LSEG to Launch Digital Securities Depository for On-Chain Settlement

London Stock Exchange Group (LSEG) has announced plans to develop the LSEG Digital Securities Depository (DSD), an on-chain settlement capability designed for institutional market participants. Scheduled for a 2026 launch subject to regulatory approval, the DSD will function as a fully interoperable infrastructure. It aims to bridge traditional and digital markets by supporting multiple blockchains and ensuring seamless interaction between existing settlement platforms and new digital frameworks.

The DSD will build upon LSEG’s existing Digital Markets Infrastructure (DMI), a Microsoft Azure-powered platform currently used for fund tokenisation. The new capability is intended to enhance collateral management and improve liquidity access across various asset classes, including equities, fixed income, and private markets. This move aligns with LSEG’s long-term vision of a financial ecosystem where the majority of securities are tokenised to increase transparency and operational efficiency.

To support the transition, LSEG is establishing a strategic partner group to integrate market feedback into the development process. This collaboration seeks to scale the infrastructure and facilitate the trading and settlement of both digitally native assets and digital representations of traditional securities. Members of this partnership group will be confirmed at a later date.

Deutsche Börse Group to Acquire Remaining 20% Stake in ISS STOXX

Deutsche Börse Group has reached an agreement to acquire the remaining 20% minority stake in ISS STOXX from the global investor General Atlantic. This transaction marks the final step in a strategic partnership that began with the acquisition of Axioma in 2019 and the subsequent integration of ISS’s ESG solutions with the STOXX index business in 2023. By moving to full ownership, Deutsche Börse aims to simplify its growth strategy and enhance market connectivity for its data, analytics, and index offerings.

The total purchase price of approximately €1.1 billion is based on a pre-agreed valuation of roughly 20 times the adjusted EBITDA of ISS STOXX. The payment will be structured in two tranches, with €731 million due in February 2026 and the balance payable in March 2026. Deutsche Börse intends to fund the buyout using existing cash and debt financing. Despite the significant investment, the group expects to maintain its AA- long-term credit rating and anticipates a low single-digit increase in cash earnings per share during the first year of full ownership.

General Atlantic’s exit is expected to be finalised by the end of March 2026, fulfilling a dual-track agreement that allowed for a private sale in the absence of an IPO. To maintain market integrity, Deutsche Börse has confirmed that ISS’s research and advisory services will continue to function under existing non-interference policies. This acquisition reinforces the Group’s focus on providing mission-critical tools for the buy-side while ensuring operational agility across its premier data brands.

Oracle Agentic Platform Targets Banks, Financial Companies

Oracle has launched a new agentic platform for the banking and finance sector, featuring applications and pre-built artificial intelligence agents designed to automate customer engagement and business processes across digital and branch channels.

The agents operate within an architecture that maintains human oversight for decision-making and ethical governance, the enterprise software and cloud services provider said.

“By combining domain specific AI, human-in-the-loop governance, and enterprise grade scalability, we’re enabling banks to drive proactive, hyper-personalised engagement while innovating responsibly and competitively,” said Sovan Shatpathy, senior vice president at Oracle Financial Services.

The system features specific tools for loan originations, application tracking and credit decision-making to improve operational speed.

Alkymi Builds Private Credit Data Extraction Tool

Alkymi, an AI-powered data specialist for private investors, has launched Alkymi Private Credit to automate the extraction of data from unstructured documents to assist with risk management and compliance within the private credit market.
The release follows projections that the private credit sector will expand to US$5 trillion dollars by 2029, increasing the complexity of manual data processing.

“Private credit is scaling faster than the infrastructure that supports it,” chief executive Harald Collet said. “Alkymi Private Credit was built specifically to address this challenge, combining AI automation with enterprise-grade controls to give firms continuous visibility into their portfolios, including covenant tracking so they can modernise operations without compromising accuracy or regulatory requirements.”

The platform centralises inbound documents like loan agent notices and financial statements to produce structured datasets for portfolio and accounting systems.

SOLVE Launches AI-Powered Confidence Score for Corporate Bond Pricing

SOLVE, the provider of fixed income market data, has introduced Confidence Score for Corporate Bonds to its SOLVE Px™ platform. This AI-driven metric quantifies pricing uncertainty on a scale of 1 to 10, providing a transparent layer to predictive pricing for over 250,000 investment-grade and high-yield corporate bonds. The tool translates complex model uncertainty into an intuitive framework, allowing professionals to assess the reliability of predicted prices for Bid, Mid, and Offer valuations.

The metric categorises scores into low, medium, and high confidence levels, which are colour-coded within the SOLVE Quotes Web application for rapid assessment. Higher scores typically reflect bonds with recent trading activity and active quoting, while lower scores indicate less liquid securities. Crucially, the tool covers the entire corporate bond universe, including highly illiquid assets and trades of all sizes, enabling risk management and trading teams to make more defensible, data-backed decisions.

Confidence Score is now integrated across all SOLVE Px delivery methods, including API endpoints, Excel add-ins, and FIX feeds. This launch follows the previous rollout of similar tools for municipal bonds and marks a further step in the company’s expansion of predictive pricing capabilities. By pairing price predictions with measurable uncertainty indicators, the service aims to reduce ambiguity and improve workflow efficiency across the fixed income markets.

Trading Technologies and Enmacc Partner to Integrate OTC and Exchange-Traded Energy Markets

Trading Technologies International (TT) has entered into an agreement with Enmacc GmbH, the market venue for OTC trading of energy and environmental commodities, to integrate their respective platforms, creating a unified execution environment for energy traders. This collaboration bridges the gap between over-the-counter (OTC) bilateral trading and listed derivatives, allowing mutual clients to manage both workflows through a single, streamlined interface.

The partnership combines TT’s global access to exchange-traded energy markets and spot venues with Enmacc’s extensive network and Request for Quote (RFQ) capabilities. By linking Enmacc’s ‘alpha’ agentic trading technology with TT’s execution suite, market participants can instantly distribute liquidity and manage bilateral credit risk. This integration aims to eliminate fragmented workflows and provide a more efficient experience across European energy and power markets.

Bloomberg Enhances ETF Shares’ Operational Efficiency with BSKT Integration

Bloomberg has announced that Australian issuer ETF Shares has adopted BSKT, an automated tool designed to streamline ETF creation and redemption workflows. By integrating this technology, ETF Shares aims to improve operational efficiency and risk management. The tool allows for the seamless distribution of portfolio composition files to authorised participants at the conclusion of each trading day, ensuring data consistency across the primary market.

The BSKT solution centralises primary market liquidity on the Bloomberg Terminal, allowing ETF Shares to manage electronic creation and redemption requests and track order lifecycles in real time. Standardised fund flow data assists portfolio managers in executing critical tasks, such as pre-trade compliance checks. Furthermore, once orders are settled, the system automates notifications to asset servicing providers, reducing manual intervention in the post-trade process.

As part of Bloomberg’s broader suite of ETF products, BSKT supports the entire investment lifecycle for issuers, investors, and liquidity providers. It complements other electronic market solutions, such as the RFQe service for secondary market trading. By automating the assembly of underlying asset baskets, the tool provides market-makers and authorised participants with a more efficient framework for managing ETF assets.

FIX Trading Community Proposes Recommendations for AI Regulation

The FIX Trading Community has submitted ten formal recommendations to the Monetary Authority of Singapore (MAS) regarding AI risk management in financial markets. This response addresses the growing integration of large language models and machine learning within algorithmic trading. The proposed framework aims to mitigate the risk of market instability and “contagion” caused by the rapid, interconnected nature of global AI-driven trading systems.

A central pillar of the proposal is the establishment of a globally recognised definition and taxonomy for AI to prevent regulatory arbitrage. FIX suggests anchoring new guidelines to existing standards, such as MiFID RTS 6 and DORA, while making company boards directly accountable for the effectiveness of AI governance. The recommendations also advocate for cross-functional oversight of third-party suppliers and the implementation of disclosure patterns for AI data and training, similar to food labelling.

Furthermore, FIX proposes expanding risk assessments to include “change sensitivity” and “interconnectedness” to account for non-linear AI behaviour. The group suggests that AI inventories must be more granular than traditional algorithm logs and that any fine-tuning or data refreshes should undergo rigorous materiality tests. By leveraging its expertise in algorithm certification, FIX aims to ensure that AI lifecycle controls remain robust as the technology evolves.

ICE Benchmark Administration Recognised by ESMA Under EU Benchmarks Regulation

Intercontinental Exchange (ICE) said that the European Securities and Markets Authority (ESMA) has granted recognition to ICE Benchmark Administration Limited (IBA) as a third-country benchmark administrator under Article 32 of the EU Benchmarks Regulation.

“IBA is pleased to have been granted recognition by ESMA,” said Clive de Ruig, President of ICE Benchmark Administration. “This decision ensures IBA’s EU-based clients can continue to use the ICE Swap Rate® and the LBMA Gold Price without disruption and demonstrates our ability to apply robust governance and best-in-class technology to give market participants confidence in the information they depend upon.”

IBA is already authorised and regulated by the UK Financial Conduct Authority for benchmark administration and oversees a wider suite of benchmarks, including the LBMA Silver Price and ICE Term Reference Rates, which are currently outside the scope of EU BMR.

Bloomberg Compresses Delivery Times for Alternative Data

Bloomberg has launched Data Entitlements within the alternatives-focused ALTD function on its Terminal, integrating analytics from providers such as Placer.ai and Similarweb into the existing investment research platform.

The service reduces the delivery lag of key performance indicator estimates to between three and five days, Bloomberg said.

Richard Lai, global head of alternative data at Bloomberg, said the launch provides clients with “a multi-dimensional view of company performance and the ability to nowcast KPIs at a lower lag”.

Users can now access granular metrics, including web traffic and foot traffic data, alongside traditional financial reports and news. Alternative data consists of non-traditional information sets used by investors to evaluate company performance outside of standard filings and price feeds.