As of 2021, Chicago is home to over 800 FinTech companies across sectors like payments, lending, and insurance, collectively raising $4.58 billion in funding, a remarkable 112% increase from the previous year. This vibrant ecosystem has made the city an attractive hub for FinTech innovation. However, what’s making waves in Chicago’s FinTech scene is not just the rapid movement of capital but also the increasing role of artificial intelligence (AI) in shaping the next generation of financial products.
AI is no longer a luxury in the financial sector; it has become an essential differentiator. In fact, according to a 2022 survey, 79% of financial institutions are already integrating AI into their operations. This is just the beginning, with AI expected to generate $6.67 billion in cost savings for the sector by 2023, and a compound annual growth rate (CAGR) of 23% between 2020 and 2025.
While building a proof-of-concept for AI solutions might be straightforward, scaling these systems for high-volume, real-world, and regulated environments is where the true challenge lies. A 2021 report by Capgemini revealed that 50% of FinTech companies face significant hurdles when it comes to scaling their AI solutions. These challenges range from building the necessary data infrastructure to overcoming compliance roadblocks, which can stifle growth and slow down the adoption of AI-driven products.
This post will walk you through the essential steps to build and scale a powerful AI platform in Chicago's booming FinTech landscape.
Many founders get stuck trying to scale AI because they don’t define what that actually involves.
Let’s break it down.
An AI model is only as good as the data that feeds it. Scalability starts with a robust pipeline for ingesting, cleaning, and processing structured and unstructured data.
For FinTech, that might include:
You need an architecture that can grow from thousands to millions of data points, handle GDPR and SOC 2 compliance, and remain responsive under load.
You’ll likely iterate on your models weekly, if not daily. That means versioning, rollback, staging environments, and reproducibility.
A scalable AI platform uses ML Ops practices, not ad hoc scripts. You need continuous training pipelines, automated testing of model accuracy, and alerting when performance dips.
You can’t have a credit risk model that takes 10 seconds to return a score. Or a fraud detection system that flags transactions after they’re approved.
AI must run at the speed of user expectations, and that means optimizing inference time, caching intelligently, and using edge deployments when needed.
Too many AI initiatives stall out before they generate value. Here’s where we see the most issues, especially in early- to mid-stage Chicago FinTech companies.
Scaling AI isn’t about hiring PhDs, it’s about orchestrating people, data, infrastructure, and user experience around a clear business outcome.
When we work with FinTech teams, we use a simple but effective structure to guide platform buildouts.
Imagine a Chicago-based credit underwriting startup. Initially, they’re using basic scoring logic tied to FICO and income statements. But their edge is a new model trained on non-traditional data, like bank activity, spending categories, and digital footprint.
With Type B Digital, they could build:
That’s not just AI. That’s a scalable product platform with AI at its core.
Founders often assume they need a full-time team of 10. You don’t. With the right partner or augmentation approach, you can scale lean and fast.
Here’s a realistic build squad:
You can start with three or four of these and scale as traction grows. At Type B, we deploy these roles from multiple countries on U.S. hours, based on your roadmap.
By augmenting rather than hiring all in-house, you retain flexibility and stay capital efficient.
We’re not a typical dev shop. We specialize in turning ideas into productized platforms for founders who want to move fast without breaking things.
We don’t just build for you. We build with you, embedded into your stack and vision.
AI can absolutely transform your FinTech product, but only if you build it right.
Let’s discuss your current architecture, future goals, and the smartest path to get there.
Whether you're exploring your first model or re-platforming a working MVP, we’re here to help.
Let’s collaborate on your next big idea to start building your AI platform in a scalable way.
We are the go-to partner for bold innovators that want to turn big ideas into real-world wins.
