The 3 Key Elements of Responsible AI

Generative AI has exploded onto the scene with unique possibilities and bold promises. Unlike other types of AI, such as those that identify patterns and make predictions, generative AI stands out because of its ability to create entirely new and original content. With just a basic prompt, it can generate a large amount of content in mere seconds.

Banks see a real opportunity this technology offers to support frontline customer experience teams that face high call volumes, staffing shortages and rising online abandonment — a part of the company where margins continue to be thin and bankers are expected to do more with less. AI could provide significant lift and value to customers, agents and managers alike.

However, in this highly regulated industry, the stakes couldn’t be higher. Generative AI can also threaten customer privacy, security and operational resilience. If an AI solution doesn’t have embedded iron-clad data privacy and PII data is shared, banks are likely to face eroded trust, regulatory fines and customer attrition. Another risk includes legal and regulatory issues that could arise if information is misaligned with a bank’s policies and procedures, such as if loans are mistakenly approved or if policy claims are inappropriately rejected. These are just a few instances of how generative AI could land banks in hot water if the technology isn’t approached carefully.

To leverage AI effectively and safely, banks need a responsible approach to AI to mitigate risks while propelling innovation. Responsible AI provides guardrails, guidelines and control to banks during customer interactions, safeguarding against the common errors, issues and concerns associated with today’s generative AI. Leveraging such a responsible AI framework enables banks to better evaluate whether potential AI partners and technologies meet specific privacy, security and compliance standards. The three key components of responsible AI are safe, turnkey and proven.

• Safe. Responsible AI should never leave its secure platform, which should have protections embedded into the infrastructure. It should be encrypted by with redundancy and high reliability to ensure data integrity and protection. With responsible AI, client data should not be used to train foundational models.
• Turnkey. Banks can take advantage of out-of-the-box, purpose-built AI, with simple setup, training and use. An AI solution that is prebuilt specifically for financial services ensures the proper practical uses, workflows, content management, reports and insights.
• Proven. With responsible AI, banks can enjoy results and value like productivity and efficiency gains almost immediately.

AI, when approached responsibly, can deliver significant value and improve experiences for customers, agents and managers. For instance, AI-powered, user-friendly tools can train staff in minutes, streamline workflows and reduce handle times, boosting agent productivity. Turnkey AI virtual assistants can automate most customer interactions across phone and digital channels, helping boost efficiency, lower wait times and enable agents to focus on more complex tasks, while increasing customer satisfaction.

AI applications can also power faster, more personalized interactions with customers, helping establish new relationships and deepen existing ones. Leveraging AI within the customer experience strategy provides insightful data and reporting, helping shape customer service strategies and other important business decisions. Customers benefit from streamlined interactions, agents are more productive and managers gain deeper, relevant insights.

As AI continues to gain momentum, banks face an important choice: embrace it responsibly or get left behind. While there is no shortage of AI technologies and providers, banks that look beyond the hype and focus on introducing safe, turnkey and proven responsible AI solutions will be well-positioned to achieve immediate value for customers, agents and managers while safeguarding the institution and its customers.