Amazement. Excitement. Controversy. Fear.
By now, you’ve probably heard of ChatGPT, the revolutionary artificial intelligence (AI) technology that has stunned the world in 2023. Perhaps you’ve even tried out the free version of this powerful tool to draft an email to your boss or write a poem about your pet.
As exciting as generative AI applications like ChatGPT are, they’ve also triggered fear and uncertainty across many spheres, from education, where many school districts have banned students from using AI to write their term papers, to the financial services industry, where major banks like JPMorgan Chase, Bank of America and Wells Fargo have prohibited their employees from using AI for corporate communications, citing compliance concerns. Meanwhile, other financial institutions, such as Goldman Sachs, are experimenting with generative AI tools internally to help write and test code, which has some developers worried about their roles.
While conversational AI tools like ChatGPT, Jasper and Google Bard have suddenly captured the public’s imagination, the underlying technology is not new. And it’s certainly not the only—or best—use case for generative AI in banking.
How did we get here?
Generative AI has a long history. The first chatbot, named ELIZA, was invented by an MIT professor in the 1960s. But it wasn’t until a type of machine learning algorithm known as generative adversarial networks (GANs) was introduced in 2014 that the technology had advanced to the point where AI can produce convincingly real images, video and audio of actual people. The brilliance of the GAN approach is that it pits two unsupervised learning models—called the “generator” and the “discriminator”—against each other to solve a particular problem.
Today, generative AI has advanced so far that it can behave and interact in convincingly “human” ways. Consider the two-hour conversation a journalist had with Microsoft’s ChatGPT-powered Bing search engine, where the AI declared its undying love and tried (unsuccessfully) to convince the reporter to leave his wife.
While generative AI might feel new and exciting, cognitive technologies like AI, machine learning and robotic process automation (RPA) have been around for years. From roboadvisors that analyze vast amounts of data, such as market trends, economic indicators and investor preferences to manage portfolios for clients, to deploying AI-powered chatbots to provide 24/7 customer support, to using AI toautomate regulatory compliance tasks, such as monitoring transactions and identifying suspicious activity, these tools have already had a positive impact on the financial services industry. In fact, nCino has been at the forefront of AI and machine learning ever since our launch of nCino IQ (nIQ) back in 2019.
While you can’t ask nCino to write your grandmother a thank you note, come up with six ideas for a themed birthday party or explain black holes to a kindergartner, you can leverage it to do something much more powerful: help your institution cross the modernization divide by powering more personalized user experiences.
In fact, looking beyond the ChatGPT hype, financial institutions can realize the greatest benefits from AI’s powerful capabilities when they are fully aligned with their strategic priorities. Features powered by nIQ, like nCino’s Commercial Pricing & Profitability and Automated Spreading, are designed to enhance efficiency and accuracy and provide deeper data insights within the commercial and small business loan cycles, are great examples of this.
Because nCino features powered by nIQ offer advanced capabilities that are faster and smarter than a human, they offer significant enhancements to traditional human-powered analysis, resulting in greater efficiency and accuracy and helping financial institutions reach their goals.
nCino continues to be a trailblazer in leveraging emerging technologies to deliver data-driven insights. Infact, with the recent announcement of our new partnership with Rich Data Co (RDC), an industry leadingAI decisioning platform, nCino is able to equip financial institutions with deeper insights into their clients’ business and empower them to improve, streamline and further automate workflow and monitoring, creating significant value and efficiencies in small business and commercial lending.ChatGPT and similar generative AI applications are garnering a lot of hype. But for banks and credit unions, the real value of AI and machine learning can be found in more pragmatic applications like automating routine processes, improving customer experiences and optimizing pricing and profitability. As a result, lenders will experience improved productivity, fewer errors and increased ROI, opening the door to an exciting new world in financial services.
As new leaps in generative AI continue to transform the world, nCino will continue to be at the forefront, ensuring that our customers can be among the first to benefit from these exciting new technologies and innovations. To that end, we’re excited to introduce this article as the first in a series on applied AI in the financial services industry. Check back in a few weeks to read the next installment and continue this journey with nCino!
