Technology and data
Technology and data are reshaping how financial institutions trade, manage risk and make decisions. Artificial intelligence, cloud computing and increasingly sophisticated analytics are creating new opportunities for automation, scalability and insight while raising fresh challenges around governance, resilience and regulation.
Risk.net explores the latest developments in financial technology and data, spanning AI and machine learning, cloud and compute, data management and analytics, risk and trading infrastructure, model development and emerging technologies.
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One legal entity. Multiple IDs. Three business risks.
How fragmented entity IDs undermine risk, compliance and revenue decisions
From cloud adoption to cloud advantage
Building cloud-native data architectures built for speed, scale and trust
XiNG provides the platform for Citi’s growth
Citi’s best-in-class risk management platform, XiNG, provided the foundation for the firm being named Risk’s 2026 Derivatives house of the year
Davy enjoys efficiency gains in wake of FIS back-office implementation
How FIS helped Davy future-proof operations through automation, data and scale
Operationalising AI: building governance foundations for capital markets risk
Senior industry leaders and practitioners explore how firms are integrating AI into enterprise risk and capital management
AI model and compute speed: the new alpha for quantitative trading
AI tools from Weights & Biases and infrastructure from CoreWeave streamline the entire quantitative research loop
Governing AI execution as institutional infrastructure
Drawn from discussions at a June 2026 AI governance roundtable in New York, convened in collaboration with Cisco
Communications surveillance in financial markets
Navigating compliance and the AI governance challenge
Operationalising AI in capital markets risk infrastructures
How firms are embedding AI into workflows such as FRTB capital calculation, P&L explain and intraday risk monitoring
From insight to execution: building the next-generation cross-asset platform
The shift from research-led platforms to fully integrated client solutions – how closer alignment between platforms is shaping the client experience
Digital asset and crypto compliance: new risks and regulatory expectations
How leading institutions are approaching cross-asset oversight and building more resilient, future-ready compliance frameworks
Digital asset and crypto compliance: new risks and regulatory expectations
How leading institutions are approaching cross-asset oversight and building more resilient, future-ready compliance frameworks
How can Apac banks harness AI for regulatory reporting?
A Q&A with Nasdaq’s Subbaiyan Vaithinathan and Uttam Albela
Financing Connect: real-time optimisation in private credit financing
J.P. Morgan’s Financing Connect, part of its Vida platform, reflects a shift towards structured data and scenario-driven analytics
Industrialising the challenge process: AI in operational risk scenario analysis
How structured modelling and AI could help industrialise the challenge process
Rethinking post trade for OTC derivatives
LSEG’s TradeAgent platform aims to improve efficiency and resilience in post trade
Integration strengthens e-trading in persistently volatile markets
Survey reveals that traders are grappling with daily volatility, while technology outranks liquidity as the top market structure concern
Reach new heights with real-time data via Cboe Global Cloud
Cboe Global Cloud provides clients with access to Cboe market data with as little as an internet connection
Transforming the trade lifecycle with pricing and reference data in the cloud
LSEG is developing its cloud-based data service to reflect how financial institutions now use information to feed systems and generate insight
Liquidity in private markets: the structural and data challenge
How structural and data-driven innovations are converging to address the liquidity challenge in private markets
Bringing trading-desk data into derivatives pricing models
PricingDirect’s new autocallable model, which reflects the shift towards data-driven transparency as firms rethink how they value complex derivatives