RDC.AI Expands North American Footprint with Agentic AI for Commercial Banking

RDC.AI has reported a 120% growth rate within its existing customer base over the last year as it accelerates its expansion into the North American commercial banking market. For fintech leaders, this move signals a shift from experimental AI pilots toward production-scale agentic intelligence that prioritizes regulatory governance and explainable risk management.

What was announced

RDC.AI, an Australian-founded fintech specializing in predictive intelligence for business and commercial banks, is scaling its operations across Australia, New Zealand, and North America. The company’s platform uses agentic AI to provide portfolio oversight, identifying early credit-risk signals up to six months sooner than traditional monitoring methods. This deployment has reportedly resulted in a 70% reduction in manual effort for banks compared to conventional monitoring processes.

The firm is currently targeting the North American market, which contains the world’s largest concentration of business and commercial banks, with over 4,500 regulated banking institutions across the US and Canada. RDC.AI is investing in a US-based commercial team and is in final-stage discussions with several banks across the region. This expansion builds on the company's existing work with top-six US commercial bank M&T Bank, where it has embedded intelligence into daily workflows for bankers.

Central to this expansion is a new "collaborative agentic workspace," currently in product preview with two customers. This workspace allows bankers to work alongside governed AI agents to interrogate portfolios and make complex decisions using the bank’s own curated data and policies. The company’s growth is supported by a partner ecosystem that includes AWS, Snowflake, and Anthropic. RDC.AI’s platform is designed to move beyond the "black box" nature of some AI models by ensuring every decision is explainable and compliant with the strict governance requirements of regulated financial institutions. The company has achieved more than 120 per cent growth within its existing customers over the past 12 months, reflecting a broader adoption of its platform as banks move from experimentation to large-scale deployment.

"Imagine this as the place where bank leaders and frontline teams can now ask questions and interrogate the portfolio in ways they have never been able to before, again underpinned by explainability. The banker makes the decision and sets the task, then the agents do the work safely and transparently on the bank's own curated data, policy and knowledge. It’s very exciting to see real value by placing agentic AI directly in the hands of bankers, at the governance level required by regulated banks."

Ada Guan, CEO and co-founder of RDC.AI.

The companies involved

RDC.AI is a Sydney-based technology provider that has spent a decade developing AI solutions specifically for the regulated banking sector. Founded in Australia, the company has built a reputation for delivering "explainable" AI, a critical requirement for institutions that must justify credit and risk decisions to regulators. The company is backed by institutional investors including Westpac and Acorn Capital. Its primary focus is on business and commercial banking, a sector characterized by complex, high-value decision-making that requires higher levels of transparency than retail banking.

Westpac, one of Australia’s "Big Four" banks, serves as both a strategic investor and a key customer, utilizing RDC.AI’s intelligence platform to manage its commercial portfolios. In the United States, RDC.AI has established a significant footprint through its work with M&T Bank, a top-six US commercial bank. M&T Bank has used the platform to embed predictive intelligence into the daily workflows of its bankers, moving the technology from the laboratory into active production. This regional presence is a cornerstone of RDC.AI’s strategy to capture a larger share of the 3,800 commercial banks operating in the US market. The company’s focus on North America follows its success in the Australian and New Zealand markets, where it has worked with major banks to realize measurable business outcomes through automation and predictive intelligence.

What this means

The transition of AI from "innovation lab" curiosity to "agentic" production tool marks a turning point for commercial banking. While retail banking has long used automated scoring for small-scale loans, the commercial sector has been slower to adopt AI due to the complexity of the data and the need for explainability in high-stakes credit decisions. RDC.AI’s growth suggests that the industry is moving toward a "human-in-the-loop" model where AI agents handle the data-heavy lifting while bankers retain final decision-making authority. This puts pressure on traditional risk management software providers who lack native AI capabilities, as banks increasingly demand tools that offer predictive foresight rather than just retrospective reporting. The challenge for the sector will be maintaining this level of "explainability" as the underlying models become more complex, a factor that will likely determine which AI providers win long-term contracts with Tier-1 institutions.