Automation Can Combat ‘Brain Fade’ in Finance

Employee Errors Cost Financial Institutions Dearly

Small employee mistakes can have massive consequences for financial institutions, which spend $5.75 for every $1 lost to error or fraud — including labor, legal and churn costs, according to a recent LexisNexis report.

Failed payments cost banks an average of $360,000 in labor and fees in 2020, per another LexisNexis report.

“Beyond the financial loss, these issues can significantly erode customer trust,” Haynes says. “But the bigger problem is that every hour teams spend cleaning up manual mistakes or responding to added regulatory scrutiny is time they aren’t spending on the strategic work that helps grow the business.”

Automation and artificial intelligence agents handling repetitive, error-prone tasks help financial institutions shift from reactively fixing issues to proactively addressing them, but first they must overcome hurdles to adoption.

WATCH: Artificial intelligence will drive efficiency for financial institutions in 2026.

Barriers To Automating Finance Workloads

In addition to security and integration issues, IT leaders find generic AI models “compliance blind,” meaning they fail to understand the difference between casual conversations and regulated financial advisory sessions. The resulting inconsistencies create risk for financial institutions, which is one reason why only 5% of AI projects go live, according to a recent Massachusetts Institute of Technology Networked Agents and Decentralized Architecture report.

“In finance, you wouldn't hire an untrained, unlicensed generalist to manage wealth,” Haynes says. “The same logic applies to digital labor.”

As a result, finance firms are increasingly adopting AI agents — autonomous AI systems capable of carrying out their own tasks — trained on industry-specific data models such as Agentforce for Financial Services. The solution is built to operate with the context, controls and guardrails needed to reduce errors and maintain compliance in highly regulated environments, Haynes says.

Click the banner below to keep reading stories from our new publication, BizTech: Financial Services.

Where Financial Institutions Can Begin to Incorporate Automation

While people will always be central to financial services work, automation and now AI reduce their “busy work” so they can focus on high-value interactions, Haynes says.

Salesforce found that finance professionals suffering from burnout lead to more errors, higher turnover and lower customer satisfaction. When professionals incorporated AI into their work, 89% — a significant majority — said the technology increased self-service resolution, according to the study.

Institutions just starting out with automation should identify high-volume, low-complexity tasks with clear, measurable ROI. Prospecting and lead conversion, deflecting inbound calls to a contact center, data entry or document processing are good options, Haynes says.

“It’s equally important to choose the right partner for your AI journey, especially a partner with a successful playbook of similar companies in your vertical,” Haynes says. “To maximize value, look for a partner with a solution built on a trusted enterprise platform that can scale with your business and integrate easily with other systems and partners.”