When you hear “AI” and “reducing operational costs” in the same sentence, you might brace yourself for a conversation about workforce reduction. Don’t worry—that’s not where we’re headed.
Instead, we’re looking at how strategic AI implementation can enhance your team’s capabilities, freeing them to focus on the golden, high-value work that only they can deliver. Read on for some of the best ways to use AI in financial services (without undermining your human workforce).
Why Are So Many Financial Services Using AI?
The quest to optimize operations is universal among financial institutions. Like your competitors, you’re probably looking to:
- Reduce unnecessary steps in your processes
- Eliminate time-consuming manual tasks
- Reorganize workflows for maximum efficiency
The difficulty is, how do you achieve all that without compromising on quality or compliance?
Enter AI
With ever more affordable options available, AI-driven tools offer a smarter way to streamline. When used effectively, they can reduce the repetitive work that holds teams back from real productivity, giving a significant boost to business profits at little to no added cost.
There is, however, a caveat: selecting and implementing the right AI technology without dedicated IT support for financial services can be overwhelming. This is especially true for smaller organizations whose teams likely already have their hands full with day-to-day operations.
So let’s simplify things and talk about just three worthwhile ways your business can get started with AI.
1. Client Segmentation: The Shortcut You Didn’t Know You Needed
One of the most powerful (yet underutilized) top AI uses for financial services is intelligent client segmentation.
Why is effective segmentation so valuable? It enables you to:
- Deliver truly personalized services tailored to specific client groups
- Allocate resources strategically toward your most profitable relationships
- Design targeted marketing efforts that resonate with distinct client needs
- Uncover hidden opportunities for cross-selling and upselling
With AI-driven client segmentation tools, you gain the power to understand your client base faster, more effectively predict their needs, and ultimately provide better services.
The Case for AI-Driven Segmentation
Choosing to use AI here makes complete business sense. Creating those segments manually is no easy feat—even the Excel wizards in our St. Louis-based IT services team will tell you that traditional methods are extraordinarily time-intensive.
Often, they’re also ineffective. Your team might invest hours poring over spreadsheets, attempting to identify meaningful patterns, only to create segments that don’t accurately reflect client behavior or desires.
It’s not uncommon for businesses to spend weeks on segmentation projects that ultimately yield minimal ROI. All that hard work wasted—because you’ve built segments on assumptions rather than hard evidence.
2. AI-Driven Trend Analysis: The Foundation of Smart Segmentation in Financial Services
What many financial services professionals don’t realize is that trend analysis should precede segmentation—not follow it. This reversal of the traditional approach is where AI delivers exceptional value and what makes intelligent trend analysis one of the top AI uses for financial services.
Rather than forcing clients into predetermined buckets based on intuition or industry norms, AI-powered trend analysis helps you discover natural patterns that already exist within your client base. This data-first approach can reveal surprising insights that reliance on decades of experience might cause you to miss.
Data vs. Decades of Experience
When we rely on our instincts, we sometimes get swayed by unconscious biases that end up leading us in the wrong direction. For instance, without AI, you might gather your team for a brainstorming session and decide to segment clients by conventional factors like:
- Age
- Income bracket
- Investment style
In contrast, with AI-powered trend analysis, you might discover that factors like:
- Significant life events
- Shifts in risk tolerance
- Digital platform engagement patterns
are actually stronger predictors of client behavior for your specific firm. Cue more effective recommendations for investment strategies and an uptick in glowing reviews for your team.
3. Enhanced Fraud Detection (Without Added Costs)
In our work with financial services, we’ve seen a common misconception: that reducing operational costs means accepting increased risk. That doesn’t always have to be the case—even if you’re introducing AI.
Take fraud detection, for example. Modern AI-powered fraud detection systems represent one of the best ways to use AI in financial services because they:
- Maintain vigilant 24/7 monitoring without the limitations of human fatigue
- Detect subtle pattern anomalies that even experienced analysts might overlook
- Dramatically reduce false positives that consume valuable staff time and create client friction
- Continuously learn and adapt to emerging fraud techniques without manual updates
The Result?
Your fraud detection team can focus their expertise on investigating legitimate threats rather than drowning in manual reviews. This simultaneously improves security, reduces costs, and enhances the client experience—a rare triple win in financial services.
What Are the Best Ways to Use AI in Financial Services Securely?
Despite their widespread appeal, public large language models (like ChatGPT) present considerable risks when it comes to handling sensitive financial data.
These platforms may store queries for training purposes, typically lack the compliance certifications required for financial institutions, and operate entirely outside your security perimeter—creating potential regulatory exposure that could prove costly.
Don’t Follow the Crowd
Instead, implement AI through the purpose-built tools recommended by trusted IT support providers with deep financial services expertise. Platforms like Microsoft Power BI, for instance, offer sophisticated AI capabilities specifically designed with compliance and security requirements in mind.
These enterprise-grade solutions typically include:
- Robust security controls that meet financial industry standards
- The capacity for compliance configurations aligned with regulations like GLBA and PCI-DSS
- Granular data residency controls to satisfy jurisdictional requirements
- Comprehensive audit logs for regulatory examinations.
And, as a welcome surprise for those focused on ROI, your firm might already own licenses for these AI-capable tools as part of your existing technology stack.
Ask Us for Assistance
Successfully implementing AI solutions requires specialized expertise at the intersection of technology, finance, and regulatory compliance. As leading providers of IT services in St. Louis and beyond, Anderson Technologies brings this precise combination of knowledge to every client engagement.
Our team can help you:
- Assess your current technology stack to identify AI capabilities you may already own
- Select the right AI tools for your specific challenges and compliance requirements
- Implement these solutions securely within your existing infrastructure
- Train your team to leverage these tools effectively in their daily workflows
- Continuously monitor performance and security to ensure ongoing compliance
Get a taste of what it’s like to work with us—schedule your free IT security risk assessment today.
“In IT, you’re totally exposed to whoever comes in, so trust is paramount. Anderson Technologies is a trusted resource—we can trust them completely.”
– J.B., Director of Client Development, Financial Firm
