Arcesium Partners with Feynman Point Asset Management to Unified Multi-Asset Infrastructure

Arcesium, the financial technology provider, has formed a partnership with Feynman Point Asset Management (FPAM) to provide a unified infrastructure for digital and traditional assets. FPAM, an investment firm focused on digital asset markets and frontier technologies, will utilise Arcesium’s reconciliation solutions to manage its expanding investment landscape within a single ecosystem.

The partnership enables FPAM to support enhanced settlement cycles and scale its operations as the business grows. By implementing Arcesium’s Reconciliation platform, the firm gains real-time transparency and automated exception management. This allows for the rapid identification of data discrepancies and operational risks across varied asset classes, streamlining workflows and strengthening overall risk management, according to the company.

Exegy Enhances nxAccess Trading Engine with 71% Latency Reduction

Exegy, provider of capital markets trading technology, has announced a major update to its FPGA-based trading engine, nxAccess. The release introduces a 71% reduction in execution-stack latency, measured from start-of-packet to start-of-packet on the switch. This performance boost is designed to provide deterministic execution for firms operating in highly volatile environments where traditional hardware constraints can lead to “latency leakage” and missed pricing opportunities.

The update features a new Session Override capability, allowing firms to monitor session performance in real-time. This tool enables trading algorithms to bypass static configurations and pivot to the fastest available session or network link at the moment of execution. By turning connectivity into a dynamic asset, firms can adapt to fluctuating exchange latencies throughout the trading day without requiring complex hardware re-coding.

In addition to speed improvements, the latest version of nxAccess expands connectivity options to include UDP-based multicast and raw Ethernet frame transmission. These additions allow for immediate integration with ultra-low latency wireless and private links. As an off-the-shelf FPGA platform, the enhanced nxAccess aims to provide firms with the speed of custom hardware logic while maintaining the deployment flexibility and shorter development cycles of software-led solutions.

TS Imagine Launches Real-Time Integrated Swap Management Module

TS Imagine has introduced a new module to its cross-asset platform, offering a fully integrated system for managing swap economics and risk. Designed for synthetic prime brokerage desks and asset managers, the solution replaces traditional end-of-day reconciliation with a unified, real-time intraday view. By consolidating swap positions and corresponding cash equity hedges within a single system, the module eliminates manual processes and significantly reduces operational overhead.

The module is available across TS Imagine’s existing suite, including SwapSmart, RiskSmart+, and TradeSmart. It provides users with immediate visibility into risk and hedge discrepancies while offering native P&L attribution. This architecture supports a broad range of instruments, such as total return swaps (TRS), basket swaps, and CFDs, and has already been validated by large institutional synthetic prime brokerage clients.

To assist with regulatory demands, the solution features embedded P&L attribution that automates Volcker Rule reporting. By providing full VO2 to VO11 decomposition, the system removes the need for manual overlays and streamlines compliance. This modular approach ensures that regardless of their role in the investment lifecycle, users can manage complex swap portfolios with greater accuracy and fewer reconciliation breaks.

Private Markets Analytics Datasets Unveiled by S&P Global

S&P Global has launched the S&P Global, Cambridge Associates, Mercer Private Markets Performance Analytics datasets, providing data on funds and underlying assets within the private credit and real assets sectors.

The datasets result from a collaboration introduced in 2025 and aim to assist investors with performance comparisons and risk management.

“As private markets evolve, the need for consistent, decision-ready intelligence has never been greater,” said Saugata Saha, president of S&P Global Market Intelligence and chief enterprise data officer of S&P Global. “This collaboration brings a more rigorous, standardised approach to the private markets ecosystem, transforming fragmented information into comparable intelligence that investors can use to assess performance, evaluate risk and make more disciplined investment decisions.”

The system utilises S&P Global’s iLEVEL portfolio monitoring platform and a proprietary taxonomy to aggregate and anonymise data for limited and general partners.

CME Group to Launch Avalanche and Sui Futures

CME Group is expanding its cryptocurrency product suite with the introduction of Avalanche (AVAX) and Sui (SUI) futures. Scheduled for launch on 4^th May subject to regulatory approval, these new contracts aim to provide market participants with increased flexibility and capital efficiency. The offering includes both standard and micro-sized contracts to cater to a broad range of investors, with AVAX units set at 5,000 and 500 tokens, and SUI units at 50,000 and 5,000 tokens respectively.

The expansion comes amid significant growth in CME Group’s digital asset markets, which saw March average daily volumes rise by 19% year-on-year, reaching approximately $8 billion in daily notional value. Industry leaders from Volatility Shares and Plus500US have welcomed the move, noting that it addresses the rising institutional demand for regulated, sound products in the high-growth crypto sector.

These new contracts join a growing list of recently added derivatives, including Cardano, Chainlink, and Stellar. Furthermore, CME Group has confirmed that starting 29 May, its cryptocurrency futures and options will transition to 24/7 trading. This shift is designed to enhance market accessibility and allow global customers to manage risk more effectively across evolving digital asset markets.

Regnology Extends Ascend Platform with Agentic AI to Operationalise Continuous Regulatory Intelligence

Regnology has expanded its Ascend platform with an agentic AI layer and deeper integration of its Regnology Supervisory Hub (RSH), positioning the platform as a unified environment for both regulatory reporting and supervisory oversight. The update builds on Ascend’s initial rollout in late 2025, which focused on data governance, automation and workflow orchestration across regulatory reporting processes.

The latest iteration shifts the emphasis from workflow automation to adaptive, intelligence-led operations. By embedding AI agents directly into the platform, Regnology is aiming to move reporting processes away from periodic, rules-based execution towards continuous monitoring and decision support. These agents are designed to manage workflows, analyse regulatory data and generate context-specific insights on an ongoing basis, operating on the firm’s unified regulatory data (RGD) model.

This architecture is consistent with broader industry moves towards granular, data-centric regulatory reporting, where consistency of underlying data models becomes a prerequisite for automation at scale. In this context, Ascend’s reliance on a single data foundation is intended to support both institutional reporting and supervisory consumption without duplication or transformation across systems.

The integration of RSH into the Ascend platform extends this model to regulators. Workflow agents are applied across supervisory processes such as data collection, validation and examination, while analytics agents surface key risk indicators and interpret outputs ranging from granular data points to narrative reports. The result is a more continuous oversight approach, where supervisory activities are embedded into the same data and workflow infrastructure used by reporting firms.

Regnology frames this as a step towards its long-standing Straight-Through-Reporting (STR) vision, in which regulatory reporting becomes a largely automated, end-to-end process supported by standardised data, embedded controls and real-time analytics. The addition of agentic AI introduces a layer of orchestration that can dynamically adjust workflows and prioritise risk signals, rather than relying on static reporting cycles.

“Our position at the nexus of risk, regulation, and finance gives Regnology a unique vantage point to support the industry’s evolution,” said Rob Mackay, CEO of Regnology. “Our next-gen Ascend platform is the engine of a paradigm shift transforming compliance into a single strategic command centre where high-quality data, continuous insight, and intelligent orchestration converge.”

The emphasis on convergence between reporting and supervision is notable. By extending the same AI-enabled infrastructure to both sides of the regulatory relationship, the platform aligns with emerging supervisory expectations around data lineage, transparency and near real-time access to granular information. This mirrors regulatory initiatives globally that are moving away from template-based submissions towards direct consumption of firm-level data.

“Ascend was designed as the foundation for a new era of regulatory reporting —bringing automation, transparency, and intelligence to the core of the financial operating model,” said Linda Middleditch, Chief Product Officer at Regnology. “By extending agentic AI to both regulators and the regulated on a trusted RGD data backbone, we empower the industry to move from reactive reporting to continuous intelligence for faster decisions and more resilient oversight.”

Regnology said it will progressively migrate its broader solution set onto the Ascend platform, indicating a longer-term strategy to consolidate its regulatory reporting, risk and finance capabilities within a single, AI-enabled architecture. For firms, the practical implication is a continued shift towards platforms that combine data standardisation, workflow automation and supervisory alignment—reducing fragmentation across reporting regimes while increasing expectations around data quality and control.

Bloomberg Expands MAC3 Risk Models for Enhanced Portfolio and Risk Forecasting Across Public and Private Investments

Bloomberg has expanded its MAC3 multi-asset risk models to cover private markets, extending the platform’s portfolio and risk forecasting capabilities beyond traditional public asset classes into private equity, private credit, real estate, infrastructure, hedge funds and liquid alternatives. The update reflects growing demand among institutional investors for more consistent measurement of risk across portfolios spanning both public and private investments. Bloomberg presents the expansion as a way to bring those exposures into a broader portfolio risk framework.

“Institutional investors are increasingly allocating across both public and private markets, yet risk is often measured in silos,” said Jose Menchero, Head of Portfolio Analytics Research at Bloomberg. “With these new models, MAC3 delivers a consistent, cross-asset factor framework that enables Bloomberg clients to understand and manage risk seamlessly across their entire portfolio in an increasingly complex investment landscape.”

Bloomberg MAC3 is a multi-asset class risk factor model that combines quantitative research techniques with Bloomberg security data to provide institutional investors with a unified view of risk across the portfolio. The platform currently includes more than 3,000 individual risk factors and supports risk forecasting, risk attribution, performance attribution, stress testing and optimization. The model also offers six time horizons, ranging from a responsive daily model to a stable long-term model, giving firms flexibility to align risk forecasts with different investment decision-making processes.

The new private markets capability adds MAC3 models for private asset funds, hedge funds and liquid alternative funds, allowing investors to forecast and decompose risk more consistently across public and private markets and support a total portfolio view across asset types. Bloomberg says the private fund model is constructed using dedicated private-asset factors and data on approximately 50,000 private funds covering private equity, private credit, real estate and infrastructure strategies, alongside hedge funds and liquid alternatives.

Across the alternatives fund suite, the models capture exposures across strategies, regions, sectors, styles and key macro sensitivities including rates, commodities, volatility and FX. Bloomberg says this can help investors identify shared risk drivers across managers and strategies, supporting portfolio construction, risk budgeting and governance at total portfolio level. Bloomberg’s MAC3 risk models are available to Terminal subscribers, who can use them to explore portfolio risk across public and private assets. Bloomberg PORT Enterprise customers can also license the underlying risk data, including risk factor exposures, volatilities, correlations and historical returns, with programmatic access available via API.

More broadly, Bloomberg positions MAC3 and PORT Enterprise as part of its wider buyside solutions suite, spanning research management, order and execution management, portfolio and risk analytics, trade compliance and operations. In that sense, the private markets expansion extends Bloomberg’s effort to support cross-asset investment workflows through a common data and analytics foundation.

FactSet Rolls Out AI-Backed Search, Bank Workflow Tools

FactSet has begun rolling out an artificial intelligence document search tool to 85,000 financial professionals, enabling them to access and extract insights from unstructured datasets including transcripts, filings and news.

The beta release follows previous integrations with external large language models and the appointment of a chief artificial intelligence officer, Kate Stepp.

“AI is fundamentally altering the financial landscape, and FactSet is proud to set the standard for trustworthy, impactful adoption,” Stepp said.

The tool includes a natural language agent for automated summaries and a comparison grid to benchmark different companies.

The Norwalk, Connecticut-based financial digital platform provider also unveiled an alpha version of an AI ecosystem for banking workflows. The software automates deal processes and research tasks through a collaboration with Finster AI, a company in which FactSet has also invested.

Users can generate pitch materials, memos and company profiles using natural language prompts within a secure environment. Stepp said the software delivers an agentic ecosystem that unlocks access to datasets and task automation capabilities.

It integrates with the FactSet workstation and Microsoft Office, allowing clients to incorporate proprietary data through various deployment configurations.

Clarity AI to Add New Climate Data Sets in Tie-Up With RiskThinking

Clarity AI will integrate granular climate-related data from more than three million assets into the US-based sustainability tech company’s platform as part of a deal with climate modelling provider RiskThinking.

The integration uses a digital twin platform to simulate hydrologic models across various climate scenarios and warming levels. The move is aimed at providing transparency into climate vulnerability and biodiversity impact.

“We are bridging the gap between corporate-level reporting and asset-level reality,” said Rebeca Minguela, chief executive and founder of Clarity AI. “While top-down models provide an essential high-level perspective, our partnership with RiskThinking adds the granular detail required for rigorous audit and risk analysis.”

The platform can be accessed via a web app, through artificial intelligence agents and through an API, an MCP and other connectors. It will “empower our clients to see the full picture of how climate and nature affect their portfolios”, Minguela added.

Gresham Renames S&P Data Management Acquisition Opus EDM

Enterprise data automation specialist Gresham has changed the name of the data management platform it acquired from S&P Global Market Intelligence.

Opus EDM, which was previously known as Markit EDM and IHS Markit EDM, has been integrated into Gresham’s portfolio to support data operations for financial institutions.

More than 150 firms use the software to manage about US$12 trillion in assets across global capital markets.

Gresham chief executive Mark Hepsworth said the new name heralds an era focused on product innovation, artificial intelligence enablement and managed services to reduce total cost of ownership.

Opus EDM operates alongside the existing Prime EDM product to offer buy-side and sell-side clients a broader range of technical capabilities.