The recent advances in AI over the last year have changed expectations. A healthy adoption of generative AI in the banking industry creates more purposeful, value-driven experiences.Download the AI Checklist
The recent advances in AI over the last year have changed expectations—not only for consumers but also for employees. A healthy adoption of generative AI in the banking industry creates more purposeful, value-driven experiences. For example, automation can answer member’s questions and co-pilots can assist member-facing employees to find sources for those answers.
But smaller financial institutions (FI) like credit unions and community banks have valid concerns regarding generative AI. They have questions like how to scale generative AI across all departments. Without understanding the full capabilities of AI, they risk an implementation that hurts their reputation and credibility. And it’s challenging to implement this technology while retaining the personal touch an FI is beloved for.
These concerns don’t have to hold an FI back. The right AI partner, like Posh AI, can hike the hill alongside FIs to harness the power of generative AI, let them continue shining where they stand apart, and to stay competitive against bigger institutions. I believe this is crucial in the months and years to come as generative AI continues to grow in potential and popularity.
A hallmark of FIs' success has long been the personal touch. It's what sets you apart from larger institutions and keeps members coming back. With generative AI, translating this personal touch into the digital sphere becomes simple. Unlike older chatbots that answered questions with fixed, long paragraphs, generative AI bots can weave together internal information and your member’s personal details—like whether they have dependents to provide for, whether they are relaxed or in a rush, and all the fun elements of your brand. These components create a specific and helpful response that looks and feels like you and your community.
Big banks have recognized this power. JPMorgan Chase reported a team of 200 AI researchers, 900 data scientists, and 600 machine learning engineers working on AI applications. And Bank of America’s virtual financial assistant, Erica, has had billions of dollars worth of investment. They are edging closer to replicating the personal touch that FIs have long prided themselves on—and within just the next couple years, they may! This impending shift demands a call to action for FIs. To those who may have been skeptical or overlooked the value of AI in the past, now is the time to reassess. Embracing generative AI today will secure FIs' position at the forefront of personalized digital experiences and distinguish themselves through the authenticity of personalized interactions in the digital era.
Posh’s technology solutions replicate your personalized in-person services digitally. On the customer side, Posh’s Voice Assistant answers hundreds of questions to deliver instantaneous, personalized customer service. And customer support teams rely on Knowledge Assistant to find precise answers to questions within seconds.
When I ask people in customer-facing roles about their jobs, no one ever says they love digging through online repositories to answer frequently asked questions. They say they love helping customers solve problems. No matter who you are, some parts of your work are tedious while others are a core part of your identity. The most forward-thinking companies automate the areas that employees don’t want to do so they can focus on the most rewarding aspects of their job. The chance to help your community is what has kept someone working at a financial institution for fifteen, or even twenty, years! Generative AI offers everyone a chance at an assistant to take care of the mundanity so we can focus on what we love.
Opportunities like these clearly show the power that generative AI has at a financial institution. The last thing the industry needs is an AI company bulldozing a vibrant business, supplanting healthy customer relationships and replacing them with something flimsy. The right AI solutions give employees superpowers to start solving problems in unique ways and spend more time helping people. The wrong AI partner will highlight their top differentiator as reducing operational costs like call center budgets—the right AI partner will empower call center representatives with the tools they need to wow callers and make them excited to come to work. That’s why Posh aims to offer natural experiences that translate employee passion and enthusiasm into productivity at the same level as a major institution.
The financial industry is no stranger to strong cybersecurity practices. From maintaining the security of critical internal documents like SOPs to protecting customer information, financial institutions must have strong cybersecurity rigor. But generative AI brings a variety of new security and public domain risks. Trusted entities like NIST and CFPB have started releasing frameworks and guidelines for AI cyber risk, and will be releasing updates in the future.
Finding AI solutions that are purpose-built for financial institutions keeps cybersecurity practices, especially those unique to AI, at the forefront. For example, a new type of cyber attack called data poisoning compromises the database that an AI system learns on with intentional malicious information. Because Posh’s solutions are purpose-built for community banks, credit unions, and other financial institutions, we have implemented several policies and practices to ensure the cybersecurity of our products, including:
The latest executive order targeting the development and use of AI introduces a roadmap for agencies with regulation following next year.The latest Executive Order (EO) targeting the development and use of AI introduces a roadmap for agencies with regulation following next year. This comes as no surprise, because irresponsible use of AI has the potential to exacerbate discrimination, bias, and disinformation as the EO says. At Posh, we recognize these limitations and have been working to advance equity and civil rights within our platform since we began building it in 2018. To do so, we adopt a process similar to Model Risk Management, in which we identify areas of potential risk in our AI, including:
We implement behavioral testing to understand how our AI solutions perform with respect to certain characteristics. For example, if we use different gendered pronouns but hold everything else constant, we analyze how the chatbot’s response changes. We then notice inherent biases and correct them before providing the solutions to our customers. Our datasheets explain how we collect data and the represented populations to more clearly identify areas of bias and remove them.
Additionally, we strategize with our clients to reach members of their community that have historically been difficult to reach, such as those who live further away or have difficulty coming to the branch during open hours. As a strategic partner, we work with our customers to expand the reach of their services.
Generative AI is how a credit union or community bank continues to be successful in the world of digital and online banking. It's the layer that offers FIs the chance to continue providing personal experiences, harnessing employee passion, and adapting to the continuously evolving environment.
If you still have questions about the power of generative AI and its applications in the financial industry, read our blog Generative Al and Large Language Models: Applications Shaping the Banking Industry or reach out to us.