Valley Bank is utilizing its relationships across the finance and technology industries to find the best AI applications to improve its efficiency.
The $64.5 billion bank continues to roll out AI tools for customer-facing applications and internal processes such as underwriting, sales and fraud detection, Valley Bank executives said on today’s second-quarter earnings call.
“Valley Bank has several structural advantages that support our AI strategy, including Valley Ventures, our international and technology banking business, and our relationship with Bank Leumi,” Chief Executive Ira Robbins said on the call.
Valley Ventures, the bank’s venture capital arm, gives Valley “direct exposure to the startup ecosystem and access to emerging talent and technologies,” Robbins said.
The $235 billion Bank Leumi, based in Tel Aviv, Israel, also gives Valley Bank “additional visibility into leading practices in cyber, fraud and risk management,” Robbins said.
Valley Bank acquired Bank Leumi’s U.S. arm in a $1.2 billion deal in 2022. Bank Leumi holds a minority ownership stake in Valley Bank, reported at about 14% in 2022 by the SEC.
“We have a robust team of AI practitioners focused on sourcing use cases and aligning solutions from these relationships,” Robbins said.
Increased efficiency
AI implementation is a critical component for increasing efficiency in banking, Robbins said.
“From a macro perspective, we believe that banks effectively adopting AI have the potential to structurally shift their efficiency ratios lower by around 500 basis points,” Robbins said.
Valley Bank reported a Q2 efficiency ratio of 52.1%, improved from 55.2% in Q2 2025. The bank expects its efficiency ratio to be 50% or lower heading into next year, Chief Financial Officer Travis Lan said on the call.
Valley Bank has spent $3 million to $4 million this year on AI against $15 million in expense run rate savings, Lan said.
According to today’s earnings presentation, Valley Bank is using:
- Generative AI to support customer care agents in accessing policies and procedures;
- Machine-learning models to improve anti-money laundering and fraud alert efforts;
- An autonomous outbound voice agent for auto loan payment reminders and collections;
- AI-driven lead targeting and customer insights consolidation; and
- Agentic AI to automate parts of credit underwriting and loan servicing.
“Like with most AI use cases, the manual work can be automated, but it doesn’t change the oversight and approval and governance that’s around those AI efforts,” Lan said.
“It’s not occurring in a vacuum with no human oversight. It’s just shifting the roles and responsibilities.”
BY THE NUMBERS: The Morristown, N.J.-based bank reported in Q2:
- Net income of $170.9 million, up 28.3% year over year;
- Revenue of $560.7 million, up 13.3% YoY; and
- Technology, furniture and equipment expense of $33.2 million, up 8.4% YoY.
Shares of Valley Bank (NASDAQ: VLY) were down 1.07% from market open to $14.37 at 3:30 p.m. ET today. The bank has a market capitalization of $8 billion.
Register here for the FinAi Lending Summit, set for Oct. 7-8 in Las Vegas.
Facts Only
* Valley Bank utilizes relationships across the finance and technology industries for AI applications.
* The bank is rolling out AI tools for customer-facing applications and internal processes like underwriting, sales, and fraud detection.
* Chief Executive Ira Robbins cited Valley Ventures, international/technology banking business, and the relationship with Bank Leumi as structural advantages for the AI strategy.
* Valley Ventures provides exposure to the startup ecosystem and access to talent/technologies.
* Bank Leumi provides visibility into leading practices in cyber, fraud, and risk management.
* Valley Bank acquired Bank Leumi’s U.S. arm in a $1.2 billion deal in 2022.
* Bank Leumi holds approximately 14% ownership in Valley Bank in 2022.
* The bank spent $3 million to $4 million on AI this year against $15 million in expense run rate savings.
* Q2 efficiency ratio for Valley Bank was 52.1%.
* Net income for Q2 was $170.9 million, up 28.3% year over year.
* Revenue for Q2 was $560.7 million, up 13.3% year over year.
* Technology, furniture and equipment expense was $33.2 million, up 8.4% year over year.
Executive Summary
Full Take
The narrative centers on embedding external strategic relationships into an AI implementation strategy to drive efficiency gains in a large financial institution. The framing positions partnerships with entities like Valley Ventures and Bank Leumi not merely as operational sources but as fundamental structural advantages enabling access to specialized knowledge and talent necessary for advanced AI deployment. This suggests that competitive advantage is being sought by synthesizing diverse expertise rather than developing capabilities internally alone.
The assertion that adopting AI can structurally shift efficiency ratios by 500 basis points sets a high, almost aspirational, benchmark against which the bank measures its progress. The reported efficiency ratio improvement from 55.2% to 52.1% indicates tangible operational movement, yet the overall financial performance metrics are also presented, which tests whether these efficiency gains translate directly into broader profitability or market confidence for shareholders.
The distinction drawn regarding AI implementation—where automation shifts roles and responsibilities without eliminating oversight—is a crucial point of tension. It reframes AI adoption from a purely cost-cutting exercise to a systemic change in organizational governance. The pattern suggests that the discussion is deliberately balancing technological optimism with institutional reality; the deployment of Agentic AI for underwriting, for instance, signals a shift in workflow responsibility, which must be managed carefully alongside established governance structures.
What are the unstated assumptions about the sustainability of these external relationships? Does relying on external visibility introduce new dependencies or potential points of failure concerning data integrity or proprietary knowledge? Furthermore, if efficiency gains are pursued through externally sourced AI expertise, who ultimately captures the long-term value created by these applied technologies, and how is governance scaled across these diverse external inputs?
Sentinel — Human
The text exhibits characteristics consistent with professional financial journalism, grounded in specific company statements and data, suggesting a high likelihood of human authorship.