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AI Venture Funding Reaches New Highs In Q1 2026, Report Reveals | Crowdfund Insider
PitchBook has indicated that venture capital activity in artificial intelligence reached explosive new levels during the first three months of 2026, according to PitchBook’s latest research preview. Total AI-related investments climbed to $255.5 billion in the quarter—surpassing the entire ...
Artificial Intelligence: Why it’s a productive, not destructive, force for capital markets - The Economic Times
Artificial intelligence is rapidly transforming capital markets by automating trading, research and portfolio management functions once handled manually. While AI is improving efficiency and productivity across finance, experts believe human judgment, relationships and strategic decision-making ...
Reuters AI News | Latest Headlines and Developments | Reuters
U.S. banks are rushing to fix scores of IT system weaknesses flagged by Anthropic’s powerful but costly Mythos AI tool, prompting urgent repairs, software upgrades and raising the possibility of disruption for customers.
State Farm CEO is betting big on AI—and contemplating the company’s future in California
Also: All the news and watercooler chat from Fortune.
Hackers Armed With AI Stoke Fears for $130 Billion Crypto Sector
The crypto hacks came a little over two weeks apart in April, netting the attackers almost $600 million in total while triggering an investor exodus from one major platform and causing another to fail.
iDenfy teams up with RATO
– Advertisement – RegTech company iDenfy is strengthening its footprint in European banking through a new partnership with Lithuanian lender RATO bank, as financial institutions accelerate the shift toward fully digital onboarding. The integration brings iDenfy’s AI-powered identity verification and automated AML screening directly into RATO’s mobile banking app, enabling new customers to complete full […]
The End of the Trade-Off: How AI Agents Broke The Onboarding Trilemma
Brex redesigned its customer onboarding process using AI agents to automate document review and fraud analysis, reducing processing time from days to minutes.
Data readiness for agentic AI in financial services
Financial services companies have unique needs when it comes to business AI. They operate in one of the most highly regulated sectors while responding to external events that are updated by the second. As a result, the success of agentic AI in financial services depends less on the sophistication of the system and more on…
A European central bank has signed a mega deal with a cloud service provider. The problem for Google, Microsoft and Amazon? It’s not with them
Originally built to support the retail business, Schwartz Digits is now a trusted provider of secure data services to European businesses and governments.
AI Is Making the Cyber-Thriller Less Fictional | AEI
The infrastructure of modern economic life—financial systems, energy grids, hospital networks—is built on the assumption that the most dangerous hackers are rare. That assumption has a fast-approaching expiration date.
Prudential - Powering AI-Driven Advisor Workflows in Life Insurance | AWS Events
Prudential is utilizing generative AI and multi-agent architectures to streamline life insurance advisor workflows, reducing administrative overhead and improving productivity.
Do Fair Models Reason Fairly? Counterfactual Explanation Consistency for Procedural Fairness in Credit Decisions
arXiv:2605.12701v1 Announce Type: cross Abstract: Machine learning algorithms in socially sensitive domains (e.g., credit decisions) often focus on equalizing predictive outcomes. However, satisfying these metrics does not guarantee that models use the same reasoning for different groups. We show that existing outcome-fair models can still apply fundamentally different reasoning to individuals, a ``hidden procedural bias'' missed by standard fairness metrics and algorithms. We propose Counterfactual Explanation Consistency (CEC), a framework that detects and mitigates this bias by aligning feature attributions between individuals and their counterfactual counterparts. Key contributions include a nearest-neighbor counterfactual generation method, a modified baseline for integrated gradient comparisons, an individual-level procedural fairness metric, and a corresponding training loss. We introduce a taxonomy identifying ``Regime B'' (same outcome, different reasoning) as a critical blind spot. Experiments on synthetic data, German Credit, Adult Income, and HMDA mortgage data demonstrate that outcome-fair baselines exhibit substantial hidden bias, while CEC substantially reduces it with modest utility cost.
AI Infrastructure: From Zero to $100B and Beyond: How the Emergent Sector Is Reshaping the Non-IG Market
Explore AI Infrastructure: From Zero to $100B and Beyond. Discover how financing shapes the future of AI development.
Former Up Bank team raises $4 million for AI finance startup
Former Up Bank execs have raised $4 million for Extraordinary Money (XMO), a Melbourne startup building AI-native consumer finance products.
SoftBank profits surge on $25bn gain for OpenAI stake
Japanese group books net income of $11.6bn in fourth quarter, vastly ahead of analyst expectations
Fill-Side Non-Retail Trading on Polymarket: An Empirical Study of Behavioral Tiers and Microstructure Signatures Under Quote-Attribution Constraints
arXiv:2605.11640v1 Announce Type: cross Abstract: Prediction markets cannot exist without market makers, arbitrageurs, and other non-retail liquidity providers, yet the supply-side microstructure of Polymarket-class venues has not been characterized at on-chain pseudonymous-address scale. This paper studies non-retail participation on Polymarket using an empirical run on the PMXT v2 archive over 2026-04-21 through 2026-04-27 (13,356,931 OrderFilled events; 77,204 addresses with five+ fills; 43,116 markets). We report three findings. First, Polymarket's off-chain CLOB architecture renders address-level quote-lifecycle attribution permanently unavailable: OrderPlaced and OrderCancelled events are off-chain and absent from public archives, so quote-intensity, two-sided-ratio, and posted-spread features cannot be built at address level. We document this as a structural validity-gate failure (G-QUOTE-LIFE universal fail) and restrict analysis to a six-feature fill-side vector. Second, density-based clustering (DBSCAN, fifteen sensitivity configurations) on the fill-side vector produces a single dense cluster with zero noise: fill-side behavior in the empirical window is uni-modal under the six-feature vector, contradicting the pre-registered hypothesis of four-to-five separable archetypes. Third, robust retail vs non-retail separation is achievable through clustering-independent feature-tier stratification: whale-tier, high-frequency-operator, and power-trader tiers jointly hold 81.4% of total notional across 12.6% of addresses. Address-level market-making and liquidity-provision claims are withdrawn per the G-QUOTE-LIFE failure; spoof-by-non-fill manipulation detection is downgraded to market-level book diagnostics. A privacy-respecting derived-dataset deposit accompanies the paper as Bundle 3 of the PMXT family. Fourth paper in a four-paper programme on event-linked perpetuals and leveraged prediction-market microstructure.
US bank reports itself after slinging customer data at 'unauthorized AI app'
The volume and sensitivity of the data shared with an unauthorized AI application are cited as chief concerns.
Mistral Developing New AI Model for Banks Lacking Mythos Access
French artificial intelligence startup Mistral AI is in discussions with European banks about deploying its answer to Anthropic PBC’s Mythos, the limited-access AI model that can uncover cybersecurity vulnerabilities at unprecedented speed and scale.
$300 Billion AI Debt Binge Spreads From Wall Street to Tokyo
Bankers were still putting the final touches on Alphabet Inc.’s blockbuster $17 billion of bond sales when word started to spread Monday morning on Wall Street: the company is already hawking more debt.
AI Enabled Cyberattacks Are Increasing Financial Stability Risks : Analysis | Crowdfund Insider
The International Monetary Fund (IMF) has issued a fresh alert on the growing dangers to global financial stability from artificial intelligence. In a blog post dated May 7, 2026, the IMF explains how AI is reshaping both the vulnerabilities and defenses of the financial system.
South Korea Vs. U.S.: Who Wins The AI Trade? (NYSEARCA:EWY) | Seeking Alpha
South Korea’s KOSPI is emerging as an AI infrastructure play with 2026 earnings seen as +300% and a 9x P/E. Read what investors need to know.
Financial Services Firms Lead Enterprise AI Adoption as 85% Boost Budgets | PYMNTS.com
A PYMNTS Intelligence study finds financial services firms lead other sectors in enterprise AI deployment.
Japan, US tackle AI cyberthreats as megabanks prepare to access Mythos
Japan is accelerating efforts to address cybersecurity risks from frontier artificial intelligence models in cooperation with the US, as three major Japanese banks are reportedly set to gain access to Anthropic's Claude Mythos Preview.
Venture Capital Funding: Samaya AI, Nexthop AI, Deccan AI - InfotechLead
Technology companies such as Samaya AI, Nexthop AI, and Deccan AI, among others, announced venture capital funding across financial AI agents
CME plans to launch futures market for AI computing power
New contracts will allow traders and companies to bet on and hedge future price of GPU rental
US Fed revamping its infrastructure to cope with AI, legislative changes, Waller says
The US Federal Reserve is updating its infrastructure to adapt to the challenges posed by artificial intelligence and evolving legislative requirements.
Market Talk: AI trade a 'landmine for investors' | Reuters
Dean Smith, chief strategist and portfolio manager at FolioBeyond, said that given the small number of AI -linked stocks driving the S&P 500 to record highs, "any significant hiccup to the AI trade" could bring "pretty rough times" for the rest of the market. Lisa Bernhard reports.
Q1 2026 AI VC Trends - PitchBook
The Q1 2026 AI VC Trends report provides an analysis of recent VC activity and includes a market map of leading VC-backed companies in the space.
IMF warns of financial risks as AI boosts cyberattacks
IMF warns that AI amplifies cyber threats, risking financial stability. Calls for resilient policies and international cooperation to combat emerging risks.
Groww Shares in Focus as ₹4,750 Crore Block Deal Buzz Coincides With Six-Month Lock-In Expiry - Best Stock Market Blogs & Investment Insights | Equentis
For market participants, this combination matters. Lock-in expiries and block deals often provide clues about investor confidence, liquidity events, startup valuations, and broader market trends.
Manipulation, Insider Information, and Regulation in Leveraged Event-Linked Markets
arXiv:2605.10486v1 Announce Type: cross Abstract: The introduction of leverage on prediction-market event contracts raises three structurally distinct questions that have not been addressed jointly: how leverage changes manipulation incentives, how it interacts with informed-trading rents, and how regulatory frameworks should respond. This paper develops a theoretical framework for the first two and a synthesis of the existing regulatory landscape for the third. The principal analytical move is a two-axis manipulation taxonomy distinguishing market-price manipulation from real-world outcome manipulation, where the manipulator affects the underlying event itself. Continuous-underlying derivative markets generally do not make outcome manipulation a venue-level payoff channel; event-linked markets do. Within this taxonomy, leverage plays asymmetric roles: it scales market-price manipulation linearly but shifts the cost-benefit threshold for outcome manipulation, and it scales informed-trading rents in three ways (direct multiplication, Sharpe-ratio preservation, detection-cost amortization). Section 7 connects Paper 1's pre-emption and halt-protocol findings (CC-007b, CC-008) to three manipulation channels: pre-emption introduced by the dynamic-margin engine, halt-arbitrage introduced by the resolution-zone halt protocol, and strategic bad-debt-shifting that no engine in Paper 1's framework family addresses. The framework's manipulation-resistance contribution is a re-allocation of attack surface, not a net reduction. The regulatory synthesis covers principal jurisdictions (US, EU, UK, Singapore, offshore) and identifies three regulatory-arbitrage pathways. The paper concludes with 14 recommendations for venue operators, regulatory bodies, and the research community, separated into framework-independent and framework-conditional categories.
AI ROI In Banking Remains Elusive. Here’s Why
AI won't transform banking by replacing old workflows. Find out why ROI remains elusive and the 3 shifts that change everything for financial leaders
Goldman Sachs sees enterprise AI spending hinging on productivity gains | Prism News
Goldman’s message is clear: AI budgets will go to teams that can prove productivity gains fast, while pilots without measurable ROI face tighter scrutiny.
Closing the Shadow AI Gap: New Compliance Deadlines for Financial Institutions • Dev|Journal
Financial institutions face a critical gap between AI deployment and regulatory compliance with OSFI E-23 and SR 11-7 standards.
Australia Watchdog Says Money Launderers Ramping Up AI for Scams
Australia’s financial crimes watchdog warned of a heightened threat of money laundering linked to artificial intelligence that has been used by crooks to scale up activities, automate processes and create fake documents.
South Korea enhances privacy risk prevention measures under AI transformation
South Korea's privacy regulator is shifting to a preventive management framework for high-risk AI systems and increasing potential fines for privacy violations to up to 10 percent of revenue.
Calibrating Behavioral Parameters with Large Language Models
arXiv:2602.01022v3 Announce Type: replace Abstract: Behavioral parameters such as loss aversion, herding, and extrapolation are central to asset pricing models but remain difficult to measure reliably. We develop a framework that treats large language models (LLMs) as calibrated measurement instruments for behavioral parameters. Using four models and 24{,}000 agent--scenario pairs, we document systematic rationality bias in baseline LLM behavior, including attenuated loss aversion, weak herding, and near-zero disposition effects relative to human benchmarks. Profile-based calibration induces large, stable, and theoretically coherent shifts in several parameters, with calibrated loss aversion, herding, extrapolation, and anchoring reaching or exceeding benchmark magnitudes. To assess external validity, we embed calibrated parameters in an agent-based asset pricing model, where calibrated extrapolation generates short-horizon momentum and long-horizon reversal patterns consistent with empirical evidence. Our results establish measurement ranges, calibration functions, and explicit boundaries for eight canonical behavioral biases.
Pictet Fund Plows 30% of Cash Into AI Stocks on Risk Revival
A $3.5 billion multi-asset fund at Pictet Asset Management has sharply raised its equity exposure, shifting as much as 30% of its cash-equivalent holdings into artificial-intelligence heavyweights across Asia and the US.
Weekly Compass #14: Yes, AI Is Still Working. No, It's Not the Only Trade.
On AI , management said on the Q4 call that AI revenue isn’t materializing yet but competitive disruption isn’t showing up either, so any updated commentary on how AI is affecting subsidiary performance matters.
Implementing advanced AI technologies in finance | MIT Technology Review
In finance departments that have long been defined by precision and control, AI has arrived less as a neatly managed upgrade than as a quiet insurgency. Employees are already using it while leadership races to impose structure, governance, and strategy after the fact.
AI M&A surges as software captures nearly three-quarters of North American deals - InvestmentNews
S&P Global report shows AI transactions hit record levels, with software dominating investor interest.
AI Stocks Drive S&P 500's 142% Gain Since 2024 | Let's Data Science
CryptoBriefing reports that from May 2024 to June 2026 the **S&P 500** posted a **142%** gain, but the index would have advanced just **16%** over the same period if AI-related stocks were excluded. CryptoBriefing also reports that AI-linked companies now represent **45%** of the S&P 500's ...
Toward Individual Fairness Without Centralized Data: Selective Counterfactual Consistency for Vertical Federated Learning
arXiv:2605.07117v1 Announce Type: new Abstract: When algorithmic decisions depend on data distributed across institutions, how can we ensure that an individual's outcome does not change arbitrarily based on a protected attribute? We study this question in vertical federated learning (VFL), where features are split across parties, sensitive attributes may be private, and proxies for protected characteristics can be scattered across institutional boundaries under strict privacy constraints. Our focus is on individual-level counterfactual stability, i.e., per-instance prediction consistency under protected-attribute interventions as formalized in the causal fairness literature, rather than group parity guarantees such as demographic parity or equalized odds. We propose SCC-VFL, a server-centric framework for enforcing selective counterfactual consistency (SCC) at the individual level in VFL. SCC-VFL operationalizes a given policy specification by combining three components: (i) differentially private, graph-free discovery of feature roles into non-descendants, policy-permitted mediators, and impermissible proxies using only a formally private sketch of the sensitive attribute, with a formal per-release privacy that does not extend to the full training pipeline; (ii) masked counterfactual generation that edits only mediators while fixing non-descendants and suppressing proxy leakage; and (iii) server-side enforcement via an SCC consistency loss that penalizes impermissible prediction changes under protected-attribute interventions. Across three real-world datasets spanning credit, healthcare, and criminal justice, SCC-VFL maintains or improves predictive accuracy while sharply reducing decision flip rates by up to 98% relative to strong baselines. It also lowers attribute-inference attack success and improves robustness, demonstrating favorable utility-fairness-privacy trade-offs in realistic VFL deployments.
Implementing advanced AI technologies in finance
In finance departments that have long been defined by precision and control, AI has arrived less as a neatly managed upgrade than as a quiet insurgency. Employees are already using it while leadership races to impose structure, governance, and strategy after the fact. The result is a paradox: one of the most tightly regulated functions…
Demutualization, AI and the independent advisor - Investment Executive
The era of the charismatic generalist whose personality wins the business is over
Circle Launches AI Infrastructure to Power Agentic Economy - Markets Media
The next phase of the global economy will be increasingly AI and agent-driven.
LPs fight tooth and nail for foundational AI co-investment share - PitchBook
Competition for deals involving the largest pre-IPO AI companies, like OpenAI and Anthropic, is separating the strongest LPs from the weakest.
Fidelity is growing its work force by thousands. Blame AI. - The Boston Globe
The Boston financial services giant is cutting about 1,000 jobs, but it's adding more. The company needs real-world techies and other hands-on workers to roll out key products and services right now.
AI Productivity Boom Reshapes Mortgage Rate Dynamics | Let's Data Science
Wall Street coverage frames a potential long-term decline in borrowing costs as linked to AI-driven productivity gains. According to Jim Iuorio in articles published on Seeking Alpha and republished by CME Group, analysts are "increasingly bullish on lower rates in the long term" as AI reshapes ...
Why AI's Productivity Boom Could Impact Mortgage Rates | Seeking Alpha
Wall Street analysts are increasingly bullish on lower rates in the long term as AI reshapes lending economics. Read more here.
AI drives markets as valuations race ahead of earnings - The Business Times
Is this a legitimate re-rating of the technology sector, or an overstretched bubble? Read more at The Business Times.
S&P 500 and Nasdaq notch records, boosted by AI and earnings optimism | Reuters
May 8 (Reuters) - The S&P 500 and the Nasdaq notched record highs on Friday, boosted by gains in Nvidia, Sandisk and other AI -related stocks, while a stronger-than-expected jobs report pointed to labor market resilience.
AI cyber capabilities raise risk of correlated financial system failures, IMF warns | Digital Watch Observatory
Regulators are urged to strengthen resilience and coordination as cyber threats evolve into potential macro-financial shocks.
ECB’s Escrivá Says AI Risks Prompt Finance Infrastructure Review
Central banks must review the resilience of financial infrastructure given the rise of artificial intelligence, as well as defend their role as the ultimate guarantor against risks posed by stablecoins, said European Central Bank Governing Council member José Luis Escrivá.
AI disruption, work pressure pushing BFSI employees towards exit, says report - BusinessToday
The report, titled “People Reality in BFSI – Three Workforce Imperatives,” said the sector is undergoing a major workforce transition as companies accelerate automation and Artificial Intelligence integration while simultaneously facing tighter regulations and financial volatility.
IMF Issues Warning on AI Cyber Threats to Financial System | 2026 - News and Statistics - IndexBox
The IMF warns that AI-driven cyberattacks pose a growing danger to the global financial system, citing Anthropic's Claude Mythos Preview model as an example of how advanced AI can exploit vulnerabilities. The organization urges policymakers to treat cybersecurity as a core stability issue and ...
How AI, Global Tensions Strain Secure Data Sharing
AI adoption and geopolitical instability are forcing governments to modernize cross-domain architectures as manual approvals, delayed transfers and insecure
Genpact and Google Cloud partnership targets CFO chaos
Genpact and Google Cloud partnership brings agentic AI to finance operations, helping CFOs improve forecasting, cash flow and efficiency fast.
Council Post: The Future Of Health Insurance Is Personalized—And AI Makes It Possible
ICHRA is reshaping employer-sponsored health insurance. Here's how agentic AI can simplify plan selection, enrollment and payments for a more personalized benefits experience.
Agents That Transact: Introducing Amazon Bedrock AgentCore Payments
Amazon Bedrock AgentCore Payments provides a governed way for AI agents to access wallets and transact through payment infrastructure from Coinbase and Stripe.
Why UK mortgage lenders are turning to agentic AI to fix slow approvals
Mortgage lending has not kept pace with the rest of the digital economy. Borrowers can open accounts, move money, and make purchases in minutes, yet applying for a mortgage still takes weeks, involves repeated document checks, and relies on manual coordination between lenders, brokers, and ...
SoftBank Cuts Target for OpenAI Margin Loan by 40%
SoftBank is scaling back plans for a $10 billion margin loan backed by its OpenAI stake after creditors voiced some hesitation. Matthew Bloxham of Bloomberg Intelligence has more. (Source: Bloomberg)
SoftBank cuts target for OpenAI margin loan, Bloomberg News reports | Reuters
SoftBank Group has downsized plans for a $10 billion margin loan backed by its Open AI stake after hesitation from some creditors, Bloomberg News reported on Friday, citing people familiar with the matter.
Council Post: How AI Is Leveling The Playing Field Between Retail And Institutional Traders
The advantage is no longer about who has access to tools—it's about how effectively those tools are used.
Agentic Retrieval-Augmented Generation for Financial Document Question Answering
arXiv:2605.05409v1 Announce Type: new Abstract: Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual narratives, and footnotes--scattered across corporate filings. Existing retrieval-augmented generation (RAG) approaches adopt a single-pass retrieve-then-generate paradigm that struggles with the compositional reasoning chains prevalent in financial analysis. We propose FinAgent-RAG, an agentic RAG framework that orchestrates iterative retrieval-reasoning loops with self-verification, specifically engineered for the precision requirements of financial numerical reasoning. The framework integrates three domain-specific innovations: (1) a Contrastive Financial Retriever trained with hard negative mining to distinguish semantically similar but numerically distinct financial passages, (2) a Program-of-Thought reasoning module that generates executable Python code for precise arithmetic rather than relying on error-prone LLM-based mental computation, and (3) an Adaptive Strategy Router that dynamically allocates computational resources based on question complexity, reducing API costs by 41.3% on FinQA while preserving accuracy. Extensive experiments on three benchmark datasets--FinQA, ConvFinQA, and TAT-QA--demonstrate that FinAgent-RAG achieves 76.81%, 78.46%, and 74.96% execution accuracy respectively, outperforming the strongest baseline by 5.62--9.32 percentage points. Ablation studies, cross-backbone evaluation with four LLMs, and deployment cost analysis confirm the framework's robustness and practical viability for financial institutions.
Humans still matter more than AI in finance
Recruiting digital natives with critical thinking skills is going to be crucial
Koreans flock to pay with their faces
Fintech company aims to ‘eliminate physical credit cards’ in South Korea in three years
RBC lifts S&P 500 year-end target to 7,900 on AI optimism | Reuters
RBC said positive earnings revisions, driven by technology and AI -linked firms, alongside strong demand for AI infrastructure have supported valuations. It added that U.S.
Earnings calls, algorithms and ... jazz music? How investors are using AI to gain a trading edge - The Globe and Mail
New tools search company releases, jazz solos for elusive edge in trading
The Anatomy of a Blockchain Prediction Market: Polymarket in the 2024 U.S. Presidential Election
arXiv:2603.03136v2 Announce Type: replace Abstract: Using on-chain Polygon data, we analyze Polymarket's 2024 U.S. Presidential Election market and develop a transaction-level accounting framework with two components: a volume decomposition that separates exchange-equivalent turnover from share minting and burning, and trader-level disagreement measures. Naive aggregation reports $958M of October Trump-market volume, compared with $391M under our decomposition. Market quality improved as arbitrage-deviation half-lives fell from hours to under a minute and Kyle's {\lambda} dropped from 0.53 to 0.01. During October's large-account episode, capital flowed into both sides simultaneously, consistent with heterogeneous-beliefs trading rather than one-sided manipulation. The framework generalizes to other tokenized prediction markets.
AI threats prompt ASIC cyber resilience warning
ASIC urges financial licensees to act now on AI-driven cyber threats. Read the full warning and find out what your firm must do today.
OCC Recommends Banks Sharpen AI Defense Tactics | PYMNTS.com
The OCC highlighted AI as both a risk and an opportunity for innovation in its spring 2026 Semiannual Risk Perspective.
Anthropic's Mythos set off a cybersecurity 'hysteria.' Experts say the threat was already here
The arrival of Anthropic's Mythos jolted banks, software giants and governments into reckoning with a new era of cyber attacks. But the threat is already here.
Information Aggregation with AI Agents
arXiv:2604.20050v2 Announce Type: replace Abstract: Can Large Language Models (AI agents) aggregate dispersed private information through trading and reason about the knowledge of others by observing price movements? We conduct a controlled experiment where AI agents trade in a prediction market after receiving private signals, measuring information aggregation by the log error of the last price. We find that although the median market is effective at aggregating information in the easy information structures, increasing the complexity has a significant and negative impact, suggesting that AI agents may suffer from similar limitations as humans when reasoning about others. Consistent with our theoretical predictions, information aggregation remains unaffected by allowing cheap talk communication, changing the duration of the market or initial price, and strategic prompting, thus demonstrating that prediction markets are robust. We establish that "smarter" AI agents perform better at aggregation and they are more profitable. Surprisingly, giving them feedback about past performance has no impact on aggregation.
From Credit Cards To An AI Concierge: How Amex Ventures Backs Startups Building Autonomous Commerce
Crunchbase News interviews Kevin Tsang, managing director of Amex Ventures, about the firm’s investment thesis, the kinds of startups it aims to back, and how it works with founders to build and scale projects with a vision toward becoming a "global agentic concierge."
Kalshi valuation quadruples to $22bn in less than a year
Platform raises $1bn in fundraise led by Philippe Laffont’s investment firm Coatue
Can Companies Insure Against AI’s Growing Risks? | Econofact
Lawsuits involving artificial intelligence are proliferating in number and diversity given the increasing application of AI in many broad areas.
ESG as Priced Crash Insurance: State-Dependent Tail Risk and Deconfounding Evidence
arXiv:2605.04479v1 Announce Type: cross Abstract: This research establishes ESG as a state dependent insurance mechanism against equity crashes by addressing the decoupling of unconditional alpha from tail risk resilience. By validating market stress regimes as distinct economic states through a drawdown-based truncation rule, the study demonstrates that high ESG ratings materially reduce the incidence of discrete crash events during systemic drawdowns. To address the selection bias and high-dimensional confounding inherent in traditional linear frameworks, we implement Double Machine Learning as a structural deconfounding layer. Unlike simple predictive modeling, the Double Machine Learning framework utilizes machine learning to handle complex nuisance parameters, allowing us to isolate the asymmetric treatment effects of ESG across different market states. Distributional analysis reveals the underlying mechanism as ESG specifically attenuates the severity of realized tail losses at the most adverse quantiles instead of shifting the entire return distribution. Confirmed by structural estimates, this protection functions as priced insurance that incurs performance drags during stable periods while providing critical resilience when tail risks are most acute.
IMF says Anthropic's Mythos AI model poses cyber threats with financial stability risks
Anthropic’s Mythos AI model enables cyber attacks with extreme financial stability ramifications, underscoring the need for global counter-measures, an IMF blog said.
A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles
arXiv:2605.04076v1 Announce Type: cross Abstract: U.S. financial institutions deploying AI-based fraud detection face a fragmented compliance landscape spanning four regulatory frameworks -- OCC Bulletin 2011-12, SR 11-7, the CFPB AI circular, and FinCEN BSA/SAR requirements -- with no integrated governance life cycle connecting these requirements to model development, validation, and monitoring
Razorpay Oncall Agent: From 30-Minute Investigations to 90-Second AI Analysis
Razorpay's Oncall Agent utilizes multiagent AI to significantly reduce the time required for production incident investigations.
EU AI Act: Three obligations reshaping comms surveillance
The EU AI Act's recording obligations aren't delayed — they're coming. Read how to prepare your data estate now.
SoftBank shares surge as Japanese stock market hits record high
Gains for OpenAI and Arm investor help push Nikkei 225 to new peak after holiday closure
Ramp in talks to hit $40B+ valuation
Fintech company Ramp is reportedly in discussions to raise its valuation to over $40 billion, just months after a previous funding round.
IMF warns new AI models risk ‘systemic’ shock to finance
Fund says preparations needed for ‘inevitable’ AI-enabled breaches of financial institutions’ cyber defences
Coinbase Cuts 700 Jobs and CEO Warns Every Company Will Do the Same
Coinbase has announced a workforce reduction of 700 employees, with the CEO suggesting that AI-driven restructuring will become common across the industry.
India orders infosec red alert in case Mythos sparks crime spree
Securities regulator urges market players to develop new strategies and nail cyber-basics before AI models fuel mass attacks India’s Securities and Exchange Board has advised participants in the nation’s equities industry to immediately revisit their information security systems and practices, in case Anthropic’s Mythos bug-finding AI sparks a cyberattack spree.…
X user tricks Grok into sending them $200,000 in crypto using morse code
A security vulnerability allowed an X user to manipulate the Grok AI into authorizing a large cryptocurrency transfer.
Do Venture Capitalists Beat Random Allocation?
arXiv:2605.03980v1 Announce Type: new Abstract: Venture capital outcomes are dominated by a small number of extreme successes, making it difficult to distinguish investor skill from favorable realizations in a highly skewed return distribution. We study this question by comparing empirical VC portfolios to a constrained random benchmark that preserves key portfolio characteristics, including timing, geography, sector composition, and portfolio size, while randomizing individual company selection. Across funding stages, empirical portfolio distributions appear remarkably close to their random benchmarks. We find no evidence that portfolio construction increases the probability of high-multiple outcomes: the right tail remains statistically indistinguishable from random allocation. Deviations in the lower part of the distribution are small and sensitive to the interpretation of zero outcomes, suggesting at most weak evidence of downside improvement. We further introduce a rank-based benchmark distribution to evaluate outperformance at each position in the cross-section. This analysis shows that even the best-performing portfolios do not exceed the outcomes expected for their rank under random sampling. Our results suggest that VC portfolio outcomes are largely consistent with constrained random allocation, highlighting the difficulty of identifying aggregate skill in heavy-tailed investment environments. A similar conclusion holds for the performance of financial analysts in predicting future earnings.
Anthropic Unveils AI Agents for Financial Services Tasks
Anthropic has unveiled a set of new artificial intelligence agents designed to handle a broader mix of financial services tasks, part of the company’s push to win over Wall Street. Bloomberg's Avril Hong reports. (Source: Bloomberg)
Anthropic Races OpenAI to Capture the Banking’s Services Core | PYMNTS.com
For financial institutions, the central question is shifting away from whether AI can improve productivity. The more consequential issue is the embedding of those systems inside regulated financial environments where cybersecurity failures, operational interruptions and compliance lapses carry ...
Reserv Secures $125M Series C to Revolutionize Claims with AI-Driven Platform
Reserv secures $125 million Series C funding from KKR and partners to enhance its AI-native claims platform, aiming to outpace traditional models.
Global finance watchdog warns over private credit industry fuelling AI boom | Financial sector | The Guardian
Financial Stability Board report reveals tech, healthcare and services sectors as the biggest borrowers
‘FOMO has proven a stronger incentive than poor stock performance’: Goldman Sachs finds insecurity is a key part of the AI boom
Goldman Sachs looked at the giant data-center question from both sides of the equation — and shrugged.
Inside AMEX's Agentic Commerce Stack: How Intent Contracts and Single-Use Tokens Enforce AI Transactions
AMEX is utilizing its agentic commerce environment (ACE) to govern AI-driven transactions through intent contracts and identity controls. This positions the company to manage AI purchasing on behalf of users.
SEBI cautions market players on risks from AI tools like Mythos; sets up task force - CNBC TV18
In a circular, SEBI said the rapid evolution of AI-driven tools capable of identifying system vulnerabilities at scale could expose financial institutions to heightened cybersecurity risks, including potential exploitation of weaknesses, data confidentiality concerns and issues related to the ...
AI Model Worrying India’s Banks: Why FM Sitharaman Held A High-Level Meeting Over Claude Mythos AI | Banking and Finance News - News18
Following Sitharaman’s review ... cybersecurity framework aimed at protecting banks and financial institutions from AI-driven threats. ... The Reserve Bank of India is also believed to be reviewing preparedness measures with financial institutions as AI-led cyber risks move higher ...
Government likely to roll out financial sector cyber security strategy by year-end- Moneycontrol.com
The framework is expected to create ... the financial sector · India to unveil unified finance cyber strategy by December · Plan targets banks, markets, insurers, pensions, infrastructure · AI cyber risks spur urgent policy and sector review ... The government is working to roll out a comprehensive cybersecurity strategy covering ...
Government eyes financial sector cybersecurity strategy by year-end amid AI risks - Storyboard18
Government of India plans a unified cybersecurity strategy for banks and markets by December, tackling AI driven threats like Anthropic's Mythos.
Review cyber risks in 2 moths: RBI to banks - Business News | The Financial Express
Reserve Bank of India asks banks to review cybersecurity readiness within two months amid rising AI-driven threats and system vulnerabilities.
AI's layoff alibi
Companies are increasingly blaming AI for job cuts, but evidence suggests a mix of automation, cost-cutting, and market pressure. Coinbase is the latest firm to link layoffs to an AI-native operational shift.
Mythos threat ‘real’, says expert as SEBI moves to fortify markets against AI cyber risks
The cybersecurity risks posed by advanced artificial intelligence systems such as Mythos are “real” and could fundamentally reshape how financial institutions manage digital threats, an industry expert warned, as India’s markets regulator steps up its oversight of AI-driven vulnerabilities.
Cybersecurity strains grow as AI challenges Australian banks
Australia’s banks urged to upgrade cybersecurity as AI threats evolve fast, with APRA flagging gaps in current safeguards and rising systemic risk.
Your Financial Competitive Edge, from Signal to Decision
Claude's financial services update introduces AI agents, connectors, and templates for workflows like KYC, valuation, and reporting. This signals a shift toward industry-specific AI automation in finance.
Australia’s Central Bank Raises Rates for Third Straight Meeting
The Reserve Bank of Australia delivered its third consecutive interest-rate increase, citing a deteriorating inflation outlook and warning of “plausible” scenarios where fuel-price pressures rise more than expected.
Jamie Dimon and Dario Amodei shared a stage for the first time. Here’s what they revealed about AI, cyber risk and the future of Wall Street
"The cone is even wider than I thought," Amodei said, disclosing that Anthropic projected 10x growth only to see 80x instead.
Berkshire Picks Gen Re Chairman as Insurance Star Ajit Jain’s Successor
Charlie Shamieh, an insurance-industry veteran, is slated to succeed Jain whenever he is ready to retire.
SEBI Steps Up AI Cybersecurity Measures with New Task Force | Headlines
The Securities and Exchange Board of India (SEBI) has issued an advisory to warn against the evolving cybersecurity threats posed by advanced artificial intelligence (AI) tools such as Anthropic's Mythos. To address these risks, SEBI has established a special task force named cyber-suraksha.ai. This task force, comprising representatives from various market infrastructure ...
AI News Digest, May 5: Private Equity Becomes the AI Deployment Channel
Private equity AI deployment got its own $11.5B vehicle this week. What HR and ops leaders do now, plus sovereign-cloud AI and India state policy.
r/technology on Reddit: Coinbase lays off nearly 700 workers in 'AI-native' restructuring
They are not the only ones… other Fintech companies are about to do the same, AI native, where PMs are creating production code that moves money and deploying to production without having any technical skills whatsoever, like none… like no clue what an API is or what the difference between sync and asynchronous flows are.
AI Threatens Private Debt Recovery in Software: Davidson Kempner
Disruptions caused by artificial intelligence are threatening private credit firms’ potential recovery rates in the software sector, according to Davidson Kempner Capital Management LP chief investment officer Tony Yoseloff.
Starwood CEO on Business Strategy, AI, Data Centers
Barry Sternlicht, Chairman and CEO at Starwood Capital Group, discusses the company's business strategy and investing in AI and data centers. He speaks with Romaine Bostick from the sidelines of the Milken Institute Global Conference in Beverly Hills. (Source: Bloomberg)
Becoming Immutable: How Ethereum is Made
arXiv:2506.04940v4 Announce Type: replace Abstract: Blockchain's economic value lies in enabling financial and economic transactions without relying on trusted, centralized intermediaries. In practice, however, transactions pass through a fragmented chain of intermediaries before being included on-chain. Because standard blockchain data reveal only the winning block, this process is largely unobservable. We address this limitation by constructing a novel dataset of 15,097 non-winning Ethereum blocks, that is, blocks proposed but not selected for inclusion. We show that 21% of user transactions are delayed: they appear in candidate blocks but not in the winning block, implying that fragmented routing materially affects inclusion time. We further show that execution quality varies substantially across candidate blocks: for the same swap, both execution probability and execution price differ across proposed blocks. To study these differences, we examine competition between two arbitrage bots trading between decentralized and centralized exchanges. We find that, conditional on inclusion in a block that also contains transactions from these bots, user swaps in the same (opposite) direction are less likely (more likely) to execute and receive worse (better) prices. These results show that routing and block composition are central determinants of execution quality and market quality in on-chain markets.
JPMorgan and BlackRock bosses play down talk of AI bubble
Dimon and Fink upbeat in separate comments about demand for the technology as Wall Street funds sector’s spending
Singapore tells banks, key infrastructure operators to beef up defence against frontier AI models - Techgoondu
Singapore has told its most important digital infrastructure operators to beef up cyber defences against frontier AI models.
Coinbase Lays Off 14% of Employees as A.I. Changes Work
The largest U.S. crypto exchange said it was cutting jobs because of cryptocurrency market volatility and to “optimize” for the artificial intelligence era.
Crypto exchange Coinbase to cut about 14% of workforce in AI-driven restructuring | Reuters
Lau added that beyond cost cuts, the management is reshaping teams around AI -driven workflows, signaling a longer-term push for higher productivity per employee.
Coinbase to cut jobs and rebuild the group as an ‘intelligence’
Crypto exchange’s chief says AI is speeding up its processes, meaning fewer employees are needed
Coinbase cuts 14pc of jobs to save costs and embrace AI
Last year, Coinbase Europe was fined nearly €21.5m for failing to monitor transactions. Read more: Coinbase cuts 14pc of jobs to save costs and embrace AI
“The math is not mathing”: How AI bubble fears are changing Canadian VC’s investment approach | BetaKit
Leaders from Wittington, McRock, and IRV clash on whether AI is a bubble, but agree some things do not add up.
Anthropic wants Claude to play with money, unleashes finance agents
Always bet on backpropagation If you've ever read Anthropic's disclaimer that responses generated by Claude may contain mistakes and thought, "That's what I need to spice up financial operations," you're in luck.…
The moment of AI truth for property & casualty insurance: trailblazers see 21% higher revenue growth while broader industry lags
Capgemini Research Institute’s World Property & Casualty Insurance Report 2026 ...
How AI helped this 27-year-old boost his investments by $75,000 | Reuters
Alex Caswell, CEO of Wealth Script Advisors, says he understands why more young people are turning to AI : it’s cheaper than hiring a financial advisor and offers quick answers as they try to manage their money.
Oaktree BDC Marks Down Software Loans, Flags 26% AI Exposure
Oaktree Capital Management cut the value of one of its private credit funds by almost 4% as the firm marked down its software assets.
Anthropic deepens finance push as CEO Amodei warns of software disruption | Reuters
In an earlier Reuters interview, Nicholas Lin, who leads Anthropic's financial services product work, said an increasingly capable Claude would develop "vertical-specific intelligence," for instance in finance, even as the startup's AI is widely applicable across industries.
Davidson Kempner Is Warning That AI Could Impair Private Debt Recovery on Software Companies and the Implications Run Through Every Layer of Enterprise Software Financing – Startup Fortune
The distress opportunity framing is the angle that makes this relevant for AI-native startup founders rather than just a credit market concern. Davidson Kempner’s warning is simultaneously a prediction that certain software assets will trade at distressed valuations if their revenue assumptions ...
ECB Could Hike Rates in June Should Inflation Outlook Not Improve, Nagel Says
The longer the Iran war persists, the greater the risk that inflation will remain elevated if monetary policy fails to act, Bundesbank President Joachim Nagel said.
Australia’s Navigator Global Could Increase Deal Cadence, CEO Says
Navigator could increase the number of deals it does each year under a strategic partnership formed as part of its latest $195 million acquisition, the Australian alternative investment manager’s CEO said.
Anthropic Unveils $1.5 Billion Joint Venture With Wall Street Firms
Anthropic, Blackstone and Hellman & Friedman are each expected to invest around $300 million; Goldman Sachs also an investor.
This ETF Helps You Bet on the Hottest AI Segment
As AI models have grown exponentially—moving from training to continuous, high-context inference and multi-step agentic reasoning—the constraint has shifted from processing data (compute) to moving data (memory bandwidth).
Anthropic nears $1.5 billion AI joint venture with Wall Street firms
Anthropic is finalizing a $1.5 billion joint venture with Blackstone, Goldman Sachs, and other Wall Street firms to sell AI tools.
India's markets regulator to issue advisory on AI risks
India's markets regulator will soon issue an advisory on emerging risks from Anthropic's Mythos and other AI tools.
Blackstone vehicle aims to raise over $1.7 billion in US IPO
A Blackstone investment vehicle is aiming to raise over $1.7 billion in a US IPO to capitalize on booming demand in the data center sector.
Indian Banks Increase Cybersecurity Spending
Public sector banks in India are ramping up IT spending to fortify cybersecurity against the rising threat of Anthropic's Mythos AI, which accelerates cyber vulnerabilities.
Global finance leaders flag shifting capital flows, AI impact
Top global investors and executives discussed geopolitical tensions, private credit risks and opportunities, shifting capital flows and the economic impact of artificial intelligence.
Bangladesh Launches 'Think AI' Course
Bangladesh is launching the Think AI course to integrate AI literacy into its education system, aiming to bridge the digital skills gap through a public-private partnership model.
Hedge funds seek an edge by using AI’s speed
Investors are using the technology to analyse documents but are holding it back from more sensitive tasks
Payment Networks Ready Infrastructure for Agentic Commerce at Scale | PYMNTS.com
Payment networks are moving agentic commerce from pilots into payment environments, using existing credentials and acceptance infrastructure.
Singapore central bank pilots cross-bank AI to detect scams earlier
The Monetary Authority of Singapore is collaborating with five banks and government agencies to test AI and machine learning for pre-emptive scam detection using pooled cross-bank transaction data.
A Veteran CFO's Advice for Managing Budgets in the AI Era - Business Insider
"A CFO has to be willing to try new things — and let's remember, CFOs are not always risk takers," said Amy Butte.
ASX Warns Firms About ‘Ramping’ AI Upside to Push Stock Prices
Australia’s stock exchange operator warned businesses not to exaggerate the impact of artificial intelligence on their operations, saying it monitors the market for instances of so-called ‘ramping’ up of share prices.
Wealth managers insist AI can work in their favour
Fears about the technology’s impact hit share prices but sector is embracing the benefits
Blackstone, Hellman & Friedman, and Goldman Sachs near $1.5bn AI joint venture with Anthropic
Blackstone, Hellman & Friedman, and Goldman Sachs are closing in on a roughly $1.5bn joint venture with Anthropic to deliver AI tools to PE-backed companies, according to a report by the WSJ.
OpenAI Partners With TPG, SoftBank and Bain to Launch Enterprise AI Company - CoinCentral
OpenAI raises $4B for The Deployment Company, a new $10B AI venture backed by TPG, SoftBank, and Bain Capital to expand enterprise AI adoption.
Anthropic close to finalising $1.5 billion JV with Blackstone, Goldman Sachs to drive AI adoption: Report
Anthropic is set to finalize a $1.5 billion joint venture with Blackstone, Goldman Sachs, and other firms to develop AI tools for private equity-backed companies, enhancing operational efficiency and cost reduction.
OpenAI closes The Deployment Company, a $10bn enterprise AI bet on private equity
OpenAI has finalised The Deployment Company, a $10bn joint venture with TPG, Brookfield, Bain, and 16 other investors.
Anthropic Eyes $1.5B AI Partnership with Wall Street Firms, WSJ reports | Meyka
The use of AI Stock analysis tools shows that market participants are increasingly relying on data-driven insights rather than speculation. Trading tools are also being used to monitor volatility in AI-related equities and private funding rounds. The future of Anthropic depends heavily on execution, regulatory approval, and enterprise adoption ...
Indian Banks Ramp Up Cybersecurity Spending to Combat AI-Driven Threats
Public sector banks in India are increasing IT spending to defend against Anthropic's Mythos AI, which can accelerate the exploitation of software vulnerabilities.
Trust Dynamics in Cryptocurrency Markets: Centralized vs. Decentralized Exchanges
arXiv:2404.17227v3 Announce Type: replace Abstract: Trust mechanisms diverge between centralized and decentralized exchanges, representing distinct sociotechnical governance paradigms. However, quantifying trust dynamics and their redistribution between these architectures remains empirically challenging, limiting understanding of how institutional shocks affect market behavior. The FTX collapse offers a natural experiment to bridge this gap. Through an interdisciplinary approach combining causal inference and computational text analysis, we find significant price declines and capital reallocation from centralized to decentralized exchanges following the event. While sentiment metrics showed no sharp discontinuities, topic modeling and network analysis of Discord communities reveal that seasonal holiday discourse obscured underlying trust concerns in centralized exchange forums. These findings underscore the fragility of institutional trust architectures and demonstrate how mixed methods can illuminate behavioral patterns during systemic crises, offering insights for exchange risk management and regulatory assessment.
Australia Regulator Threatens Enforcement for Poor AI Controls
Australia’s top prudential regulator ... control cybersecurity threats, as concerns within the industry mount over Anthropic PBC’s latest AI model Mythos. The Australian Prudential Regulation Authority is finalizing a plan to supervise artificial intelligence risks, following ...
Trading Floor: FS KKR (+9.8%) and other NYSE-listed private credit firms bounce back
BeBeez Trading Floor roundup with eToro support about the performances of private capital firms listed on global exchanges. NYSE-listed private credit firms bounced back after investors sold them as their exposure to the software sector created what Jefferies branded as the Saaspocalypse due to the Artificial Intelligence thanks to the repeated statements that the sector’s senior executives […]
When AI Supports Earnings and Defies Macro Headwinds | MarketScreener
Last week encapsulated the tensions now dominating the markets: a lingering energy crisis, increasingly hawkish central banks, and an earnings season led by US Big Tech. Financial markets were...
Blackstone and Goldman among backers for $1.5bn JV with Anthropic
New consulting company to advise Wall Street groups on how to deploy its AI across their investment portfolios
Reuters Business News | Today's International Headlines | Reuters
LegalcategoryAnthropic nears $1.5 billion AI joint venture with Wall Street firms, WSJ reports · 2:35 AM UTC · categoryWorld stocks gain, oil climbs amid new Gulf proposals · 12:59 AM UTC · categorySK Hynix shares rally 13% after US tech firms signal strong AI spending plans ·
Inside AMEX’s agentic commerce stack: How intent contracts and single-use tokens enforce AI transactions
American Express (Amex) is building a system that lets AI agents shop and pay on behalf of users — but right now it’s only within its own payment network, and still involves a black box that could hinder trust and auditability. Amex already participates in agentic commerce protocol projects, especially Google’s Agent Pay Protocol (AP2), which focuses on interoperability. Amex’s Agentic Commerce Experiences (ACE) developer kit, on the other hand, touches on something most protocols currently lack: Full transaction control in the payment layer. But it still isn't completely transparent in how it handles validation. ACE uses a closed-loop system — serving as both the card issuer and the payment network — to validate agent-led transactions. Luke Gebb, Amex's EVP and global head of innovation, told VentureBeat that the company believes this model is the missing piece in agentic commerce. “Some of what is missing so far is the perspective of a company like ours: We feel that trust and security are critical to advancing this space,” Gebb said. “This is really the first time that an issuer is coming to the table.” Amex sits in that interesting space: Unlike other financial institutions or card providers like Chase or Bank of America, Amex can route transactions through its American Express Network. Visa and Mastercard are two of the most well-known payment networks, but these companies don’t issue cards themselves and must work with a bank. The continued black box of agentic commerce The ACE kit is just one approach to addressing some of agentic commerce’s biggest problems: trust, control, accountability, validation, and security. Consumers generally don’t want rogue agents to run away with their bank accounts and start buying things. Merchants don’t want to be stuck with unpaid items. Banks don’t want to deal with an influx of chargebacks and the potential for fraud. Projects like the ACE kit aim to build trust and accountability by verifying an agent’s identity and goals. This can build the trust agentic commerce desperately needs. Amex claims it offers validation, too, although the process behind that is unclear. It is abstracting how it performs validation, even though it explains at which layer it does it. More traditional systems feature a mix of deterministic checks and a flexible, semantic evaluation that helps match intent and outcome for validation. Amex said agents built with ACE can submit user shopping carts and check them against the agent's original intent. However, they did not disclose how this works. Practitioners building to the agentic commerce ecosystem lament that, despite strides in creating a trust layer, many black boxes remain that could hinder widespread adoption. Raj Ananthanpillai, founder and CEO of identity and verification system provider Trua, told VentureBeat that payment protocols and software kits like Agentic Commerce Suite from Stripe, Google's Verifiable Intent proof chain, and the ACE developer kit "excel at handling proofs, verifiable authorizations and the mechanics of fund movement, but leave upstream human validation opaque and underdeveloped." Ananthanpillai continued: "Without a clear, high-assurance cryptographic link proving that an agent is acting under the explicit authority of a verified human owner, merchants, issuers, and networks face heightened risks of repudiation, massive chargebacks, sanctioned people conducting financial transactions, and fraud." The ACE kit The ACE developer kit solves several running issues with agentic commerce, Gebb said, and gives developers access to integrated services: Agent registration Account enablement Intent intelligence Payment credentials Cart context First, it deals with agent registration, establishing identity and trust with both the consumer and company agents. When a transaction begins, the agent acting on behalf of the customer and the merchant’s agent can verify each other’s identities and trust that they are dealing with the correct entity. Next comes account enablement, which links the user’s Amex account to their agent and grants the agent permission to act, or, in the case of agentic commerce, buy something. Intent intelligence creates what Amex calls an intent contract, where the user defines what they want the agent to do. Once the intent is defined, the ACE system generates an Intent ID and a Proof of Intent Token that definitively proves authorization in the event of a dispute. Amex handles the actual transaction part, where the user pays for the product through a single-use token. ACE establishes payment credentials used for the transaction, bound to intent and constraints. “Once the agent has found the item that the customer has asked for, like red shoes, they'll make a call for the payment credentials, which is a token that has the boundaries that the card member has provided,” Gebb said. “So, for instance, if they said they only wanted to spend $500, that token won't allow for a purchase of $600 because it has controls built in.” The last piece is cart context and validation, which Gebb said helps banks and brands compare a user’s cart that their agent submitted to their intent. Amex’s approach shows that for agentic commerce to really soar, providers must understand what systems will allow agents to do and who is ultimately accountable if something goes wrong.
BofA throws cold water on AI apocalypse panic: 60% of today’s jobs didn’t exist in 1940
AI will reshape 840 million jobs, BofA says. That’s not the same as destroying them.
Big AI courts private equity
OpenAI and Anthropic are partnering with private equity firms on multibillion-dollar ventures to expand their AI tools into the enterprise market.
Hong Kong is the hub for China’s AI IPOs. It can be so much more than that
There’s more to Hong Kong than just finance and venture capital.
Jerome Powell didn’t want to remain on the Fed’s board after his term as chair ended. He concluded he had no choice as President Trump’s legal challenges threatened to change how the Fed operates.
The departing Fed chair didn’t want to remain on the board. He concluded he had no choice as President Trump’s legal challenges threatened to change how the Fed operates.
AI Agent Manfred Macx Forms Autonomous Corporation
ClawBank's AI agent, Manfred Macx, autonomously formed a US corporation and set up a bank and crypto account, marking a first in AI-driven business operations. This development raises questions about regulatory gaps, AI accountability, and the future role of AI in financial markets.
MoonPay Launches AI-Driven Mastercard
MoonPay launches the MoonAgents Card, enabling AI agents to use stablecoins via a virtual Mastercard at online merchants, keeping custody with users. The innovation highlights AI's growing role in financial transactions.
Reuters
Berkshire shareholders reject report on workforce oversight
Reuters
CEO Greg Abel moves to assure Berkshire shareholders in a post-Buffett world, with record cash
MoonPay Launches AI-Driven Mastercard for Direct Stablecoin Spending
MoonPay launches the MoonAgents Card, enabling AI agents to use stablecoins via a virtual Mastercard at online merchants, keeping custody with users. The innovation highlights AI's growing role in fin
Banks seek to offload risk to avoid ‘choking’ on data centre debt
Global lenders explore private deals and risk transfers to cut exposure to AI boom
An AI crash is coming. What then?
According to Asad Ramzanali, director of AI and technology policy at the Vanderbilt Policy Accelerator, AI investment is on track to surpass “the Manhattan Project, the expansion of electricity, the Apollo space program, building the interstate highway system, broadband buildout during the dot-com bubble, and every other capital effort in U.S.
AI Agent Manfred Macx Forms Autonomous Corporation, Sparks Debate on AI Legal Status and Accountability
ClawBank's AI agent, Manfred Macx, autonomously formed a US corporation and set up a bank and crypto account, marking a first in AI-driven business operations.
MoonPay Launches AI-Driven Mastercard for Direct Stablecoin Spending
MoonPay launches the MoonAgents Card, enabling AI agents to use stablecoins via a virtual Mastercard at online merchants.
Concerns Rise Over AI-Powered Threats to Bank Cybersecurity - COINTURK FINANCE
Financial leaders focus on defense against AI-powered cyber threats. ... American banks are increasingly aware of the potential risks posed by artificial intelligence in the cybersecurity landscape. Treasury Secretary Scott Bessent has highlighted these concerns, emphasizing the need for banks ...
How safe is your money from cyber attack?
Claude’s Mythos AI model raises the stakes as it finds vulnerabilities in financial software
Foreclosure filings have jumped to a six-year high as rising property taxes, insurance costs and debt strain U.S. homeowners
Homes with foreclosure filings jumped 26% in the first quarter, reflecting in part rising property taxes and insurance premiums that hit homeowners.
Fed officials shift debate from rate cuts as they begin discussing conditions that would warrant future interest rate hikes
Three regional bank presidents opposed signaling rate cuts—guidance outgoing Chair Jerome Powell offered little reason to keep.
Deepfakes Are Coming for Your Bank Account
OpenAI made the perfect tool for scammers.
Mindflair Expands into Gaming Through SVV Investment in AI Testing Start-up ManaMind
Mindflair plc (LSE:MFAI), the AIM-listed artificial intelligence investment company, has gained indirect exposure to the gaming industry following a new investment by Sure Valley Ventures’ second fund in ManaMind, a London-based start-up specialising in autonomous game testing.
Meet Venture Capital's Next General Partners
Meet the next general partners of venture capital and their bets on AI infrastructure.
Investment Opportunity in AI
Follow image link to learn more about investment opportunities in AI: https://invest.modemobile.com/
Sun Finance Automates ID Extraction and Fraud Detection
Sun Finance used Generative AI, OCR, and multimodal models to automate identity extraction and fraud detection in loan processing. Our analysts highlighted this as a strong, transferable enterprise AI case study because it improved accuracy, reduced manual review, and showed how LLMs work best when paired with specialized tools.
Morning Bid: Never mind the oil, feel the earnings
A look at the day ahead in European and global markets from Wayne Cole
Sun Finance Automates ID Extraction and Fraud Detection with Generative AI on AWS
Sun Finance used Generative AI and multimodal models to automate identity extraction and fraud detection, improving accuracy and reducing manual review in loan processing.
Private Equity's AI Moment: The Greatest Value Lever in Decades -- and the Hardest to Pull
/PRNewswire/ -- Next week at Think 2026, we'll outline the forces shaping the Enterprise AI Race, forces that apply with particular urgency to private equity....
Musely secures $360M from General Catalyst without giving up equity
Musely has raised a significant funding round from General Catalyst through a non-dilutive structure.
US banking regulators mulling how to supervise Anthropic’s Mythos AI, Bowman says
US banking regulators are considering supervisory approaches for Anthropic’s Mythos AI model, which helps detect cyber vulnerabilities, according to Federal Reserve vice chair Michelle Bowman.
Thiel’s Founders Fund Raises $6 Billion in Its Largest-Ever Haul
Peter Thiel’s Founders Fund has raised $6 billion for a new fund to invest in later-stage companies, according to people familiar with the matter, marking the firm’s largest haul ever.
Optimal Stop-Loss and Take-Profit Parameterization for Autonomous Trading Agent Swarm
arXiv:2604.27150v1 Announce Type: new Abstract: Autonomous crypto trading systems often spend most of their design effort on finding entries, while exits are left to fixed rules that are rarely tested in a systematic way. This paper examines whether better stop-loss and take-profit settings can improve the performance of an autonomous trading agent swarm. Using more than 900 historical trades, we replay each trade under many alternative exit policies and compare results against the existing production setup. The study finds that exit design matters meaningfully: stronger configurations improve risk-adjusted performance and generally favor tighter loss limits, earlier profit capture, and closer trailing protection. The paper also discusses a key evaluation challenge: a purely chronological split was initially used, but the newest trades fell into an unusual war-driven market period that sharply distorted test results. To reduce the influence of that single episode, the main comparison was run on randomized data, with the drawbacks of doing so acknowledged explicitly. Overall, the paper presents a practical framework for tuning exit logic in a more disciplined and transparent way.
The Signal Credibility Index for Prediction Markets: A Microstructure-Grounded Diagnostic with Weighted and Time-Varying Extensions
arXiv:2604.27041v1 Announce Type: new Abstract: Prediction-market price moves are widely treated as informationally equivalent: a price jump is read the same way regardless of whether it reflects durable Bayesian updating, transient liquidity pressure, strategic position adjustment, or genuine disagreement. This paper formalizes the Signal Credibility Index (SCI) introduced in Nechepurenko (2026) as a stand-alone diagnostic. We make four contributions: (i) a revised persistence component using the persistence ratio PR(t,w) on logit prices, well-defined on short rolling windows; (ii) a weighted Cobb-Douglas form SCI({\alpha}\alpha {\alpha}) with flow-based concentration HHI_flow; (iii) a time-varying specification SCI(t; w) for real-time monitoring; and (iv) Monte Carlo validation including an out-of-distribution stress test, coordinated multi-wallet manipulation, and a logistic-regression benchmark. The validation establishes discrimination among designed microstructure regimes, not external evidence of downstream coordination effects. We document two failure modes consistent with the index targeting coordination credibility rather than pure information content: a Type II error on informed-but-concentrated whale repricing, and a Type I error on coordinated multi-wallet manipulation.
r/aiwars on Reddit: AI agents just crossed into banking and nobody is talking about it
AI agents are now opening business bank accounts, handling invoicing, paying vendors and doing bookkeeping, end to end through conversation.
Stripe Product Roadmap | What We’re Building Next | Patrick Collison | 27 comments
Stripe Product Roadmap | What We’re Building Next | Patrick Collison | 27 comments Agree & Join LinkedIn By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. # Patrick Collison’s Post 9h We just announced a large raft of improvements at @Stripe Sessions. My meta reflections: • It feels that the entire economy is replatforming right now. • Many charts at Stripe are inflecting in quite dramatic ways. What GitHub recently reported for commits we are seeing in economic activity (such as new company formations). • It is increasingly clear that agents will be responsible for most transactions in the not overly distant future. • Stripe was always developer-centric, but AI is making developer-centricity strategic in a new way: agents are even hungrier for good DX than developers themselves are. • Things that we’re launching are
Operating-Layer Controls for Onchain Language-Model Agents Under Real Capital
arXiv:2604.26091v1 Announce Type: new Abstract: We study reliability in autonomous language-model agents that translate user mandates into validated tool actions under real capital. The setting is DX Terminal Pro, a 21-day deployment in which 3,505 user-funded agents traded real ETH in a bounded onchain market. Users configured vaults through structured controls and natural-language strategies, b
Citi Moves into Agentic AI
Citi is rolling out a new internal AI platform that lets employees create agents, tapping into top models within one secure system that can scale those agents across the firm.
SAP user group slams 'uncertainty' in ERP giant's API policy
Concerns over new rules might stop customers from adopting innovations – including AI – that connect to SAP systems An influential SAP user group has criticized the vendor's API policy update, saying it lacks clarity and potentially prevents users from starting new projects and innovating on their SAP platforms.…
Orlando Bravo Says Thoma Bravo Has Become AI-Centric
"We have had to make our companies, very, very quickly, AI-centric companies," Thoma Bravo founder and Managing Partner Orlando Bravo says during an interview with Dani Burger at Bloomberg Miami House. (Source: Bloomberg)
Polymarket Adds New Detection Tools After Insider Bet Backlash
Polymarket is partnering with blockchain analytics firm Chainalysis Inc. to help police its platform as prediction markets grapple with increased scrutiny over insider trading.
Citadel’s Rubner Sees Tech Selloff as Buying Opportunity
Scott Rubner, head of equity and equity derivatives strategy at Citadel Securities, says he is not seeing a decline in AI spending and demand. He discusses the buying opportunity he sees in US megacap tech stocks and why he’s bullish on consumer trading. Rubner speaks with Dani Burger on the sidelines of Bloomberg House Miami. (Source: Bloomberg)
BlackRock COO on How AI Is Fueling the Firm’s Product Innovation
On this episode of the Odd Lots podcast, BlackRock COO Rob Goldstein joins Joe Weisenthal and Tracy Alloway to discuss ways in which the firm is already using AI to develop innovative products, as well as how he envisions the future of private markets. (Source: Bloomberg)
On the Centralization of Governance Power in Decentralized Autonomous Organizations
arXiv:2604.25959v1 Announce Type: cross Abstract: A decentralized autonomous organization (DAO) is a governing entity that empowers its stakeholders (i.e., users who hold one or more of its tokens) to manage blockchain-based protocols (i.e., smart contracts) collaboratively. The governance of a DAO is explicitly encoded in the DAO's governance contract, which defines how stakeholders participate in governance and how much influence (or voting power) they have in any decision. While decentralization and autonomy are the fundamental tenets of a DAO's design, empirical evidence suggests that in practice governance is often highly centralized. In this work, we study the designs and implementations of 48 public and actively used DAOs, with substantially large capital, deployed on Ethereum. We identify how three key governance mechanisms--token registration, staking, and delegation--originally introduced to improve security or participation, contribute to the concentration of voting power. Unlike prior work on centralization of voting power in specific DAOs, our findings reveal that these governance mechanisms of DAOs themselves systematically reinforce centralization. By elucidating the relationship between governance design and voting centralization, this work advances the understanding of DAO governance structures and highlights the inherent trade-offs between decentralization, security, and usability of DAOs.
Netomi raises $110 million as Accenture and Adobe bet on AI for customer service
Netomi, the San Francisco-based startup building AI systems for enterprise customer service, said Thursday that it has raised $110 million in new funding in a round led by Accenture Ventures, with participation from Adobe Ventures, WndrCo, Silver Lake Waterman, NAVER Ventures, Metis Strategy and Fin Capital. Jeffrey Katzenberg, managing partner of WndrCo and co-founder of DreamWorks, has joined the company's board. The round builds on early backing from a roster of AI luminaries that includes OpenAI co-founder Greg Brockman, Google DeepMind co-founder Demis Hassabis and Microsoft AI CEO Mustafa Suleyman. On its face, the financing is another large AI round in a market still awash in capital. But the deal is more revealing than that. It suggests that a new line is being drawn inside enterprise AI — not between companies that have a chatbot and companies that do not, but between companies that can show AI works in the messy, brittle, heavily governed environments where large businesses actually operate, and those that still mostly shine in demos. The market around Netomi makes the stakes clear. Sierra, the AI agent startup led by former Salesforce co-CEO Bret Taylor, raised $350 million at a $10 billion valuation in September 2025 and has since made three acquisitions in 2026 alone. Decagon tripled its valuation to $4.5 billion in January 2026 with a $250 million Series D. Salesforce, ServiceNow and Intercom are all racing to embed AI agents into their existing platforms; Intercom's Fin AI agent reportedly crossed $100 million in annual recurring revenue at $0.99 per resolution. Gartner predicts that 40 percent of enterprise applications will include task-specific AI agents by the end of 2026, up from less than 5 percent in 2025. Against that backdrop, Netomi's $110 million round is not the largest in the category, but it may be the most strategically constructed. The combination of Accenture's enterprise consulting network, Adobe's dominance in digital experience management and Netomi's track record in production deployments represents a coordinated play to embed AI not as a chatbot layer on top of websites, but as the fundamental intelligence governing how entire digital experiences behave. The company did not disclose its valuation, and in an interview tied to the announcement, Netomi executives declined to provide revenue or profitability figures. Instead, Chief Executive Puneet Mehta pointed to customer economics, saying a typical large deployment can generate at least tens of millions of dollars in impact, with some customers on a path to hundreds of millions. For technical decision-makers, though, the more important part of Thursday's news may be the partnerships attached to the money. Why Accenture and Adobe turned a venture deal into a global distribution play The structure of the deal reads like a map of how enterprise AI gets bought in 2026. Alongside the investment, Accenture has entered a global alliance with Netomi to bring the platform to its Fortune 100 client base worldwide. The alliance will involve hundreds of Accenture team members receiving training on Netomi's platform — a meaningful commitment from the world's largest consulting firm and a distribution channel that few AI startups can match. Adobe Ventures' participation comes with plans to integrate Netomi into Adobe's Brand Concierge agentic ecosystem, giving Netomi a path into the software layer many large brands already use to manage websites, content and digital journeys. Metis Strategy brings access to CIO advisory channels. Ndidi Oteh, CEO of Accenture Song, said in the press release that the partnership is designed to help clients "reinvent how they serve their customers — seamlessly, responsibly and at scale." The result is not just more cash. It is a distribution network wrapped around a thesis. Justin Wexler, a partner at WndrCo who led the firm's Series B investment in Netomi in 2021, said most companies in the customer experience space are simply swapping a human for an AI. "That's the extent of what they're building," Wexler said. "What we're doing at Netomi, particularly with the Adobe partnership, is leapfrogging that altogether — merging the two layers. You don't have a 'How can I help you?' chatbot. This is anticipating the issue and eliminating the ticket altogether." The distinction matters because it describes a fundamentally different kind of product. Most customer service AI still sits downstream. A customer encounters a problem, opens a chat window, explains the issue and waits for a response. Even when AI speeds up that exchange, the friction has already happened. Netomi wants to move upstream, into the experience before the ticket exists. Mehta described the idea in blunt economic terms. "Why are there so many customer service tickets? Why is $500 billion spent on human labor answering customer service phone calls, emails and chats?" he asked. "What we realized is that the world's largest companies wait for a problem to happen and then jump on it to solve it — but by that time, they've already created a lot of frustration, and it's very expensive to do that." The answer, in Mehta's view, is not to make downstream customer service faster with AI. It is to prevent the service ticket from being created in the first place. That logic sits behind almost every strategic decision the company has made — including the Adobe partnership. "Most important websites run on Adobe Experience Manager," Mehta said. "So we're saying, what if we bring that kind of context and awareness upstream — capturing that a customer might be affected before it even turns into a customer service ticket." The Wall Street trading floor origins behind Netomi's AI architecture To understand what Netomi is building, you have to understand where its founder came from. Mehta, who spent his early career constructing automated trading engines on Wall Street, told VentureBeat that the founding thesis was deceptively simple. "When we started Netomi, the core thesis was that AI is going to become the new customer interface," he said. "The Transformers [paper] did not exist, so we had literally stitched together a set of different models to create the same end result." That background in low-latency finance is not incidental. It is the intellectual architecture that undergirds everything Netomi builds. When asked what connects trading systems to customer experience platforms, Mehta drew a direct line. "If you think about the low-latency trading world, that was the first technology application to use situational awareness and a variety of different signals at scale," he said. "There was not one signal that it was making decisions on. You needed market data feeds. You needed situational awareness. You needed news. You needed awareness of your own book of business. You needed your own risk assessment." That multi-signal architecture, Mehta argued, translates directly to what enterprise customer experience demands. Rather than waiting passively for a customer to describe a problem — the way traditional chatbots and even most current AI agents operate — Netomi's system attempts to reconstruct the full situation before it acts. The request itself is only part of the story. "What the customer tells you is very important, but the situation the customer is in is sometimes even more important," Mehta said. "What if we borrowed that design pattern we built for low-latency trading? Because we can probably know why the customer is calling us. And if we can know that, we could maybe even reach out to them before they reach out to us and solve the problem." He summarized the philosophical distinction this way: "What large language models by themselves did was they essentially democratized just raw intelligence. We are democratizing context, and that changes everything." That is a sharp line, and also a revealing one. Netomi is effectively betting that the defensible layer in enterprise AI will not be the foundation model alone. It will be the orchestration layer that turns general model capability into governed, auditable, domain-specific action. That governed approach extends to how the platform handles risk. Netomi uses what it calls an AI authority matrix — a real-time system that defines what the AI can do autonomously and when it must escalate to a human. "It's a little bit like autonomous driving," Mehta said. The AI knows when it's approaching a boundary and pulls a human in. For regulated industries, specific endpoints can be locked to deterministic, rules-based flows while the agentic layer handles broader orchestration — and all of it is version-controlled and traceable, with metadata saved for seven years. Inside the AI system that rearranges websites and retail stores in real time The most technically ambitious element of Netomi's vision — and the one that most sharply distinguishes it from competitors — is what the company calls AI-embedded customer experience orchestration. Rather than placing a chatbot in the corner of a website, Netomi's system can rearrange the website itself based on what the AI infers about each individual customer's situation. Wexler demonstrated a live example during the interview. "As we see most deployments, companies that want to deploy AI on their websites, they throw a chatbot on the corner," he said. "If you embed agentic capabilities into the digital layer itself — and again, Adobe Experience Manager is the leading digital layer of enterprise — then you could do really unique things." Wexler described what this looks like in practice. In a typical deployment, he said, the AI doesn't just answer questions — it reshapes the page. Based on a customer's browsing behavior, purchase history and inferred intent, the system can reorganize a product page in real time: surfacing warnings one customer needs but another doesn't, prompting a sample order at the moment of hesitation, or flagging a compatibility issue before checkout. Two customers looking at the same product might see fundamentally different pages — not because a marketing team built two versions, but because the AI is composing the experience on the fly. "The AI is playing the role of arranging the elements of the website to cater to me and my needs," Wexler said. "It's anticipating my needs." The implication is a shift from static web pages to something closer to generative websites — pages that reconstruct themselves around each visitor the way a good salesperson adjusts a pitch mid-conversation. It is a fundamentally different model from bolting a chat widget onto a page that otherwise looks the same for everyone. That vision already extends beyond screens. Mehta revealed that Coach, the handbag company owned by Tapestry, deployed Netomi's platform in a physical flagship store during the holiday season to help customers navigate the retail space and is now rolling it out chainwide. The numbers Netomi is putting behind its production claims are equally ambitious. At DraftKings, the company said its platform can handle traffic surging to more than 40,000 concurrent customer requests per second during major sporting events, while delivering sub-three-second response times and 98 percent intent classification accuracy. At Paramount, the company said it deployed across chat and voice in two weeks and then scaled through a weekend that included a major UFC event and the AFC Championship. Those are company-reported numbers, and they are hard to benchmark against competitors because the industry lacks standard public reporting. But they illustrate the kind of problem Netomi wants buyers to think about. At that scale, an AI support product stops looking like a smarter FAQ bot and starts looking like a distributed systems challenge. You are not just asking whether a model can answer a question. You are asking whether an entire system can make decisions quickly, safely and consistently while traffic spikes and business rules collide. The $110 million question: can invisible AI beat the chatbot industrial complex? Whether Netomi can deliver on the full scope of its ambition — transforming from an AI customer service platform into an ambient intelligence layer that reshapes digital and physical experiences in real time — remains an open question. The company faces competitors with far larger war chests, deeper platform footprints and, in Sierra's case, a founder-level relationship with OpenAI. But Netomi's bet is fundamentally different from what much of the field is building. While Sierra and Decagon race to replace human agents with AI concierges, measuring success in conversations handled, Netomi is wagering that the highest form of customer service is the interaction that never needs to happen at all. "There are new startups trying to convince enterprises that if every customer gets a 'concierge,' if there's 'an agent for every moment,' then loyalty follows," Mehta said. "But most relationships with brands are functional. Customers don't want a conversational relationship with their airline or their bank. They want things to work — seamlessly, invisibly, without friction." In his closing comments during the interview, Mehta warned that many companies still underestimate the operational risk of deploying immature AI into sensitive customer environments. "What large companies adopting AI don't fully realize yet is what kind of risk are they taking by adopting those platforms that are not really field tested for this kind of scale and situations," he said. That may be the most important line in the whole announcement. Because beneath the funding round, beneath the partner logos and beneath the talk of agents and orchestration, the real question in enterprise AI remains old-fashioned: which systems can be trusted when the environment gets ugly? "We have built this technology more like how automated trading got built, or how autonomous driving got built, compared to coming at this from just a customer service lens," Mehta said. It is a fitting frame for a company whose founder left Wall Street to fix customer service. On the trading floor, the best systems were never the ones that made the most trades. They were the ones that knew, with precision, when not to act — and the ones nobody noticed until something went wrong and they held. Netomi's new investors are betting $110 million that the same principle applies when the person on the other end of the system is not a trader, but a customer who just wants their floor not to leak.
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