DTCC and CME Secure Approval to Expand U.S. Treasury Cross-Margining for End Users

DTCC and CME Group have received approval from the SEC and CFTC to extend their U.S. Treasury cross-margining arrangement to end-user clients of dually registered broker/dealers and futures commission merchants that are common members of DTCC’s Fixed Income Clearing Corporation (FICC) and CME.

The expanded service is due to go live on April 30 and broadens a long-standing house-account arrangement into client accounts. In practice, it will allow eligible end users clearing U.S. Treasury securities through FICC and interest rate futures through CME to offset positions with opposing risk exposures across the two clearing venues. The aim is to reduce margin requirements, release capital and improve liquidity for firms active in cash Treasuries and rates futures.

The extension comes as the US Treasury market adjusts to the practical effects of expanded central clearing requirements, with market participants under pressure to manage collateral, balance sheet usage and operational complexity more efficiently. Against that backdrop, cross-margining is being positioned as a way to soften the funding and margin impact of clearing related Treasury and futures positions through separate infrastructures.

DTCC pointed to the scale of the existing arrangement in proprietary accounts. Frank La Salla, President & CEO at DTCC, said the current model has “a proven track record of creating an average of $1 billion across both clearing houses in risk offsets every day,” and added that “we expect the end-user cross margin effort will lead to additional offsets for the industry.”

CME framed the move in the context of regulatory change in the Treasury market. Terry Duffy, CME Group Chairman and Chief Executive Officer, said: “With the SEC’s central clearing mandates now taking effect, cross-margining is essential — not only for operational efficiency, but to help end users manage the real costs of compliance.”

Cross-margining between CME and FICC has been available for proprietary, or house, accounts since 2004, and the firms announced significant enhancements to the arrangement in 2024. This latest step extends comparable treatment to client business, giving clearing members a way to pass margin efficiencies on to end users where positions meet the eligibility criteria.

Under the model, FICC will designate cross-margin accounts so eligible positions can offset against CME interest rate futures. CME Clearing will allow participants to direct futures into end-user cross-margin accounts during the trading day, making those positions available for inclusion in the offset calculation.

SIX Brings European Equities Data Onchain via Chainlink Oracle Network

SIX has made equities data from its exchanges available onchain for the first time through an integration with Chainlink’s DataLink publishing service. The arrangement covers equities listed on SIX’s exchanges in Switzerland and Spain – representing over €2tn in market capitalisation – and makes the data accessible to more than 2,600 applications across 75-plus public and private blockchains within the Chainlink ecosystem. The integration is currently live on testnet, with mainnet deployment expected later this year.

SIX has been one of the more active traditional exchange groups in digital asset infrastructure, notably through its digital asset central securities depository. The Chainlink integration extends that positioning into onchain data distribution, opening potential use cases including tokenised indices, structured products, compliant DeFi applications, and prediction markets built on regulated equity market data.

The move reflects a broader trend of regulated data providers exploring blockchain-native distribution channels as tokenisation of traditional asset classes accelerates. Chainlink’s existing institutional relationships – its partners include Swift, Euroclear, DTCC, and S&P Dow Jones Indices – position DataLink as an emerging conduit between conventional market data infrastructure and onchain environments.

STS Digital Becomes First Principal Derivatives Dealer Integrated on BitGo’s Go Network

STS Digital has launched as an exchange partner on BitGo’s Go Network for Off-Exchange Settlement (OES). This integration allows institutional clients to trade digital asset derivatives directly with a principal dealer while keeping their assets secured in BitGo’s regulated custody. Previously, the OES model was limited to connecting clients with exchanges; this update enables direct dealer-to-client execution without the requirement to prefund accounts or move assets out of independent custody.

Under this arrangement, clients access STS Digital’s liquidity for over 400 tokens, including vanilla and exotic options, spot, and structured products. Regulated by the Bermuda Monetary Authority, STS Digital provides two-way pricing and global coverage via UI, API, or voice channels. The model is designed to separate custody from execution, reducing counterparty risk by ensuring that client assets remain segregated from both the dealer’s balance sheet and the exchange environment.

SimCorp Enhances Axioma Risk With AI-Powered Stress Testing

SimCorp has launched a new AI-powered capability within its Axioma Risk platform designed to automate the configuration of portfolio stress tests. By using natural language processing, the enhancement allows investment and risk managers to move from manual, multi-step workflows to AI-assisted setups. This shift reduces the time required to configure complex scenarios from hours to seconds, enabling teams to respond to market events in real time rather than being delayed by technical administration.

The tool enables users to describe macroeconomic or geopolitical concerns in plain English, which the system then translates into specific financial shocks and relevant market data. Beyond merely generating scenarios, the AI assists in identifying historical precedents and assessing the statistical plausibility of a test to ensure results are realistic. This helps managers gain deeper insights into tail risks associated with inflation, interest rate shifts, and global geopolitical instability without the need for spreadsheets or manual data exports.

Crucially, the update maintains rigorous calculation governance to meet increasing regulatory demands for transparency. While AI simplifies the initial design and iteration of stress tests, the analytical foundation remains fully auditable with human-in-the-loop approvals. This ensures that all decisions and analytics are explainable, allowing investment professionals to focus their specialized expertise on interpreting risk and making informed portfolio decisions.

BMLL Historical Data Launches on Databricks Marketplace

BMLL, the independent provider of historical market data and analytics, has made its datasets available via the Databricks platform. This move is part of the firm’s broader strategy to offer flexible delivery mechanisms, complementing its existing API, SFTP, and S3 options. The collaboration was driven by customer demand and guidance from the BMLL Client Product Advisory Board, with initial adoption already seen among major global investment management firms.

The integration allows market participants to access granular data across equities, ETFs, futures, and options directly within their existing Databricks workflows. To facilitate ease of use, BMLL has provided a series of marketplace notebooks designed by quantitative analysts. These tools enable users to evaluate the product suite with minimal integration effort and lower data storage costs, accelerating the transition from raw data to actionable insights.

The platform supports various financial functions, including execution analysis, backtesting, and market surveillance. By providing granular, normalised historical data on a scalable platform, BMLL aims to help firms perform more efficient analysis. The initiative reflects a commitment to meeting the growing industry demand for sophisticated data engineering while providing flexibility in how large-scale datasets are discovered and evaluated.

Bloomberg Introduces MYQ to Centralise Foreign Exchange Price Discovery

Bloomberg has launched MYQ, a price monitoring tool designed to aggregate and display foreign exchange (FX) quotes identified by Natural Language Processing (NLP) within Instant Bloomberg (IB) chats. The solution addresses the “swivel chair” challenge by consolidating fragmented pricing data from multiple chat rooms into a single, centralised FX curve-style format. By grouping quotes by currency pairs, tenors, and bid/offer levels, the tool provides traders with a clear overview of available liquidity and market interest prior to execution.

The tool aims to reduce operational friction and the risk of missed opportunities in fast-moving markets. Key features include a history tab for chronological price tracking and a “click-to-navigate” function that allows users to jump directly to the specific chat line where a quote originated. Advanced filters further enable participants to customise their view by currency or counterparty, streamlining the pre-trade workflow and helping users secure competitive pricing more efficiently before executing trades on platforms like FXGO.

SimCorp Builds AI-Powered Market Stress Test for Axioma Risk

SimCorp has introduced an artificial intelligence capability for stress testing market scenarios within its Axioma Risk platform.

The enhancement uses natural language processing to enable investment managers to design customised market scenarios and identify historical precedents without manual configuration. It identifies portfolio vulnerabilities and interprets risks arising from interest rate changes, currency movements or geopolitical events.

“Accelerating stress testing workflows can be game changer for investment teams,” said Ian Lumb, head of risk and performance product management. “When stress test configuration takes hours, risk teams cannot respond to events in real time. We are removing that bottleneck with AI-powered stress testing.”

The system translates macroeconomic concerns into financial shocks and provides statistical metrics to evaluate the plausibility of each scenario.

Private Direct Lending Data Added to Bloomberg 

Bloomberg has introduced a private direct lending data service to increase visibility within the private credit market.

The offering aggregates information from multiple sources to cover 15,000 active loans representing about US$1 trillion in deal flow. It consolidates US business development company filings, merger and acquisition disclosures, and news reporting to create standardised loan-level records.

“Direct lending has historically been difficult to evaluate because loan-level data is often fragmented, inconsistent and not easily comparable across the markets,” said Brad Foster, head of fixed income and private markets. “Bloomberg is extending its end-to-end credit capabilities into private markets by combining a normalised dataset of all US BDC-reported and other direct lending loans with integrated analytics and enterprise delivery so clients can analyse pricing trends, compare loan terms, and apply more consistent analysis across public and private credit.”

The platform includes specific data points such as deal size, interest rate spreads and credit health indicators to support risk monitoring and benchmarking.

Clients can access the service via the Terminal and via Data License at its web portal, with delivery options including SFTP, REST API or a cloud environment.

Avelacom Launches Lowest Latency Hybrid Route Between Amsterdam and Tokyo

Avelacom, a global provider of low-latency network solutions, has launched a new hybrid fibre and microwave route connecting Amsterdam and Tokyo. The route achieves a round-trip latency of less than 127 milliseconds, establishing a new benchmark for connectivity between Europe and Asian digital asset markets. This expansion complements the company’s existing ultra-low latency infrastructure linking London and Frankfurt to major hubs such as Shanghai and Hong Kong.

The route is specifically designed to support institutional digital asset trading, where execution speed directly influences profitability. Amsterdam has emerged as a significant hub for this activity, hosting venues like BtcTurk and a growing concentration of blockchain validator nodes. Connecting this ecosystem to Tokyo provides traders with high-speed access to global liquidity centres and price discovery on platforms such as Binance.

To achieve these speeds, Avelacom has integrated additional microwave segments into its proprietary hybrid architecture, leveraging its existing Points of Presence. By combining fibre and microwave technologies, the network minimises delays across long-distance paths. This infrastructure investment reflects the increasing demand for high-performance connectivity as Amsterdam evolves into a critical gateway for decentralised networks and global electronic trading.

TS Imagine Launches Automation 2.0 as Assets Under Service Reach $19.5 Trillion

TS Imagine has unveiled Automation 2.0, an event-driven trading platform designed to help institutional desks manage sophisticated, rule-based workflows across multiple asset classes. The launch coincides with a significant growth milestone for the firm, which now manages over $19.5 trillion in assets under service, a substantial increase from the $5.3 trillion reported in 2023. This expansion reflects the increasing demand for scalable solutions in a high-speed market environment where manual order routing often leads to operational inefficiencies.

The new platform addresses the limitations of traditional automation tools, which frequently struggle with nuanced logic and complex compliance requirements. Automation 2.0 introduces a robust rule-building environment that incorporates cost intelligence, liquidity awareness, and market calendars. By utilizing two core components – the Rule Manager for workflow design and a stateful Workflow Engine for real-time execution – the system ensures consistent, reliable handling of orders without the need for manual intervention when market conditions shift.

Furthermore, Automation 2.0 establishes the architecture for the “Execution Agent,” the next phase in the evolution of Execution Management Systems (EMS). This foundation enables the transition from predefined rule-following to autonomous, agent-driven execution. By combining real-time event processing with structured logic, the platform allows trading systems to reason and adapt across the entire order lifecycle, providing institutional desks with greater control and sophisticated fallback capabilities during execution.