The FCC’s proposal aims to increase transparency in AI-powered communications. If implemented, these rules would require upfront disclosure of AI use in automated calls and messages, potentially altering how businesses interact with consumers.

“The FCC rules, if adopted, may require businesses that use automated voice and text communications to make adjustments to their processes, as well as investments in technology and training to ensure compliance,” Trevor Francis, CEO at voice connectivity company 46 Labs, told PYMNTS. “They may need to revise scripts, rethink their use of automation, or implement alternative ways of communicating with their customers.”

Compliance Challenges and Opportunities

The proposal, detailed in Notice FCC 24-84, would require callers to inform consumers when AI is employed in communications. This move aims to equip the public with tools to identify and avoid potentially fraudulent or scam-related calls, according to the FCC. The FCC has issued a notice seeking public comments on its proposed rules and ideas for alerting consumers to AI-generated spam calls and texts.

Instructions for commenting on FCC proposals can be found online. 

Robocalls have long been a nuisance for consumers and a challenge for regulators. In 2022, Americans received nearly 50 billion robocalls, according to YouMail, a company that tracks and blocks such calls. 

These automated communications range from legitimate business reminders to fraudulent scams, costing consumers billions annually. Previous FCC efforts to combat robocalls have included implementing STIR/SHAKEN protocols to authenticate caller IDs and imposing fines on violators. However, as technology advances, so do the tactics of bad actors. 

The rise of AI-generated voices has added complexity to the issue, enabling more convincing impersonations and potentially more effective scams, underscoring the need for updated regulations.

The proposal includes mandatory disclosure of AI use at the start of calls, subject to consumer consent, provisions to protect AI applications that assist consumers with disabilities, and improvements to the FCC’s robocall mitigation database. These measures could impact industries relying on automated communication systems, including marketing, customer service and political campaigning.

However, Francis sees potential benefits: “Swift adoption of the proposed FCC rules could favorably impact a business’s reputation and help establish a level of trust with their customers.

“Voice is historically the most trusted and regulated form of communication available, but the abundance of robocalls and scams consumers receive on a daily basis make many reluctant to answer their phones anymore. Consumers appreciate transparency, and businesses that embrace these changes could see a positive gain in customer satisfaction, trust and loyalty.”

Business Opportunities

The new regulations could also reshape the competitive landscape for AI communication services. Francis noted, “These changes create an opportunity for businesses offering AI communication services to differentiate themselves from their competitors by offering more innovative and personalized solutions that prioritize transparency and privacy while facilitating compliance.”

As AI technology evolves, these regulations attempt to balance innovation with consumer protection. Businesses must navigate these new requirements carefully, potentially leading to more transparent and ethical use of AI in customer communications.

The FCC now seeks public comment on the proposed rules, inviting input from businesses, consumers and other stakeholders before finalizing the regulations. While compliance may present challenges, it also offers opportunities for companies to build trust and loyalty in an AI-driven communication landscape.

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In am Aug. 12 comment letter to Treasury Secretary Janet Yellen, the CFPB outlined its approach to regulating AI and other emerging technologies in the financial sector. The agency emphasized that innovation must not come at the expense of consumer protection or fair competition.

“Although institutions sometimes behave as if there are exceptions to the federal consumer financial protection laws for new technologies, that is not the case,” the CFPB stated in its letter. “Regulators have a legal mandate to ensure that existing rules are enforced with respect to all technologies, including those marketed as new or novel.”

The agency’s position comes as financial institutions increasingly adopt AI and machine learning technologies for everything from customer service to fraud detection and credit underwriting. While these technologies promise increased efficiency and potentially better outcomes for consumers, they also raise concerns about fairness, transparency and compliance with existing regulations.

CFPB General Counsel Seth Frotman and Chief Technologist Erie Meyer, who co-signed the letter, said that the agency is closely monitoring the adoption of these technologies.

“If firms cannot manage using a new technology in a lawful way, then they should not use the technology,” they wrote.

CFPB Concerns

The CFPB highlighted several areas of concern, including automated customer service, fraud screening and lending and underwriting decisions. The agency warned that AI-powered customer service tools may provide incorrect information, fail to provide meaningful dispute resolution, and raise privacy and security risks.

Regarding fraud screening, the CFPB cautioned that such activities conducted as part of a transaction for a consumer financial product or service must comply with relevant laws, including the Consumer Financial Protection Act and, in some cases, the Equal Credit Opportunity Act.

For lending and underwriting decisions, the agency emphasized that the Equal Credit Opportunity Act applies regardless of the complexity of the technology used, “including when it comes to combatting unlawful discrimination or explaining how certain credit decisions are made.”

The CFPB’s approach marks a departure from previous efforts to encourage innovation through regulatory “sandboxes” and No Action Letters. The agency found that these programs “fell short of their intended purpose of encouraging pro-consumer innovation in financial markets” and sometimes resulted in waiving important consumer protections.

Instead, the CFPB is turning its focus to creating a level playing field for all market participants.

“Innovation is fostered when regulators ensure that all market participants adhere to the same set of rules and compete on a level playing field,” the letter stated.

To achieve this goal, the agency outlined several initiatives, including providing clear guidance on applying existing laws to new technologies, ensuring regulations don’t stifle competition or favor incumbents, combating anticompetitive practices and proposing rules to make it easier for consumers to switch financial service providers.

AI in Finance Draws Global Scrutiny

The CFPB’s stance aligns with a growing trend among regulators worldwide to scrutinize the use of AI in financial services. In Europe, the AI Act imposes strict rules on the use of AI systems in various sectors, including finance.

As part of its oversight efforts, the CFPB is taking steps to evaluate how companies are testing the algorithms they use to make lending decisions to ensure compliance with the law, including the prohibition against discrimination based on protected characteristics. The agency is also closely tracking how tech firms are expanding into banking-like services in virtual worlds and monitoring the potential misuse of generative AI tools for fraud.

Additionally, the CFPB has proposed to subject large technology companies that offer services like digital wallets and payment apps to its supervisory process, aligning oversight of their offering of consumer financial products or services with that of banks and other financial institutions.

As AI continues to reshape the financial services landscape, the CFPB’s position signals that regulators are determined to keep pace with technological change. The agency concluded its letter by emphasizing that “artificial intelligence” is just one aspect of the rapid adoption of new technologies in the consumer financial marketplace, accompanied by new risks and challenges that the CFPB is keenly focused on.

With this clear statement of intent, financial institutions and FinTech companies alike must carefully navigate the regulatory landscape as they seek to harness the power of AI and other emerging technologies. The CFPB’s approach means that innovation in financial services will be expected to occur within the bounds of existing consumer protection laws, with no special exemptions for new technologies.

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While companies explore humanoid robots for tasks from assembly to customer service, opinions vary widely on their adoption rate and implications. The consensus among experts leans toward gradual integration rather than rapid revolution, with key challenges in technology development, workforce adaptation, and customer acceptance still to be overcome.

“As Henry Ford said, ‘Why is it that I always get a whole person when all I want is a pair of hands?’ This sentiment applies here too,” Ding Zhao, associate professor of mechanical engineering at Carnegie Mellon University, told PYMNTS. This skepticism highlights the ongoing debate about the most effective forms of automation in various industries.

Current State of Robotics

Robotics have been a staple in industrial manufacturing for decades, with a complex impact on employment. Mica Endsley, government relations chair at the Human Factors and Ergonomics Society, told PYMNTS, “They tend to create both higher-skilled, higher-waged jobs, as well as some lower-skilled, lower-wage jobs.” This nuanced view provides context for the current wave of interest in more advanced, AI-driven robots.

Recent trials, like BMW’s test of the “Figure 02” robot in chassis assembly, showcase the current capabilities of humanoid robots. In a news release, Milan Nedeljković, BMW’s board member for production, said, “With an early test operation, we are now determining possible applications for humanoid robots in production.” This real-world application demonstrates the auto industry’s commitment to exploring automation technologies.

However, the road to widespread adoption may be longer than some anticipate. Andy Williams, EVP of North America at Exotec, told PYMNTS, “The time frame for practical use of humanoid robots in the warehouse is easily five-plus years down the road, giving the workforce time to transition.” This perspective highlights the gap between current capabilities and industry requirements.

Future of Work and Customer Service

As the technology develops, its impact on employment and customer service remains a topic of debate. Maria Kyrarini, assistant professor at Santa Clara University, told PYMNTS, “There is an opportunity for upskilling or reskilling workers, who the robots may displace, to take over new roles in an environment with humanoid robots.”

Opportunities for new roles balance the potential for job displacement. Williams predicted, “New services associated with the support of these robotics include the extension of advertising mediums through humanoids or more comprehensive bundling of services to offset capital costs.”

In customer-facing roles, functionality may trump appearance. Endsley emphasized, “Just like with many systems that companies adopt, such as chatbots or phone-based voice menus if the technology is not capable of addressing customers’ questions and needs, they will become frustrated and go elsewhere.”

Recent research in Japan suggests that even limited robot interactions can influence customer behavior. Kyrarini reported, “A recent study was conducted in Japan about having a service robot in a bakery shop to greet customers and provide product information. The study found no increase in the number of customers visiting the bakery, but the robot recommendations to the customers had an impact.”

Integrating humanoid robots in commerce is expected to alter workplace relationships. Endsley warned, “Now that inter-office communications are largely handled by email, text or video calls, for example, we often see a decrease in the direct interaction and relationship building that would otherwise occur naturally in companies.”

Pat Marsh, principal designer at argodesign and a designer behind the NASA-backed humanoid robot Apollo, sees potential for new business models. 

“Much of our maintenance and care labor is undervalued at least by economic standards,” he told PYMNTS. “I like to think of robots as a possible leverage to our tendencies that are inherent to capitalism and GDP-driven economics, in that robots can do the work we find too expensive for humans to do well.”

Experts agree that the key to successful integration is careful planning and human-centered design. Williams said, “We can draw a parallel between how human workers have learned to accept AI and use it in their daily workplaces and how we can expect the humanoid robotics transition to unfold if done carefully and correctly.”

As the retail and manufacturing sectors continue their robotic explorations, they focus on developing machines that can effectively meet human needs, regardless of how humanlike they appear. Marsh concluded, “People need exposure to robots in ways that reinforce good expectations. They also need patterns of behavior that set clear boundaries.”

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Chain-of-thought (CoT) AI is designed to provide step-by-step explanations of its decision-making process. By revealing the intermediate steps in its reasoning, CoT AI allows researchers and users to better understand how the system arrives at its conclusions. This increased transparency can potentially enhance accountability in AI-driven organizations. ​​​​​​​​​​​​​​​​

New techniques have made language AI better at solving problems by delineating steps. Scientists are exploring if these methods can also make robots smarter. They’ve created a system called “embodied chain-of-thought reasoning” to help AI models analyze their tasks and surroundings before they act.​​​​​​​​​​​​​​​​

The development of CoT AI aligns with a growing emphasis on explainable AI (XAI) in the tech industry and research community. As AI systems are increasingly deployed in critical areas such as healthcare, finance and legal services, the ability to scrutinize and understand AI decision-making processes is crucial.

Proponents of chain-of-thought AI suggest that this approach could accelerate the adoption of AI in fields where interpretability is essential. By providing insight into the AI system’s reasoning, it may become easier to identify and address potential biases or errors.

From ‘What’s 2+2?’ to ‘Why Is the Sky Blue?’

Remember those math teachers who always insisted you show your work? Chain-of-thought AI is that teacher’s dream come true. When asked a question, CoT AI doesn’t just blurt out an answer. Instead, it lays out its reasoning step by step.

Take a classic word problem: “If a train leaves Chicago at 2 p.m. going 60 mph, and another train leaves New York at 4 p.m. going 75 mph, when will they meet?” A traditional AI may crunch the numbers and spit out a time. But a CoT-enabled AI is more like that enthusiastic kid in class who walks you through every calculation, from figuring out the distance between cities to accounting for the time difference.

This isn’t just about impressing math teachers, though. Researchers at Google Brain have shown that this approach can significantly boost AI performance on complex reasoning tasks. Their paper, posted on Arxiv, a non-peer-reviewed journal site, demonstrated that CoT could help AI tackle everything from basic arithmetic to mind-bending logic puzzles.

But chain-of-thought isn’t confined to the realm of textbook problems. It’s making waves in fields where the stakes are much higher than a grade on a math test. For instance, researchers at Stanford University are exploring how CoT can make medical AI systems more transparent. Imagine a future where an AI doesn’t just suggest a diagnosis but explains its reasoning in a way that doctors and patients can understand. “Well, given the patient’s elevated white blood cell count, combined with the localized pain in the lower right abdomen, I’m leaning toward appendicitis. Here’s why …”

AI for Education

CoT could potentially help turn AI tutors from stern taskmasters into patient explainers in education. A study from Carnegie Mellon University showed that CoT-enhanced tutoring systems could significantly improve student learning outcomes in mathematics. It’s like having a tutor who knows all the answers and can break down complex concepts into bite-sized, digestible pieces.

Of course, like any budding technology, chain-of-thought has its growing pains. For one, all this explaining takes a lot of computational power. It’s the difference between asking someone for a quick yes or no versus sitting them down for a TED talk.

Keeping AI’s “thoughts” on track is also challenging. Just as humans can sometimes follow a train of thought right off a cliff, AI can sometimes produce reasoning chains that appear more “stream of consciousness” than “logical deduction.”

Some computer scientists are even pushing the boundaries further. Researchers at DeepMind, for instance, have developed a technique called “Tree of Thoughts,” which allows AI to explore multiple reasoning paths simultaneously. It’s like giving AI the ability to brainstorm with itself.

The rise of chain-of-thought AI is changing how we think about artificial intelligence. This new approach focuses on making AI decision-making clear and understandable.

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The seed funding round, announced last week in a post on the German company’s blog, will help DC Connected Car develop AI diagnostic tools for roadside assistance, warranty and repair.

“AI has the potential to revolutionize various automotive areas that Borusan operates in, such as aftersales, fleets and used car business,” said Timo Kilp, whose Borusan Ventures took part in the funding round. 

“We believe DC Connected’s AI-driven digital technician holds significant promise to accelerate the diagnosis and repair of vehicle issues, further enhancing our customer service.”

According to the blog post, DC Connected Car offers a virtual technician platform aimed at easing a shortage of skilled labor in the automotive industry. 

“Unlike conventional diagnostic systems, their AI-driven solution delivers automated, intelligent insights into vehicle health and performance, providing real-time problem-solution recommendations,” the post said. 

“This approach not only minimizes the need for physical inspections and repairs but also seamlessly integrates into customers’ lives by offering remote support.” 

The funding round comes at a time when AI is unlocking potential across the auto industry, as PYMNTS wrote last month.

“The technology has the capacity to transform the sector across vehicle design, manufacturing and customer experience,” that report said.

“By enabling rapid design iterations, virtual testing and optimization of manufacturing processes, generative AI could significantly reduce time to market. It can also enhance personalization, improve safety features and support the development of autonomous vehicles.”

However, that report added, widespread adoption has its challenges, such as accurately predicting performance metrics and ensuring the manufacturability of AI-generated designs, as well as the need to navigate ethical and regulatory environments around the technology’s data privacy and security concerns. 

AI is also helping transform the experience of buying and selling a car, Steven Silver, managing director, Automotive, Transportation & Mobility for Publicis Sapient and Publicis Groupe, told PYMNTS in an interview earlier this year.

“Currently, numerous companies are exploring AI’s potential to enhance their operations,” Silver said. “Once integrated and scaled, AI is poised to have a profound impact on the mobility industry. However, business leaders must be willing to embrace AI experimentation. It’s important to capture the opportunity now, rather than wait for perfection and mass adoption.”

He told PYMNTS he foresees two ways AI could improve the customer experience: predictive maintenance and in-vehicle personalization, as well as removing friction from the car-buying journey by giving car dealers market behavior data based on buying patterns across a collection of data points.

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This agreement applies to public posts that were made by European Union (EU) and European Economic Area (EEA) users of X and were processed by the company between May 7 and Aug. 1, the DPC said in a Thursday press release.

The processing will be suspended while the DPC and other EU and EEA regulators investigate whether this use of the public posts complies with the General Data Protection Regulation (GDPR), according to the release.

The agreement came as the DPC brought a court case against X focused on its use of the data, and after “extensive engagement” between the DPC and X, per the release.

“One of our main roles as an independent regulator and rights-based organization is to ensure the best outcome for data subjects and today’s developments will help us to continue protecting the rights and freedoms of X users across the EU and EEA,” DPC Commissioner Des Hogan said in the release.

“We will continue to engage with all data controllers to ensure the rights of our citizens under the EU Charter of Fundamental Rights and the GDPR are upheld.”

A lawyer for X told the Irish court hearing the case brought by the DPC that the company would stop using the data until the court makes a decision in the case, Reuters reported Thursday.

A judge had determined that X began processing EU users’ data to train AI systems on May 7 but didn’t begin rolling out the option for users to opt out until July 16, according to the report.

The company’s lawyers plan to file opposition papers against the suspension order by Sept. 4, per the report.

In a Wednesday (Aug. 7) post on the social media platform, X Global Government Affairs said that X communicated to users how it uses data to train AI, provides a simple control that allows users to decide if their public posts can be used for AI training, and allows users to control their interactions with Grok.

“The order that the Irish DPC has sought is unwarranted, overbroad and singles out X without any justification. This is deeply troubling,” X Global Government Affairs said in the post.

“The order applies not just to Grok but to any AI model that X uses, potentially impacting our work to keep the platform safe and possibly the ability to offer X in the EU,” it added.

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The initiative outpaces similar efforts by rivals Wendy’s and White Castle. Yum Brands aims to implement AI-powered ordering systems across the United States and globally.

“The AI voice technology would enable standardization of the customer journey and experience, which can then be compared across branches globally,” Alina Timofeeva, an expert in technology and data risk, told PYMNTS.

Taco Bell joins a growing cadre of quick service restaurants, traditional restaurants and delivery services which have been testing the technology to streamline the ordering process. Food delivery services like Uber Eats and DoorDash are using AI chatbots to personalize customer recommendations and improve ordering.

Last December, McDonald’s said it is partnering with Google Cloud to use AI to streamline operations and enhance customer experiences. The fast-food giant plans to implement AI in back-of-house tasks and launch new digital platforms in 2024. But a test of AI tech in drive-thrus was halted recently and the company plans to take another look at the program.

For their part, consumers seem to be open to idea of food ordering with AI, according to the PYMNTS Intelligence study, “How Consumers Want To Live In The Voice Economy.” That data shows nearly 40% of consumers believe voice recognition technology will be as advanced as human conversation within five years; and 63% say they would use voice now if it were as capable as a person, because it is easier and more convenient.

From Test Kitchen to Global Rollout

At Taco Bell, the AI experiment began in 2021 with just five locations. By May 2023, 30 California restaurants were using the technology. Over 100 of Taco Bell’s nearly 7,700 U.S. locations now employ AI order-takers, with hundreds more slated to join by December.

According to Lawrence Kim, Yum Brands’ chief innovation officer, two years of testing form the foundation for the company’s confidence. Reports indicate improved order accuracy and reduced wait times, addressing key industry pain points. In 2022, the average drive-thru wait across major chains stretched to 6 minutes and 13 seconds, up from 5 minutes and 57 seconds in 2021, SeeLevel HX reported.

Timofeeva paints a picture of AI’s potential to transform Taco Bell’s operations from top to bottom. The technology could dissect customer satisfaction, pinpointing exactly what delights or frustrates diners — whether it’s long wait times, high prices or limited menu options. These insights would cascade to staff, enabling teams to refine customer interactions.

Beyond the counter, AI’s influence could extend to the menu, revealing which items sell well and why, Timofeeva said. This data-driven approach promises a Taco Bell more responsive to customers’ tastes and expectations, potentially revolutionizing the fast-food experience. By helping firms understand customer preferences, improve staff performance and optimize the product lineup, AI could help Taco Bell serve a more satisfying meal, literally and figuratively.

Data-Driven Decision Making

The financial implications are significant for Taco Bell, which says it saw global system-wide sales of $14 billion in 2022. This technology promises to address labor shortages and rising wages while potentially boosting sales through automated upselling.

Yet Timofeeva cautions against overlooking the human element. “To minimize the complaints, there needs to be sufficient staff available to deal with any concerns and ensure continued customer satisfaction,” she said.

Taco Bell’s late entry into AI-powered ordering may prove advantageous. The company can learn from the struggles of early adopters like McDonald’s, which recently scrapped its decade-long experiment with IBM’s automated system. Timofeeva suggests this timing could allow Taco Bell to sidestep common pitfalls and capitalize on recent technological advances. Moreover, she said, the company can benefit from evolving standards in AI ethics and risk management, potentially avoiding the ethical quandaries and technical hiccups that have plagued earlier attempts in the industry.

Success in this AI implementation could set a new standard for the fast-food industry, where drive-thrus account for 70% of sales at quick-service restaurants, according to QSR Magazine. Yet challenges remain, including privacy concerns and the need to accommodate customers who prefer human interaction.

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What do these companies have in common? As The Wall Street Journal (WSJ) reported Tuesday (Aug. 6), they’re all part of a new trend in the artificial intelligence (AI) field: struggling startups being rescued by Big Tech companies in a new type of deal that tech sector observers say are essentially acquisitions.

Other similar deals are on their way, investors tell the WSJ, as the generative AI bubble appears ready to peak, and startups learn they don’t have the cash to develop AI large language models.

“There were a lot of companies that raised on a big vision, but not tangible examples and actual detail,” said Shaun Johnson, a founding partner at the AI-focused venture outfit AIX Ventures.

Meanwhile, Big Tech’s own AI efforts seem to have drawn some skepticism on Wall Street, as Google, Amazon and Microsoft all saw their share prices fall after releasing quarterly earnings last week.

The WSJ report comes days after Character.AI’s co-founders, Noam Shazeer and Daniel De Freitas, announced they were joining Google as part of a larger arrangement that lets the tech giant license the startup’s AI technology.

The deal reportedly involves a buyout of existing investors’ shares at a valuation of $2.5 billion, a sharp increase from its previous valuation of $1 billion, though short of the $5 billion valuation discussed in investor talks last year.

The Amazon/Adept AI deal happened in June, with the tech giant hiring executives and workers from the smaller firm and — sources told the WSJ — paying $300 million to license Adept’s tech.

Sources also say that Adept had raised $400 million, though the cost of developing its technology surpassed what its founders had projected. The WSJ — again, citing sources familiar with the matter — says that the company’s founders had also tried to forge deals with Microsoft and Salesforce.

Microsoft, meanwhile, hired virtually the entire staff of AI developer Inflection in March to bolster its consumer AI division, paying $650 million for its technology.

Last month, the U.K.’s Competition and Markets Authority launched an investigation into this deal to determine whether it qualifies as a merger. Microsoft has said it was cooperating with the investigation and was confident that its arrangement “promotes competition.”

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John Schulman announced his exit on X Monday (Aug. 5) evening, months after OpenAI dissolved its safety-focused superalignment team, and hours before another co-founder – company president Greg Brockman – said he was going on sabbatical for the remainder of the year.

“This choice stems from my desire to deepen my focus on AI alignment, and to start a new chapter of my career where I can return to hands-on technical work,” Schulman wrote.

“I’ve decided to pursue this goal at Anthropic, where I believe I can gain new perspectives and do research alongside people deeply engaged with the topics I’m most interested in.”

He added that his decision was not because OpenAI didn’t support the topic, saying that, on the contrary, its leaders “have been very committed to investing in this area.”

The leaders of the superalignment team, Jan Leike and Ilya Sutskever, both left this year. Leike is now with Anthropic, while Sutskever, also an OpenAI co-founder, launched a new company, Safe Superintelligence Inc.

While Sutskever has expressed confidence in OpenAI CEO Sam Altman’s AI safety priorities, Leike said he felt his team was at odds with the rest of the company.

“Building smarter-than-human machines is an inherently dangerous endeavor,” he wrote in May.

“OpenAI is shouldering an enormous responsibility on behalf of all of humanity.”

Brockman, meanwhile, announced on X Monday he was taking a sabbatical for the rest of 2024.

“First time to relax since co-founding OpenAI 9 years ago,” he wrote. “The mission is far from complete; we still have a safe AGI to build.”

AGI refers to “artificial general intelligence,” an as-yet-unrealized version of AI that can think and reason at the level of human beings.

OpenAI executives have said – at varying times – that the technology is within five to 15 years of becoming a reality.

As PYMNTS wrote recently, the reports of these efforts have sparked discussion in the business community of the possibility of AI-powered commerce that could reshape the rules of global trade, assuming the technology lives up to the hype.

“OpenAI’s pursuit of human-level reasoning isn’t just a technological marvel; it’s a narrative of pushing boundaries and sparking new possibilities in every sector,” Ghazenfer Mansoor, founder and CEO of Technology Rivers, told PYMNTS. “In business, AI can dramatically change how supply chains are managed, forecast market trends with great accuracy, and make customer experiences very personal on a big scale.”

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This new funding from Acorn Capital follows the initial close of AU$28 million in November 2023, bringing RDC’s total Series B funding to AU$37 million, the company said in a press release emailed to PYMNTS.

“This capital injection ensures we have the runway needed to significantly grow our North American operations,” Ada Guan, CEO and co-founder of RDC, said in the release. “Our recent partnership with nCino and M&T Bank highlights our commitment to expanding our footprint and delivering a cutting-edge AI decisioning platform that enhances risk management, lending strategies and regulatory compliance for financial institutions.”

RDC’s AI-powered platform helps banks make lending decisions efficiently and safely, deliver more meaningful customer interactions, improve credit outcomes and increase lending, according to the release.

The firm has been expanding its team and operations in North America over the past two years and it signed its first U.S. customer, M&T Bank, in May, per the release.

Acorn has demonstrated a strong product-market fit, a sustainable competitive advantage and a highly scalable model, Andrew Burt, investment director at Acorn Capital, said in the release.

“We look forward to working with Ada and the RDC team to support their continued success in commercializing RDC’s proprietary technology in Australia and internationally, with a particular focus on rapid expansion in the U.S. market,” Burt said.

When RDC announced that it signed M&T Bank, it said the bank — which is the sixth largest commercial bank in North America — will use the AI platform to gain more comprehensive insights into cash flow health, credit risk and lending opportunities.

RDC also said its collaboration with nCino, which is a cloud banking firm and RDC’s reseller partner, facilitated the deal, as that company’s Continuous Credit Monitoring solution leverages the RDC platform.

NCino announced its value-added reseller agreement with RDC in February 2023, saying the AI decisioning platform would enhance the lending process for its customers and create value and efficiencies.

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