RDC.AI targets North America with banking software

RDC.AI is sharpening its focus on North America as it expands its banking software business. The Australian-founded company said growth within existing customers rose by more than 120 per cent over the past year.

The increase came as banks in Australia, New Zealand and North America expanded their use of its tools for customer analysis, portfolio oversight and decision support. RDC.AI counts Westpac and M&T Bank among its customers and said it is in final-stage discussions with banks in the United States and Canada.

North America is a key target because of the scale of its banking market. RDC.AI cited more than 4,500 regulated banking institutions across the US and Canada, including about 3,800 commercial banks in the US.

Backed by investors including Westpac and Acorn Capital, the business has been building its presence in the region while expanding its US commercial team. Over the past decade, it has developed software for business and commercial banks, a segment where lenders manage broad portfolios of corporate customers and face close regulatory scrutiny.

Banking push

Its platform is designed to help bankers identify changes in customer conditions and portfolio trends earlier, with the aim of improving oversight and reducing manual work. In one deployment with M&T Bank, RDC.AI said early credit-risk signals were identified up to six months earlier, while manual effort fell by 70 per cent compared with conventional monitoring.

The deployment underpins the company's argument that lenders are moving beyond limited artificial intelligence trials and into broader operational use. Banks have spent the past two years testing generative AI and automation in narrow settings, but many have moved cautiously because of concerns about governance, explainability and regulatory compliance.

RDC.AI argues those constraints can be addressed within banking workflows rather than around them. Its software is designed to let bankers query portfolios, assess risks and opportunities, and use automated systems while keeping human decision-makers in control.

Ada Guan, Chief Executive Officer and Co-Founder of RDC.AI, said the company's recent customer growth reflected broader changes in the banking sector.

"As RDC.AI marks its tenth year, we're seeing growing validation of the approach we've taken from day one - building AI specifically for regulated financial institutions, with explainability, governance and safety at its core. Today, banks are moving beyond experimentation and looking for proven solutions that deliver measurable business outcomes coupled with regulatory confidence. This is reflected in the growth we're seeing across our customers, where banks are broadening the adoption of our platform," Guan said.

Agentic tools

The company is also testing a new collaborative workspace with two customers. RDC.AI described it as a setting where bankers and software agents work together on tasks linked to complex lending and portfolio decisions.

Guan described that work in a second comment. "We continue to push the envelope with agentic AI for regulated banks, and we are currently in product preview with two customers for our new collaborative agentic workspace. This is the place where bankers and governed agents work together on complex, high-value decisions typical of what we see in business and commercial banking.

"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," Guan said.

RDC.AI also said it works with AWS, Snowflake and Anthropic through partner programmes, reflecting how specialist banking software groups are increasingly building on larger cloud and AI infrastructure providers. For regional and mid-sized lenders in particular, such partnerships can shape how quickly new systems move from pilot projects to broader deployment.

According to its corporate background, the company's customer list also includes BNZ. Its products span early warning systems, review and renewal recommendations, portfolio insights and merchant lending, all aimed at business and commercial banking teams.

For banks, the commercial appeal of such software lies in handling large volumes of customer and portfolio data more consistently, especially as credit conditions shift. For providers such as RDC.AI, the challenge is proving that AI can fit into tightly controlled banking environments without weakening oversight.

In one of its clearest operating metrics, RDC.AI said its work with M&T Bank surfaced early credit-risk signals up to six months earlier and cut manual effort by 70 per cent compared with conventional monitoring.