If you missed our Practical Guide to AI in Banking webinar, check out this quick recap.
During the webinar, we discussed the basic terminology around AI every executive should be aware of before launching an AI project. Next, we reviewed the chronological history of select AI/ML breakthroughs followed by a demonstration of various AI use cases. AI is transforming the banking world and our CEO shared his vision of a future where AI augments and enhances human intelligence, not replaces it. We concluded with actionable insights on how financial institutions—whether banks, credit unions, or fintechs—can begin using AI in practical ways.
At Kinetech, we believe AI should complement your existing digital strategy, not replace it. If you are ready to get started with AI but are still trying to figure out where to begin, this webinar was designed for you.
Talking About AI: What You Need to Know
The session began with a foundational overview of the key AI concepts that will help you when starting your AI journey. This is especially important when you are speaking with your team about AI, as it is easy to get lost in the hype without the right context. Here are the key topics that Kyle covered:
- AI Models: AI models are the engines that power your AI system. They are designed for specific tasks, such as generating text or analyzing images. Kyle discussed several popular models, including OpenAI’s GPT (the engine behind ChatGPT), as well as options from Meta and Amazon.
- Temperature: Temperature ranges from 0 - 2. This setting controls how creative or factual the AI’s responses are. If you need precise, data-driven responses, a low temperature (closer to 0) is preferable. However, if you are writing a blog post or looking for something more creative, a higher temperature may be appropriate. Default responses in ChatGPT are generally defaulted to 1.
- Data - Public Vs. Private: Understanding who owns your data when using AI is critical. Public AI models, such as those from OpenAI, are trained on publicly available data. However, you may want to fine-tune these models using your own data. Ensure you are clear on who owns the data you use for training your models.
- Function Calling & Inference: These terms are vital to understanding how AI works. Function calling enables AI models to interact with your applications in real time, retrieving contextual data for more accurate decision-making. Inference, on the other hand, allows the AI to make predictions based on past data.
A Quick Look Back at AI’s Journey
Next we took a trip down memory lane regarding the evolution of Artificial Intelligence and Machine Learning models. From the early days of OCR technology in 2005 to the introduction of Siri and IBM Watson in 2011, AI has come a long way. By 2022, the introduction of ChatGPT marked a turning point, reaching 100 million users in just two months; making AI a mainstream buzzword.
Kinetech has taken a measured approach to AI integration, dabbling with OCR and other technologies. With the launch of OpenAI, we quickly pivoted - launching our first AI module in 2023 and rolling out an AI-powered assistant in 2024. These tools allow financial institutions to integrate AI seamlessly into their applications, driving innovation and operational efficiency.
AI in Action: How It Can Help Your Bank
After Kyle’s discussion of AI fundamentals and the timeline to the present day, Kinetech CTO, Marc Lehane demonstrated how AI can be applied practically in banking with a live demo. He walked through a pre-built application designed to help onboard commercial clients, showcasing how AI-powered Optical Character Recognition (OCR) can streamline document intake. Here is where things got really interesting:
- AI Assistant(s): First we showcased our plug & play AI-powered assistant that can respond to customer queries. The assistant can pull data from the open web, or be trained / fine-tuned with your data, to retrieve and share information about your bank’s products and services (i.e. what is the current auto-mortgage rate).
- OCR (Optical Character Recognition): Next, Marc demonstrated how AI can scan documents, such as W9 forms and driver’s licenses, to automatically extract key data, and then populate it for the end user. This eliminates manual data entry, provides self-service tools to your customers, which eliminates work for your employees, and consolidates multiple steps in the workflow (i.e. fill in data, then share supporting document Vs. upload document and AI extracts and populates key fields - saving time and reducing errors)
AI’s Potential in Banking
AI presents significant opportunities for the banking industry. From automating repetitive tasks to analyzing large data sets, AI can transform how financial institutions operate. Michael Guido, our CEO, concluded the session by emphasizing how AI can enhance customer outcomes—whether through personalized banking experiences or more efficient operations.
For example, AI can help offer personalized recommendations to customers, such as suggesting they open a savings / brokerage account after receiving a pay raise. The goal is to use AI to engage with customers in a way that drives their financial well-being—and ultimately, drives your business forward.
How to Start with AI at Your Bank
The key takeaway from the webinar is that while AI is powerful, it is not a one-size-fits-all solution. Financial institutions must carefully assess whether they want to build, buy, or partner when implementing AI. The opportunities are vast, but so are the challenges—especially when it comes to talent, infrastructure, and security.
If you are interested in learning more about AI for your bank or credit union, we are offering a free consultation to help you identify the best use cases for AI in your operations. No strings attached!
Simply send an email to sales@kinetechccloud.com with "AI in Banking" in the subject, and we will set up a time to chat.
Wrapping Up
AI has the potential to revolutionize banking operations—from streamlining onboarding to personalizing customer experiences. Kinetech’s recommendation is to take a measured start > structure > scale approach. By starting small, getting the basics right, and expanding as you go you can eliminate risk, keep costs under control, and work toward tangible outcomes.
Good luck on your AI journey!
Watch the full Webinar, here.
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About Kinetech
Founded in 2014 and headquartered in San Antonio, Texas, Kinetech is a leading provider of composable SaaS applications and digital transformation services for the banking industry. With a focus on low-code solutions, Kinetech enables banks and credit unions to modernize their operations, enhance digital experiences, and stay competitive in today’s rapidly evolving market. The company’s flagship product, the Kinetech FinTech Cloud™, is built on the Mendix platform and provides rapid deployment and customization capabilities to banks of all sizes. For more information, please visit www.kinetechcloud.com.
