FI Works Launches Signals to Turn Predictive Insights into Action for Community Banks and Credit Unions
Key Takeaways
- •FI Works launched Signals on November 10, a machine learning feature that identifies households likely to add a product, adopt checking or digital services, or leave a community bank or credit union.
- •Signals analyzes an institution's integrated data rather than transaction data alone, enabling attrition warnings that can prompt outreach before a customer or member moves funds elsewhere.
- •The feature runs inside the same platform as FI Works' marketing automation and CRM, allowing teams to convert a signal into a campaign, opportunity, or frontline task without exporting lists or switching systems.
- •Predictive scores, predicted balances, and profitability estimates help institutions prioritize outreach and gauge each opportunity's potential value, while connected reporting tracks outcomes over time.
- •FI Works founder and CEO Keith Henkel said prior signal tools often flag opportunities already lost, and that Signals places discovery and action in one environment that requires no data science expertise.
FI Works, the Relationship Intelligence and Engagement Platform purpose-built for community banks and credit unions, announced on November 10 the launch of Signals, a new feature that applies machine learning to identify households likely to add a product, adopt checking or digital services, or leave the institution altogether.
The company says the launch addresses a common frustration among community institutions: predictive tools that surface opportunities but leave staff to figure out how to act on them. Signals is designed to close that distance by pairing model-driven identification with execution tools in a single environment.
Because Signals runs inside the same platform as FI Works’ marketing automation and CRM, teams can move directly from a signal to a targeted campaign, an opportunity, or a frontline follow-up task — without exporting a list or switching between systems.
“Finding the opportunity is only half the job. Signals puts discovery and action in the same place, which is where community financial institutions have always needed them,” said Keith Henkel, founder and CEO of FI Works.
Community institutions are increasingly investing in tools that promise to spot opportunities hidden in their data. Many of those tools, however, rely primarily on transaction data, which reveals only a narrow slice of a relationship. By the time a payment to another lender appears in the transaction feed, the customer or member has often already moved the business elsewhere. FI Works describes Signals as its answer to that gap.
“Institutions that bought signal tools in the past tell us the results feel like a ‘so what,’” Henkel said. “Most of those tools point to opportunities you’ve already lost. FI Works Signals casts a much wider net across everything an institution knows about its relationships, and it lets a team go straight from a signal into a campaign in seconds. No one needs to be a data scientist to use the results.”
Signals analyzes an institution’s integrated data — not transactions alone — to uncover opportunities to grow loans and deposits, increase service adoption, and retain valuable relationships. Predictive scores help financial institutions prioritize outreach, while predicted balances and profitability estimates show the potential value of each opportunity. Because the feature is designed to detect early warning signs, an attrition signal can prompt a conversation before the customer or member starts moving money. Connected reporting helps teams track outcomes and refine their approach over time.
“Finding the opportunity is only half the job,” Henkel added. “Banks and credit unions need to know whom to contact, why, and what that relationship could be worth, and then they need a way to act on it. Signals puts discovery and action in the same place, which is where community institutions have always needed them.”
With the launch, FI Works positions predictive scoring, predicted balances, profitability estimates, and connected reporting alongside the campaign and relationship-management tools that community institutions already use day to day.
Source: Global FinTech Series
