Balancing Growth and Risk with Smarter Lending Strategies

Growth and risk go hand in hand.

Expand too quickly, and risk exposure can rise beyond what’s manageable. Tighten lending criteria too much, and growth slows, leaving opportunities on the table, especially among members with limited credit history or non-traditional financial backgrounds. The challenge is finding the sweet spot where growth is steady, risk is contained, and members feel supported.

Recent advances in automation and artificial intelligence (AI) are helping credit unions walk this line with greater confidence. These tools can analyze far more data faster than human underwriters working alone, while standardizing decision-making for consistent results.

Automation is not a substitute for sound judgment—it’s a tool that equips lending teams with deeper insights and faster workflows, so they can make smarter, more informed decisions.

Expanding Approval Without Losing Control

Traditionally, thin-file applicants with limited credit history presented a dilemma. Their lack of a robust score made it challenging to approve them without assuming more uncertainty. However, automation and AI now enable lenders to incorporate alternative data points into credit decisions, such as income stability, employment history, rent payment patterns and transaction behavior.

This expanded view allows credit unions to identify members who may be strong credit candidates despite having limited traditional credit data. The result can be more approvals without blindly increasing exposure. By building custom scorecards that weigh alternative data alongside bureau scores, credit unions can better segment applicants and adjust pricing or terms accordingly.

Using AI to See the Full Picture

AI is transforming how credit unions evaluate member risk and opportunity. By synthesizing data from multiple sources—such as account activity, cash flow patterns, and repayment behavior—AI builds a more complete financial profile than a credit report alone can offer. It reveals not just where a member stands today, but how their financial habits are trending over time.

For example, rather than flagging a member as “high risk” based solely on a low score, an AI model might detect that their monthly savings rate is increasing, their debt-to-income ratio is shrinking, and account balances are stable. These patterns could support more favorable lending decisions that align with the credit union’s risk appetite.

The benefit isn’t just in more approvals; it’s in making smarter approvals. With AI, credit unions can expand access to credit by staying true to their mission of supporting members’ financial well-being.

Automation as a Back-Office Ally

Some of the most impactful uses of automation happen behind the scenes. While members may never see it in action, automation accelerates loan processing, enforces policy consistency, and supports compliance—without slowing the experience.

For credit unions, automation can: 

• Instantly flag applications that meet pre-set approval conditions, sending them straight through for funding.
• Identify applications requiring further review based on risk factors, enabling underwriters to focus only on those that need human judgment.
• Perform real-time fraud checks on application data, comparing it against known patterns of fraudulent activity.

These capabilities allow teams to focus on strategic decisions rather than repetitive manual tasks, shortening turnaround times, and improving member satisfaction.

Strengthening Fraud Detection Without Adding Friction

Fraud detection is another area where AI and automation excel. Unlike traditional systems that rely on static rules, modern AI models continuously learn from emerging fraud patterns and adapt in real time.

For instance, AI can recognize subtle anomalies in application data or transaction behavior that a rule-based system might overlook. This could include sudden shifts in spending habits, inconsistencies in reported income versus observed deposits, or unusual IP address patterns during online applications.

Importantly, these fraud checks can happen behind the scenes, without forcing members to endure excessive verification steps. By reducing false positives, credit unions can protect themselves and preserve a smooth application process.

Real-world Practices for Balancing Growth and Risk

Credit unions that successfully balance growth with risk often follow a few key practices:

1. Establish clear risk parameters. Define the level of risk the credit union is willing to take, then configure automated systems to reflect those thresholds. This keeps growth aligned with strategic goals.
2. Layer automation with human oversight. Automation excels at processing and flagging, but human expertise remains essential for complex cases or exceptions.
3. Continuously refine models. Data-driven decisioning tools are not “set it and forget it.” Regularly review approval outcomes and adjust scoring models to reflect actual performance.
4. Integrate fraud detection early. Building fraud checks into the earliest stages of application review prevents wasted time on fraudulent files and reduces funding risks.
5. Use automation to enhance member relationships. Speed and efficiency matter but so does trust. Automation should empower staff to focus on member conversations rather than paperwork.

Looking Ahead

As lending technology evolves, the most successful credit unions will embrace automation as a strategic partner rather than a threat to traditional values. AI can help identify opportunities in overlooked markets, speed up decision-making, and strengthen fraud defenses, all while keeping member service at the forefront.

Balancing growth and automation against risk is not about choosing one over the other. It’s about using technology to see more clearly, act more quickly, and serve more fairly, ensuring credit unions can grow sustainably while staying true to their mission.

Sean Ferguson is the vice president of product strategy for direct lending and account opening at Origence and focuses on transforming technology solutions to create exceptional user experiences.