AI Research

Senator Reintroduces Bill for AI Regulatory Sandbox for Finance

Published

1 month ago

July 31, 2025

PYMNTS

A bipartisan bill to establish regulatory sandboxes for artificial intelligence (AI) experimentation in financial services took center stage at a Senate subcommittee hearing Wednesday (July 30), as lawmakers weighed how to balance AI-driven innovation with oversight.

Sen. Mike Rounds (R-S.D.), who chairs the Senate Subcommittee on Securities, Insurance, and Investment, announced the reintroduction of the “Unleashing AI Innovation in Financial Services Act.”

The bill, co-sponsored with Sen. Martin Heinrich, D-N.M., would let financial institutions test AI-enabled products and services without immediate risk of enforcement action, as long as they meet transparency, consumer protection and national security requirements.

“By creating a safe space for experimentation, we can help firms innovate and regulators learn without applying outdated rules that don’t fit today’s technology,” Rounds said. The bill was originally introduced in 2024.

If enacted, S.4951 would direct financial regulators — including the Securities and Exchange Commission, Consumer Financial Protection Bureau and the Federal Reserve — to evaluate and potentially waive or modify existing rules for approved AI test projects. Agencies would have 90 days to approve or deny applications, with automatic approval if no decision is made by the deadline.

During the hearing, lawmakers from both parties said they wished to foster innovation while mitigating the risks of unregulated AI adoption.

Sen. Mark Warner, D-Va., remembered a prior hearing called by Sen. Chuck Schumer, D-N.Y., that brought together CEOs of top AI companies. “Remember Schumer asked, ‘How many of you all think AI needs to be regulated?’ Everybody raised their hand.”

But once it came down to brass tacks, “I worry that we’re frankly going almost completely in the opposite direction,” Warner said. For example, President Trump’s AI action plan favored deregulation of AI.

Warner said that if people could turn back time, “most of us would think that if in 2014 we’d put some guardrails on social media, at least [to protect] our kids’ mental health, we’d be in a better spot. We didn’t — and social media is tiny compared to the potential that AI has.”

Warner pointed to the example of Delta Air Lines testing AI systems that use an individual’s data to tailor airfare pricing, a practice he called “surveillance” pricing. Warner and two other senators are concerned and have written a letter to Delta asking for additional information.

Insurers Refuse to Cover AI Risks

Kevin Kalinich, global leader for intangible assets at Aon, said during the hearing that the insurance industry is beginning to respond to the risks posed by emerging AI capabilities, including hallucinations from generative models, deepfakes, and autonomous software agents.

However, Kalinich said that actuarial models lack sufficient historical data to accurately price these risks. As a result, some insurers are excluding AI-related exposures in professional liability and cyber policies.

Meanwhile, “a few cutting-edge insurance carriers have created AI-specific insurance protection, albeit with smaller limits than are sufficient for larger clients,” Kalinich said.

The Aon executive noted that underwriters are more likely to offer favorable terms when firms have strong AI governance practices, including documented model audits, explainability metrics and bias mitigation protocols. “Good governance leads to better insurability, which in turn supports innovation and consumer protection,” he said.

Tal Cohen, president of Nasdaq, described how AI is already improving market surveillance, reducing false positives and streamlining investigations. Last week, Nasdaq launched its agentic AI workforce for compliance and efficiency.

Nasdaq’s first two AI agents — the digital sanctions analyst and digital enhanced due diligence analyst — were put to work to labor-intensive compliance tasks. For the digital sanctions analyst, when integrated into a bank’s alert triage workflow, reduced the review workload by over 80%.

Beyond efficiency is stability. Rounds asked Nasdaq’s Cohen what threats from adversarial nations might be coming that would destabilize U.S. financial markets, since delays of even milliseconds in order execution can erode investor confidence.

Cohen said that Nasdaq’s chief information security officer not only uses the most advanced AI cybersecurity tools but also coordinates with industry peers on protection. “This is not a competitive element for us with other exchanges,” he said. “We share and we collaborate.”

But when pressed whether a formal multiagency task force exists to address AI risks across exchanges, Cohen replied, “We need one. We need to have that discussion.”

Moreover, the liability arising from these AI incidents would be “shared,” Cohen added.

David Cox, vice president for AI models at IBM Research, said an open-source approach in AI development is important in building trust.

“We strongly believe in the value of open source AI. It enhances security, trust and collaboration through transparency, enables smaller firms and research organizations to compete without prohibitive upfront capital costs, and it expands the pipeline of future talent,” Cox said.

Large language models (LLMs) must be auditable, particularly in regulated environments.

“Firms must understand exactly what data underpins their models and be able to audit those systems over time,” Cox said, adding that few model developers disclose their training datasets, making compliance tougher.

Sen. Katie Britt, R-Ala., raised concerns about AI-powered impersonation scams, citing a 148% year-over-year increase in financial fraud driven by generative AI. She also asked Cohen about trading bots and the risk of AI-based decision systems on market integrity. Cohen said any regulated firm would have the “proper controls” in place.

In the end, there was broad agreement at the hearing that the status quo on regulations is not sufficient. Warner noted that China is no longer merely copying technology instead of innovating. “That’s changed,” he said. “China is not playing for second place in the race for AI.”

Added Britt: “This is the race that matters.”

AI Regulations Bring Deluge of Lobbying Efforts to DC

Senate Shoots Down 10-Year Ban on State AI Regulations

Source link

Up Next

Inside the relentless race for AI capacity

Don't Miss

Virtual labs with AI scientists produce promising result in Stanford study, ETHealthworld

PYMNTS

Click to comment

AI Research

The Future of Market Research and Strategy: AI, Big Data & Beyond | nasscom

Published

43 minutes ago

September 2, 2025

The Editors

In today’s fast-changing business world, accurate market research and strong strategies are significant. Consumer priorities are changing rapidly, digital changes are again reforming industries, and competition is really high. Organisations are moving to artificial intelligence (AI), big data, and advanced analysis to understand consumer behaviour research, predict market trends, and design future strategies. Market research’s future lies in technology combined with human expertise to generate smart, faster, and more actionable insights.

AI in Market Research

Artificial intelligence revolutionises the way businesses conduct research. Traditional research conducting methods like surveys and focus groups are now complemented by AI-driven tools. Natural language processing (NLP) and sentiment analysis can scan millions of social media posts, online reviews, and customer feedback in real-time sentiment gauges.

The AI-operated chatbot collects qualitative data at scale, while predictive analytics analysis allows organisations to predict requirements and customer preferences. It reduces costs, saves time, and produces very accurate results. Many market research consulting firms already use AI technologies to offer customers deep insight and competitive management in decision-making.

Unlocking Consumer Behaviour

Data is new currency, and businesses are leveraging big data to make the most out of it. From browser history and purchasing records for geolocation and IoT data, companies now have access to the latest versions of information. Big data tools clean, process, and analyze this data to highlight the patterns and trends that were once hidden.

For example, retailers can estimate the demand for regional products by combining weather data with purchase history. Similarly, streaming services depend on large data for users to recommend personalized content. The future power of large data makes sure that businesses not only understand today’s consumer behaviour, but can also predict future functions with great accuracy.

The Perfect Balance between Human and Machine

While AI and big data are powerful, human elements are important. Machines can highlight “what” and “how”, but humans give reference to “why”. Emotional intelligence, cultural awareness, and moral ideas require human interpretation.

The future of market research will depend on the hybrid model where AI handles data analysis of large and itself. At the same time, researchers and strategists combine this insight with human motivations and values. This balance will help companies craft data-informed strategies and emotional resonance strategies. Companies that offer strategic consulting services will play an important role in helping organisations mix technical insights with human-centric strategies.

Ethics and Privacy in Data-Driven Research

When companies collect more consumer data, the concerns of privacy and ethics become central. Rules such as GDPR and CCPA now require strict data management and use compliance. Consumers also expect transparency in how their data is collected and used.

The future of market surveys will emphasise responsible practices; transparency, consent, and trust-building will be non-negotiable. Companies that prioritise ethical research practices will comply with the legal framework and receive consumer loyalty.

Emerging Technologies on the Horizon

Apart from AI and Big Data, many new technologies will reshape market research:

Adopted and Virtual Reality (AR/VR): Simulating product experiences before launch.
Blockchain: Provides transparency and authenticity in data collection.
IoT (Internet of Things): Continuous real-world data through connected devices.
Voice analysis: Extracting insight from voice interaction with smart devices.

Strategy in the Age of Intelligent Insights

Future strategies will go beyond static annual plans. Instead, companies will use dynamic strategies shaped by real-time data. The AI-operated landscape will allow us to model outfits to prepare for several potential futures.

In addition, personalized product design, management chains, and customer service will expand beyond marketing. Instead of one-size-fits-all, the business will use adaptive strategies that accurately meet the requirements for different customer groups.

Conclusion

Technology and spontaneous integration of human insight will define the future of market research and strategy. AI and Big Data will continue to provide fast, more future insights, while new tools like AR, IoT, and Blockchain will enrich the research ecosystem. Yet, human touch, creativity, and ethical decisions are irreplaceable.

Companies that embrace this hybrid approach will understand what consumers want and predict their future needs. Companies can create agile, consumer-centric, and future-proof strategies by combining technology, data, and human expertise.

Source link

AI Research

Douyin, WeChat among major Chinese platforms to roll out AI labels amid new rules | MLex

Published

49 minutes ago

September 2, 2025

The Editors

By MLex Staff ( September 2, 2025, 06:52 GMT | Insight) — China’s major Internet platforms are moving to comply with sweeping new rules that took effect on Sept. 1, requiring clear labeling of content generated by artificial intelligence. The move underscores Beijing’s determination to rein in fast-growing AI applications and curb online risks. ByteDance’s Douyin, the sister app of TikTok in China, said yesterday that it has rolled out two key functions regarding how AI-generated content posts will be tagged — explicit identifiers visible to users and implicit identifiers in metadata.China’s major Internet platforms are moving to comply with sweeping new rules that took effect on Sept. 1, requiring clear labeling of content generated by artificial intelligence. The move underscores Beijing’s determination to rein in fast-growing AI applications and curb online risks….

Prepare for tomorrow’s regulatory change, today

MLex identifies risk to business wherever it emerges, with specialist reporters across the globe providing exclusive news and deep-dive analysis on the proposals, probes, enforcement actions and rulings that matter to your organization and clients, now and in the longer term.

Know what others in the room don’t, with features including:

Daily newsletters for Antitrust, M&A, Trade, Data Privacy & Security, Technology, AI and more
Custom alerts on specific filters including geographies, industries, topics and companies to suit your practice needs
Predictive analysis from expert journalists across North America, the UK and Europe, Latin America and Asia-Pacific
Curated case files bringing together news, analysis and source documents in a single timeline

Experience MLex today with a 14-day free trial.

Source link

AI Research

Nigeria jumps from zero to 20 AI research papers in 18 months

Published

2 hours ago

September 2, 2025

Frank Eleanya

Nigeria has published 20 peer-reviewed artificial intelligence (AI) compute research papers in less than two years, up from zero, in a sign of the government’s push for Nigeria’s entry into the global conversation on AI research.

That jump is thanks to the Nigerian Artificial Intelligence Research Scheme (NAIRS), a federally funded program designed to stop the country from being a mere exporter of talent and instead anchor research output under Nigerian institutions.

Launched in early 2024 by the Ministry of Communications, Innovation, and Digital Economy, and funded through the National Information Technology Development Agency (NITDA), NAIRS seeks to address a structural gap: while Nigerians abroad were contributing thousands of AI papers, none were credited to local universities or labs, leaving the country with little to show under its own name.

“We discovered thousands of AI papers authored by Nigerians, but none tied to Nigerian institutions,” Olubunmi Ajala, National Director of the National Centre for Artificial Intelligence and Robotics, told TechCabal on the sidelines of GITEX Nigeria in Abuja on Monday. “That’s why NAIRS was created, to give Nigerian researchers, both at home and in the diaspora, a structured platform to produce Nigeria-led AI research.”

Over 4,000 researchers applied to the first NAIRS call, with 45 consortia of academics and startups eventually selected. Each group received grants of up to ₦5 million ($3,400) and a mandate to publish within a year in one of five thematic areas: agriculture, healthcare, education, sustainability, and utilities.

By August 2025, the results were in: 20 peer-reviewed papers, two of them in Springer journals, and several projects already tested in the field. One agricultural consortium used YOLOv8 computer vision models to detect “tomato Ebola,” a disease that wipes out harvests. Another built a smart traffic management system that replaces Nigeria’s fixed 60-second light cycles with an adaptive model, allocating green light time based on real-time traffic flows.

“These are not just academic exercises,” Ajala said. “They are practical solutions tested with real data, designed to solve problems that directly affect Nigerians.”

The initiative is also building long-term infrastructure. Through the AI Collective, a network of over 2,000 Nigerian AI practitioners globally, participants share data, mentor students, and form syndicates to commercialise work.

Ajala said the next phase is to push for patents, biotech applications, and scalable startups.

“Once strong research outcomes begin to emerge, funding naturally follows,” he said. “Global partners are keen to see how AI can address African realities, and Nigeria is beginning to provide answers.”

Mark your calendars! Moonshot by TechCabal is back in Lagos on October 15–16! Join Africa’s top founders, creatives & tech leaders for 2 days of keynotes, mixers & future-forward ideas. Early bird tickets now 20% off—don’t snooze! moonshot.techcabal.com

Source link