Familiar pressures, new AI territory for financial institutions
Key topics covered in this post:
AI
AML/CFT
Asset/Liability
Data & Analytics
Fraud Prevention
Lending & Credit Risk
Portfolio Risk & CECL
Bolder banking: From AI experiments to execution
May 8, 2026
0 min read
Supporting better decisions with AI
Financial institutions are digging deeper into artificial intelligence (AI) at a time when familiar pressures are intensifying: loan and deposit growth, efficiency, fraud, cybersecurity, credit quality, staffing constraints, and rising customer expectations. Boards and regulators are asking questions, too, pushing AI planning, governance, and accountability to the forefront.
That shift from experimentation to execution was a central theme at Abrigo’s recent ThinkBIG conference, where presenters discussed how banks and credit unions can use AI to support better decisions without losing the required oversight. Speakers emphasized applying AI in the right business context, with the right policies, data, and human involvement.
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Jay Blandford, Abrigo CEO
Abrigo CEO Jay Blandford told nearly 1,200 attendees from banks, credit unions, and conference sponsors that AI can help institutions scale insights while creating more opportunities to strengthen relationships, a core advantage for banks and credit unions that compete on local knowledge and service.
“Relationships scale trust, and that’s your real competitive moat,” he said.
Execution begins with useful work
Several speakers suggested focusing AI execution first on practical work: specific tasks that can be defined, reviewed, and improved. Using artificial intelligence doesn’t have to put the bank or credit union at unnecessary risk, and it doesn’t have to solve everything or the institution’s biggest problem to start.
“The goal isn’t to get AI perfect; it’s to start building the capability,” said Andy Snow, Abrigo’s Chief Customer Officer. “Waiting is a decision. It is not free.”
For many institutions, that means starting with a narrowly defined workflow, identifying where staff review is required, documenting how outputs will be checked, and measuring whether the tool improves speed, consistency, or capacity before expanding the use case.
Responsible action starts by using AI where risk is lower and value is clear. In fact, a good approach is to begin by identifying repetitive tasks that can be reviewed and controlled, or work that is costly, slow, or overly manual. That’s often the work where AI can improve consistency and give employees more time for judgment-based work.
Applying AI to work that is repeatable, time-consuming, and well understood will help institutions build confidence and further focus their AI efforts.
Melissa Marsal, right, and John Brichetto, left, at Abrigo's ThinkBIG conference on May 5, 2026
Melissa Marsal, a former community bank CEO and COO and now a community bank advisor, said the clearest AI opportunities for many will be tied to operational efficiency in processes governed by rules or defined workflows. She pointed to exception-item processing, document management, training procedures, and anti-money laundering/countering the financing of terrorism (AML/CFT) alert triage as examples of areas where institutions are engaging.
Tackling those areas can reduce the time talented staff spend on repetitive back-office tasks, giving them more capacity to interact with customers, review exceptions, or support higher-value work, she said.
“At the institutions that I’ve seen that have leaned into it, it’s working well,” Marsal said.
AI’s value depends on data, automation, and context
For financial institutions, it’s vital that AI be purpose-built for specific tasks, said Abrigo Chief Technology and Product Officer Ravi Nemalikanti.
Financial institutions face a convergence of technology-driven forces that can feel overwhelming, he said. “On one end, we have the speed of intelligence changing, driven by AI. On the other, changes in money movement are driving faster expectations for the speed of execution.”
General AI can provide generic answers and lacks a true understanding of specific business contexts. But Nemalikanti described how purpose-built agentic AI can understand the context, necessary details, and wider business process of an operating framework. Integrated into systems like loan origination, it can better understand data within the workflow to craft appropriate, specific responses at the right time and automate credit origination steps. “This is where we move from answers to action,” he said.
As work moves through end-to-end workflows, the AI begins to coordinate steps. Use cases could include reviewing credit prescreening results, collecting documents, and setting up ticklers.
The technology becomes more useful because it operates within the institution’s operating framework, helping teams act with better information, more consistent processes, and the oversight the banking industry requires.
“These are deployed into your environment to understand your data sets, your workflows, and most importantly, your policies,” Blandford said.
Governance and trust are adoption requirements
Just as financial institutions vary their initial AI use by risk, banks and credit unions should ensure that the governance and autonomy granted to AI actions align with their policies, risk appetite, documentation requirements, and regulatory expectations.
Governance was a recurring theme across the sessions. Snow said leaning into AI will be easier by working with “the right partner, someone you trust that understands your business and is not going to put you into a reckless situation.”
That guidance is especially important in financial services. AI tools need to fit into data privacy expectations, policy controls, auditability, and governance.
Employees also need enough education to understand where AI can help, where it needs review, and where human judgment remains essential, especially in banking.
Speakers consistently positioned AI as a way to support people rather than displace the value of banker judgment.
“There are some amazing things happening with AI,” said Brad Schaefer, Abrigo Vice President, Product. “But we feel the human interaction and touch and judgment is going to be the driving factor to make that productive.”
Ultimately, the speakers framed AI as a way to give financial institution staff more time and better information for the relationship-centered work that sets community institutions apart. “Relationships are what build trust, and trust is the foundation for how you differentiate yourself,” Blandford said.
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