Q2 Eyes Personal AI Agents as Banking’s Next Channel—and Fraud Frontier

Key Points

• Personal AI agents may become banking’s next customer channel. Q2 is enabling connections through MCP endpoints while emphasizing that banks need control over permissions, security, branding and compliance.
• AI is expanding both fraud risks and detection capabilities. Q2 says attackers can use AI for deepfakes and social engineering, while its UAM account-takeover product uses digital-banking and external signals to identify threats, including those originating through AI-agent interfaces.
• Q2 Assistant and UAM are nearing general availability. Both products remain in early access but are expected to launch broadly before year-end, with Q2 reporting faster deployments and growing customer interest in its AI tools.

Q2 NYSE: QTWO executives said artificial intelligence is creating new opportunities and risks for digital banking, with personal AI agents emerging as another channel through which consumers and businesses may interact with financial institutions.

During the company’s second investor-focused AI discussion, Chief Operating Officer Hima Mukkamala described personal agents as “the next banking channel,” following branches, online banking and mobile applications. She said Q2 expects agent-based interactions to serve as a new entry point rather than replace banks’ digital-banking or fraud platforms.

Mukkamala said financial institutions could keep AI experiences within channels they control, such as websites, or support connections through outside services, messaging apps, smart devices and cloud-based AI tools. Q2 is exposing Model Context Protocol, or MCP, endpoints across much of its digital-banking stack, she said, allowing personal agents to connect through a new form of API integration.

However, Mukkamala said banks will need controls over security, permissions, policies and branding as agentic channels develop. “The digital banking platform is in the middle,” she said, citing its role in providing context, integrations, orchestration, data and controls.

Agentic Banking Could Broaden Bank Differentiation

Chief Technology Officer Adam Blue said external AI agents could expand, rather than commoditize, banks’ digital experiences. He said the agentic channel provides a wider surface for institutions to express their brand, capabilities and personalization than prior channels such as web, mobile, SMS, wearables and open-banking interfaces.

Blue acknowledged that some financial institutions may initially decline to support connections from external agents because of the associated risk. But he compared the development to the growth of account aggregation over the past two decades, arguing that customer demand for connectivity could influence banks’ eventual decisions.

“I think this is a for now kind of decision and not a long-term decision,” Blue said of banks that restrict agentic access. He added that Q2 would support customers that choose not to enable such connections while they develop a technology and risk-management strategy.

Mukkamala said adoption will depend on banks gaining confidence in areas including observability, auditability, controls, containment and incident disclosure. She said customers are already using agent-related services through relatively limited aggregation experiences and may seek richer capabilities as platform providers enhance their technology.

AI Raises Fraud and Security Demands

Blue said AI is strengthening both fraud attackers and defenders. Attackers can use the technology to create more sophisticated exploits, deepfakes and social-engineering schemes, while financial institutions and technology providers can use AI to identify and mitigate threats more quickly.

He said Q2’s position in the digital-banking workflow gives it access to data and operational context that standalone cybersecurity providers or core providers may not have. That includes user behavior within applications, across applications and across the broader financial ecosystem, according to Blue.

Mukkamala said fraud is one of Q2’s fastest-growing product lines. She highlighted the company’s UAM account-takeover product, which uses signals from digital-banking systems and outside sources to identify potential fraud. Q2 added a detector for agentic interfaces after customers reported fraud originating through that channel, she said.

As more channels become available, fraudsters gain a larger potential attack surface, Mukkamala said. She added that personal agents can create substantially more signals as they use sandboxes or virtual machines to interact with financial institutions.

Blue also emphasized the importance of cybersecurity operations and rapid patching as new vulnerabilities emerge. He said Q2 maintains teams focused on identifying, mitigating and preventing recurring risks, and is using AI to evaluate systems and improve its software-development lifecycle.

The company recently completed an AIUC-1 assessment for its Q2 Assistant product through an independent auditor, Blue said. He described the review as part of what could become a broader set of standards for AI assistant safety, quality and controls.

Early-Access Products Near General Availability

Mukkamala said Q2 Assistant and UAM are the company’s most advanced AI offerings. Q2 Assistant is designed to help financial institutions automate customer-care and back-office tasks, including entitlement changes and password resets. She said workflows that once could take an hour or longer can be completed in less than a minute using the product.

UAM monitors signals from Q2’s digital-banking environment and external detectors to identify account-takeover activity, she said. Both products are in early access and are approaching general availability before year-end, according to Mukkamala.

She said Q2 has seen customers move from early adoption toward broader use of AI products, with some deployments occurring in weeks rather than the quarters typically required for traditional software rollouts. Blue said AI-supported development tools have also shortened the feedback loop between customer conversations, prototypes and product iterations.

Executives Cite Platform, Integration Experience

When asked about competition from startups and frontier AI models, Mukkamala said a frontier model alone is not a banking product. She said Q2’s differentiation includes its integration layer, orchestration, contextual data, extensibility and controls developed over two decades of serving financial institutions.

Blue similarly said customer intimacy and domain expertise are as important as writing software code. He said AI can make development faster, but companies still need to manage complex financial-services integrations, security requirements and operational workflows.

Mukkamala rejected the idea that Q2’s history necessarily implies outdated technology, pointing to the company’s ability to bring new products to customers quickly, expose APIs and MCP endpoints, and operate an active-active cloud architecture. Blue said architecture should be evaluated through reliability, resilience and how systems respond to operational failures, rather than by a list of technology-stack terms.

Both executives said they view AI as an accelerant for Q2, while identifying inaction as the principal risk. Blue said the technology can help the company analyze customer data, test ideas more rapidly and develop solutions faster. Mukkamala said customer interest in adopting AI through Q2 has increased over the past six months.

About Q2 (NYSE:QTWO)

Q2 Holdings, Inc is a financial technology company that provides cloud-based software to banks, credit unions and other financial institutions. Its platform is designed to help these organizations deliver digital banking experiences, manage customer relationships and expand access to financial services through online and mobile channels.

The company's products and services include digital banking, account opening, lending and loan origination, payments, data and analytics, financial crime prevention, and tools for managing customer engagement.

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