to thoroughly evaluate the training data and ensure it is diverse and representative of the population you want to serve. Many off-the-shelf LLMs are trained on large internet snapshots, which naturally contain social biases.
How To Mitigate These Risks
Best practices and safeguards can be put in place to mitigate the risks of generative AI, enabling organizations to realize substantial benefits today from this technology.
• Find The Right Partner: Select an AI partner that is vertically focused with domain expertise which inherently contributes to enhanced quality of service and security, best-in-breed knowledge and better performance. Verify that your chosen partner has a successful track record of implementing AI with the right due caution.
• Create A Plan: Work with your AI partner to develop a strategic plan to implement AI and identify the specific use cases where AI is currently applicable. As technology advances and public sentiment shifts more positively toward AI, the risks will become increasingly more manageable and provide the opportunity to expand the use across your organization.
• Strengthen Data And Privacy Protocols: As an extension, banks should ensure that vendor partners have robust data security and privacy protocols for AI to protect customer information when implementing generative AI technologies. Request evidence of audited security/privacy controls from vendor partners, such as SOC 2 Type 2 or CSA Star Level 2 reports.
• Education Is Necessary: Before choosing an AI partner, equip your organization with the knowledge needed to understand the technology, its potential and its limitations. Understand the options for configurability and that optimization is an ongoing process to help maintain and improve deliverables. A good vendor partner should take an education-first approach vs. a sales-first approach.
In assessing the risks and benefits of generative AI for your business, examining the immediate and future implications is crucial.
Generative AI can provide strong benefits but comes with risks you must learn to manage. Create a strategy and work with experts who can provide strategic guidance to ensure you create a positive impact with your employees and customers while protecting data privacy and avoiding pitfalls such as hallucinations and bias. Ultimately, the decision to use generative AI should be based on a careful evaluation and a tailored approach.