Bloomberg’s BQuant Augmented with AI Assistant

Bloomberg has launched a domain-grounded conversational artificial intelligence coding assistant, BQuant Assistant, that is integrated into BQuant Desktop and BQuant Enterprise.

The tool enables users to write code, construct applications and accelerate data analysis using natural-language prompts. The assistant operates directly within the Python environment to generate code, answer questions, query datasets and run scripts in a sandbox.

“BQuant Assistant brings AI-driven coding that is informed by Bloomberg’s understanding of financial data and quantitative workflows directly into the workflows our clients already use to build investment strategies,” said Shawn Edwards, chief technology officer of Bloomberg.

Symbol Master Launches API for 35 Data Endpoints

Symbol Master, which provides standardised options symbology and reference data for the financial services industry, said its API solution has been approved for full production utilisation.

The API Dashboard provides a single interface that gives clients access to 35 data API endpoints to retrieve data, query historical ranges and check data availability.

Access can be governed by administrative permissions as Symbol Master will provision subscribers for defined entitlements based on contracted usage.

“Our API solution will open the door for existing users to integrate to a more usable technical solution without flat file management,” said chief executive George Tull.

The symbology validation software supports firms across the financial ecosystem, covering over 6,000 underlying securities with US options across 20 exchanges. Ten years of historical data is available for the core content set, expanding on previous data distribution methods to enable backtesting and risk management.

tZERO Plans Public Listing via SPAC

Tokenisation infrastructure-as-a-service pioneer tZERO Group is listing as a public company via a merger with FG Imperii Acquisition Corp, a special purpose acquisition company. The transaction values tZERO at a pre-money equity valuation of $350 million. The combined entity plans to list on the NYSE American exchange under the ticker “TZRO”.

Existing shareholders will roll their equity into the new public company, which stands to gain up to $231 million from FG Imperii’s trust account, subject to redemptions and fees. Proceeds will support tZERO’s tokenisation infrastructure, balance sheet, and commercial growth under current CEO Alan Konevsky.

“We have talked about the next phase of tZERO’s evolution requiring a more independent footprint. This transaction delivers that objective, unlocks growth paths and strengthens our ability to scale market infrastructure required for an increasingly tokenised financial system,” says Alan Konevsky, CEO of tZERO. “Our infrastructure-as-a-service capabilities are complete, hard to replicate individually and, in many cases, are unique in the marketplace. These capabilities are built, ready and already commercialised with Tier 1 institutional customers. With this step, we will continue to grow that infrastructure and deepen our diversified institutional and strategic relationships across asset classes.”

The merger, unanimously approved by both boards and backed by some 62% of tZERO’s stockholders, is targeted to close in early 2027 pending regulatory approval.

S&P Global Ratings Taps Chainlink for Vault Risk Service

S&P Global Ratings has partnered with blockchain oracle Chainlink to make S&P Global Vault Risk Assessment data available on chain. The integration gives institutions and investors direct access to independent vault risk analysis, enabling market participants to evaluate lending vault risks and make more informed decisions about where to deploy capital on chain.

The integration leverages Chainlink DataLink, an institutional-grade data publishing service, with the Chainlink Runtime Environment (CRE) orchestrating the retrieval of S&P Global Ratings’ assessment data and its publication on chain. A Chainlink decentralised oracle network retrieves the source data, reaches consensus on the reported values, and delivers them on chain, with Base as the initial supported

S&P Global Ratings’ Vault Risk Assessment provides a forward-looking opinion on the relative risk of impairment to an investor’s position in a lending vault. Its analysis considers portfolio credit quality and liquidity mismatch, alongside risks related to the curator, blockchain, protocol, and vault security and governance. A Vault Risk Assessment is not a credit rating and does not comment on yield levels.

By bringing S&P Global Ratings’ assessments on chain, the integration makes institutional-grade risk analysis available directly to lending platforms and their users. Institutions gain access to independent opinions to support due diligence and investment governance, while developers can build applications that let depositors compare assessed vaults and monitor changes in their risk profiles.

The integration builds on Chainlink’s existing collaboration with S&P Global Ratings, which brought its Stablecoin Stability Assessments on chain. Extending this model to lending vaults gives S&P Global Ratings a new distribution channel for its analysis within the applications where digital assets are managed and deployed.

TT Adds Bitstamp by Robinhood Digital Asset Access

Trading Technologies now supports trading on Bitstamp by Robinhood’s digital asset markets. Institutional market participants can access Bitstamp by Robinhood’s crypto spot and derivatives markets alongside other asset classes, including futures, fixed income and foreign exchange within TT’s multi-asset environment.

TT becomes the first major traditional-markets order/execution management system (O/EMS) to connect directly to Bitstamp by Robinhood, expanding Bitstamp’s connectivity beyond predominantly crypto-native trading platforms and into established multi-asset trading workflows.

Nicola White, VP of Institutional Crypto and GM of Bitstamp by Robinhood, says: “Connecting with Trading Technologies continues our rapid expansion of institutional distribution partners. As a leading multi-asset trading platform with deep roots in traditional markets, TT extends our venue to a global network of sophisticated institutional traders, proprietary desks and buy-side firms. Market participants, through Trading Technologies, can access Bitstamp by Robinhood’s deep liquidity and institutional execution services within their primary daily workflow seamlessly.”

StarCompliance Adds Natural-Language Agent to Compliance Analytics

Maryland based StarCompliance has added an artificial intelligence (AI) agent to its Analytics product, allowing compliance teams to question connected employee and firm data in natural language. The agent returns responses as text, charts or tables. It is intended to reduce the manual work involved in producing compliance analysis and management information.

Users can create and refine dashboards from plain-language descriptions. They can also investigate risks across compliance areas through a new cross-product data model. StarCompliance said this enables compliance staff to explore information without depending on data scientists, information-technology teams or separate business-intelligence tools.

The agent can analyse trends, correlations and outliers within the available data. Users can add explanatory context to its charts and dashboards, then export or schedule reports in PDF, Excel and comma-separated value formats. These functions could support recurring management reporting and investigations that combine data from several compliance processes.

StarCompliance attributes the potential efficiency gains to the agent’s ability to generate queries, analysis and visualisations from natural-language instructions. The announcement does not quantify the manual effort involved or provide customer results showing how much time the functionality saves.

“The new AI functionality in Analytics reflects our commitment to delivering frictionless compliance intelligence that makes data more accessible, meaningful, and actionable,” said Kelvin Dickenson, Chief Product Officer at StarCompliance. “By simplifying how firms explore, visualize, and analyse complex information, we’re helping compliance teams uncover deeper insights, identify emerging risks, and make more informed decisions with greater speed and efficiency.”

The release follows StarCompliance’s May launch of StarAssist. That capability converts rule evaluations and audit trails into natural-language explanations within employee-compliance workflows. Its initial coverage includes personal account dealing, pre-clearance and trade monitoring. StarCompliance plans to extend StarAssist across other parts of its platform.

Covalent Backs AML Analytics Expansion of Financial-Crime Control Testing

Covalent Equity Partners has made an undisclosed growth investment in AML Analytics to fund new testing engines and international expansion. AML Analytics provides independent testing, validation and risk analytics for anti-money laundering (AML), counter-terrorist financing and sanctions controls. The transaction’s value and Covalent’s ownership interest were not disclosed.

Founded in 2010, AML Analytics uses reference datasets and benchmarks to evaluate financial-crime systems and control architectures. Its platform supports the measurement, calibration and verification of AML systems. The company says more than 50 supervisory authorities and 1,450 financial institutions use its technology across almost 60 countries.

Covalent’s capital and operational support will fund AML Analytics’ engineering roadmap, next-generation testing engines and wider geographic coverage. The announcement provides no timetable or technical specification for the new engines. Founder and Group Chief Executive Officer Justin Holder will continue to lead the company with its existing management team.

The companies link the investment to the adoption of generative and agentic technologies in financial services. They argue these developments are creating additional routes for financial crime. AML Analytics’ datasets and independent benchmarks are intended to help institutions and supervisors assess whether their controls continue to detect relevant risks.

“From day one, our mission has been to give the defenders of the financial system the empirical tools to stay ahead of increasingly sophisticated threats. Covalent shares our conviction and brings deep sector and operational expertise, which will help us scale that mission to more institutions and regulators worldwide,” said Holder.

AML Analytics currently tests sanctions-screening and transaction-monitoring systems. Its products include tools for ongoing validation, system benchmarking and tests using synthetic transaction data. The company also provides testing services for supervisory authorities conducting reviews across regulated firms.

Hummingbird Acquires Quantimon to Connect AML Detection with Alert Outcomes

San Francisco based Hummingbird has acquired anti-money laundering (AML) risk-detection company Quantimon to connect transaction-monitoring models with the outcomes of alert investigations. The acquisition adds Quantimon’s machine-learning technology and federated learning network to Hummingbird’s financial-crime compliance platform. Financial terms were not disclosed.

The planned workflow feeds completed alert decisions back into detection. Hummingbird records whether an analyst or artificial intelligence (AI) agent closes, escalates or files on an alert. Quantimon’s models are designed to learn from those decisions and risk-rank subsequent alerts. The companies said the models could also identify activity resembling confirmed cases when no existing rule fires.

Quantimon has also built a federated learning network. It is designed to identify patterns across institutions without sharing their customer data. Hummingbird said customers could eventually combine these signals with third-party intelligence and their own alert history. That cross-institution capability forms part of the integration roadmap. The announcement did not describe it as immediately available.

Hummingbird plans to retain rule-based monitoring alongside machine learning. Its roadmap includes tools to build, test and manage rules across larger and more complex programmes. The company presented strong rule coverage as the foundation for machine learning. The models would prioritise alerts and extend detection without replacing deterministic controls.

FactSet and Hamilton Lane Partner to Integrate Private Markets Data into Portfolio Analytics

FactSet and Hamilton Lane have announced a strategic partnership to integrate Hamilton Lane’s proprietary private markets data and benchmarks into FactSet’s portfolio analytics platform, enabling institutional investors to analyse public and private assets within a unified workflow.

The integration will provide access to data covering more than 70,000 funds and 240,000 assets, alongside fund- and deal-level benchmarks developed from Hamilton Lane’s extensive private markets investment experience.

The offering will support customised performance benchmarking, enhanced risk analysis and commitment pacing models, as well as portfolio construction and monitoring across asset classes. Investors will be able to assess performance, attribution and risk across public and private holdings without relying on separate analytical systems.

The partnership reflects growing institutional demand for integrated portfolio analytics as private markets become an increasingly significant component of investment allocations.

Further details on product availability and additional capabilities are expected in the coming months.

Nasdaq Europe to Launch PureStream-Based Trajectory Trading in November

Nasdaq Europe plans to launch a new trajectory trading service in November 2026, using PureStream technology to help institutional investors execute large European equity orders while reducing market impact and information leakage. The service will match trading interest based on a specified percentage of future market volume, allowing orders to execute progressively at volume-weighted average prices (VWAP).

It will operate through Nasdaq Investment Firm B.V., which received authorisation from the Dutch Authority for Financial Markets on 26 October. Trades will be formalised and published on Nasdaq’s regulated trading venues.

Initial coverage will include selected equities listed on Nasdaq Copenhagen, Helsinki and Stockholm, including constituents of the OMXC25, OMXH25 and OMXS30 indices, alongside stocks from nine other European markets. Nasdaq expects to add approximately 1,200 European equities in January 2027. The service forms part of its Digital Liquidity Networks business, with institutional onboarding beginning through a phased rollout.