Switzerland implemented FRTB for its banks on 1^st January 2025 and FINMA recently extended its scope to include Leonteq. When the FRTB implementation deadlines became clear, Leonteq evaluated several vendors for a solution that could integrate with its existing pricing engines. After a detailed assessment, it selected Atoti.

The solution provides dashboards and preconfigured reports that meet FINMA’s requirements, along with analytics aligned to the ISDA Unit Tests and additional capabilities such as what-if analysis and capital decomposition. Leonteq worked closely with ActiveViam’s customer success team and moved to production within six months. The ability to implement within this timeframe, supported by previous deployment experience, was an important factor.

We have successfully implemented ActiveViam FRTB in a very short period. This enables us to efficiently control and report FRTB capital charges while providing enhanced drill-down capabilities. Both front office traders and risk controllers can seamlessly analyze figures at various levels. The solution brings improved oversight, transparency, and adaptability to our internal processes.

Eric Schaanning
Chief Risk Officer, Leonteq

We are delighted to expand our partnership with Leonteq with a long-term commitment to support their FRTB reporting. This was a challenging, ultra-quick deployment of Atoti for FRTB demonstrating our ongoing commitment to deliver on our promise to simplify the deployment and reporting of FRTB.

Shelley Magee
CEO, ActiveViam

About Atoti

Atoti is a data analytics platform developed by ActiveViam for financial services organizations. This unique technology meets the specific needs of the industry in ways general-purpose databases and mass-market business intelligence tools do not. Atoti is flexible, purpose-built, scalable and handles massive datasets in sub seconds. With its transactional database and modern, multidimensional OLAP aggregation engine, Atoti is the fastest data analytics software in financial services. Half of the world’s largest banks – along with top hedge funds, asset managers, custodians, exchanges and regulators – rely on Atoti.

Follow us on LinkedIn for the latest news and updates.

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Why Graviton works so well with Atoti

Atoti is built on a Java runtime, making it architecture-agnostic and enabling it to run on Graviton instances with no code changes. This removes typical migration barriers associated with hardware shifts and allows firms to adopt Graviton quickly and safely.

ActiveViam collaborated with AWS to validate Atoti on Graviton, ensuring performance parity with x86-based deployments while delivering substantial improvements in cost efficiency. Customers with large Atoti deployments have already recorded substantial reductions in hardware spend after moving to Graviton-backed instances. One Tier‑1 bank running more than 100 Atoti instances saw approximately a 40% reduction in cloud hardware costs following its migration.

Nomura’s Graviton deployment: Measurable, immediate impact

Nomura’s Market and Credit Risk Technology teams manage highly granular, compute-heavy analytics across large historical datasets. To increase access to historical data while reducing compute expenditure, Nomura migrated its Atoti workloads from in‑house data centers to AWS and deployed them on Graviton using the same memory footprint.

The transition required no refactoring or modification to application code, accelerating their cloud optimization program and avoiding the risk and complexity normally associated with major infrastructure changes. After the migration, Nomura achieved a 42% reduction in compute costs with no degradation in performance or user experience. Analysts retained fast access to both real-time and historical aggregation capabilities across market and credit risk use cases.

“By embracing the power of Atoti on AWS Graviton… Nomura has achieved an unparalleled granular aggregation capability at a drastically reduced cost.”

Conor Brennan
Managing Director of Risk Technology, Nomura

About Atoti

Atoti is a data analytics platform developed by ActiveViam for financial services organizations. This unique technology meets the specific needs of the industry in ways general-purpose databases and mass-market business intelligence tools do not. Atoti is flexible, purpose-built, scalable and handles massive datasets in sub seconds. With its transactional database and modern, multidimensional OLAP aggregation engine, Atoti is the fastest data analytics software in financial services. Half of the world’s largest banks – along with top hedge funds, asset managers, custodians, exchanges and regulators – rely on Atoti.

Follow us on LinkedIn for the latest news and updates.

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The win highlights ActiveViam’s continued innovation in delivering high performance, cost efficient risk analytics in the cloud. The judging panel recognised key advancements to the Atoti platform, including optimisation for AWS Graviton, the integration of JVM hibernation technology, and the launch of Atoti Platform as a Service.

Read the full article to discover how ActiveViam is reshaping the economics of cloud based risk analytics and setting a new benchmark for the industry.

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Atoti Intelligence integrates machine learning and generative AI directly into the platform’s semantic and computational layers, enabling institutions to accelerate analytics while maintaining full control over data lineage and governance.

Read the full Risk.net editorial to explore why the judging panel described ActiveViam’s approach as both sophisticated and uniquely practical.

The post ActiveViam awarded Best Use of Machine Learning/AI for Atoti Intelligence: Redefining risk and P&L analytics appeared first on ActiveViam.

This tragedy is deeply personal to our team, with ActiveViam employees having families directly impacted. We recognize that true ESG commitment means immediate action when our community needs us most.

ActiveViam is actively supporting the recovery efforts in Jamaica through an employee donation matching program. 

We are proud to support the recovery efforts of Jamaica. To find out how you too can help, donate here.

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• Best Use of Machine Learning / Artificial Intelligence
• Best Use of Cloud

These awards recognize ActiveViam’s pioneering work in transforming financial analytics through advanced AI and cloud-native technologies.

The Best Use of ML / AI award celebrates the launch of Atoti Intelligence, a breakthrough framework that integrates machine learning and generative AI into ActiveViam’s flagship analytics platform. Atoti Intelligence enables financial institutions to gain deeper insights and faster decision making. Key innovations include:

• Auto-Explain: an AI powered tool that automates root-cause analysis of complex metrics like P&L and VaR, delivering plain-language summaries and actionable insights
• Query Engine Optimizer: uses machine learning to configure Atoti’s caches, simplifying deployment and improving query performance up to 50%
• An open architecture for AI: firms retain full control over their LLMs and data, ensuring compliance, transparency, and seamless integration with firm-wide AI strategies.

The Best Use of Cloud award recognizes ActiveViam’s innovations in cloud deployment, including Atoti Platform Admin which simplifies multi-cloud and on-premise deployments with out-of-the-box administration and observability. In collaboration with Nomura, AWS Graviton and Azul, cloud deployment costs have been reduced up to 60% for analytics use cases.

“These awards reflect our commitment to solving real-world challenges with bold, practical innovation. We’re proud to help financial institutions unlock the full potential of AI and cloud technologies to drive smarter, faster, and more resilient operations.”

Alan Lee, Chief Product Officer, ActiveViam

ActiveViam continues to lead the way in delivering agile, scalable, and intelligent analytics solutions for the financial industry.

About Atoti

Atoti is a data analytics platform developed by ActiveViam for financial services organizations. This unique technology meets the specific needs of the industry in ways general-purpose databases and mass-market business intelligence tools do not. Atoti is flexible, purpose-built, scalable and handles massive datasets in sub seconds. With its transactional database and modern, multidimensional OLAP aggregation engine, Atoti is the fastest data analytics software in financial services. Half of the world’s largest banks – along with top hedge funds, asset managers, custodians, exchanges and regulators – rely on Atoti.

Follow us on LinkedIn for the latest news and updates.

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Overview

• Smartstream and ActiveViam have partnered to deliver an integrated solution combining Smartstream’s Smart Collateral with ActiveViam’s Atoti Collateral Optimization platform.
• The collaboration enables financial institutions to optimise collateral allocation, reduce reliance on costly liquidity buffers, and achieve immediate return on investment.
• The modular, high-performance solution supports regulatory compliance (UMR, EMIR, Basel III) and empowers clients to make smarter use of their collateral inventory.

Smartstream, the trusted data solutions provider for leading global financial institutions and enterprises, today announces the partnership with ActiveViam, a global provider of advanced data analytics and decision-making solutions for financial services – together the two companies will provide immediate ROI for collateral management optimisation, for clients in treasury and capital markets.

This collaboration connects two technologies, Smartstream’s Smart Collateral with ActiveViam’s Atoti Collateral Optimisation solution. The result is an efficient, streamlined and cost-effective solution for optimising and allocating cheaper-to-deliver assets, whilst reducing reliance on expensive liquidity buffers. The partnership provides a comprehensive, and modular collateral management workflow for financial institutions. This powerful combination future-proofs clients and enables them to make more efficient use of their cash and non-cash collateral inventory in a timely manner.

“Partnering with ActiveViam unites two industry leaders which has become an extremely attractive proposition. As client demands grow more sophisticated, there is an increasing need for advanced tools that optimise collateral across all inventory lines. This partnership ensures maximum efficiency in the use of high-quality liquid assets, boosts overall performance, and provides a modular, customisable solution tailored to each firm’s unique requirements.”

Roland Brandli
Head of Partners and Alliances, SmartStream

“We are thrilled to announce this partnership with Smartstream. This collaboration offers a robust and cost-effective solution that enables clients to benefit from the efficiencies of optimising their inventories, whilst maximising their liquidity buffers.”

Florence Falck
Head of Partnerships, ActiveViam

The solution integrates with Smartstream’s collateral infrastructure, delivering high levels of automation and straight-through processing (STP) for collateral flows between counterparties. With its modern architecture and modular design, the platform can be tailored to meet each client’s specific requirements. It supports compliance with evolving regulatory frameworks, including UMR, EMIR, and Basel III, while also helping to optimise the use of high-quality liquid assets.

About SmartStream

Smartstream unlocks trusted, intelligent data insights – clearly, consistently, and without compromise.

Empowering leading global financial institutions and enterprises with innovative solutions that deliver accurate, timely data insights to streamline operations, reduce costs, and meet regulatory demands
with confidence.

By harnessing data at the core of customer operations, Smartstream drives smarter, faster outcomes across reconciliations, liquidity, collateral, corporate actions, fees, and reference data solutions.

smart.stream

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SUNNYVALE, Calif., and LONDON, UK – October 28, 2025

Azul, the only company 100% focused on Java, and ActiveViam, the global leader in high-performance analytics for financial services, today announced a partnership that delivers a breakthrough in cost optimization for financial analytics in the cloud. The solution combines Azul’s high-performance Java platform, Platform Prime, with ActiveViam’s Atoti platform to provide financial services organizations with faster, more elastic in-memory analytics that can dynamically scale with demand — reducing cloud costs, accelerating insight and improving responsiveness to real-time market conditions.

Solving the perfect storm of cost, performance and regulatory pressure in financial analytics 

Financial institutions are under pressure to deliver real-time risk analytics in volatile markets while controlling infrastructure costs and adhering to stringent regulatory demands for uptime, resiliency and compliance. To address these demands, data intensive applications have been migrated to the cloud, which has increased cloud spend and made cost optimization a board-level priority.

By leveraging Azul Platform Prime’s support for CRaC (Coordinated Restore at Checkpoint), which is designed to significantly reduce the startup and warm-up times of Java applications, Atoti users can “checkpoint” or snapshot a fully warmed-up JVM instance and application state, which can then be used to launch new JVMs almost instantaneously from that saved state, dramatically reducing Java cold start and warm-up times.

A large global financial services group was struggling with start-up times for a large, in-memory credit risk application deployed on AWS Graviton. By leveraging Atoti, combined with Platform Prime’s support for CRaC, the customer was able to provision in-memory Atoti instances in minutes, not hours, thereby increasing application elasticity, improving reliability, reducing cloud costs and helping to grow their business.

“Through continuous innovation and close collaboration with Azul and our launch customers, Atoti has become the most cost-effective platform for complex financial analytics.”

“By leveraging the power of Atoti and Azul Platform Prime, the two companies working together have unlocked a new way to reduce total cost of ownership while maintaining high performance and improving availability.”

Antoine Chambille
Chief Technology Officer, ActiveViam

“The combination of ActiveViam’s Atoti in-memory analytics and Azul Platform Prime has already proven its ability to deliver lightning-fast insights on terabytes of data without pauses or errors. By leveraging CRaC support in Azul Platform Prime, organizations can spin up new Atoti cubes in a fraction of the time previously required.”

“This breakthrough not only accelerates time-to-insight but also drastically reduces infrastructure costs, making high-performance in-memory analytics more efficient and accessible than ever before.”

Gil Tene
Co-founder and Chief Technology Officer, Azul

About Azul Systems Inc.

Headquartered in Sunnyvale, California, Azul provides the Java platform for the modern cloud enterprise. Azul is the only company 100% focused on Java. Millions of Java developers, hundreds of millions of devices and the world’s most highly regarded businesses trust Azul to power their applications with exceptional capabilities, performance, security, value, and success. Azul customers include 36% of the Fortune 100, 50% of Forbes top 10 World’s Most Valuable Brands,10 of the world’s top 10 banks and leading brands like Avaya, Bazaarvoice, BMW, Deutsche Telekom, LG, Mastercard, Mizuho, Priceline, Salesforce, Software AG, and Workday. Learn more at azul.com and follow us @azulsystems.

Media contact for Azul – Treble, Sarah Rachul

Media contact for ActiveViam – Global Head of Marketing, Sarah Weeks

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The real breakthrough will not come from better models alone – it will come from enabling AI agents to interact with secure, governed and high-performance analytical environments with respected and trusted partners. This is where Atoti comes in.

Atoti is built for the fast moving, high volume, complex datasets that drive risk, P&L, and analytics in capital markets. It is already used by traders and risk managers around the world to help them understand their business, to make better decisions and to be prepared for the unexpected. It transforms granular trade-level data into business metrics like VaR, Expected Shortfall, P&L, capital charges, liquidity ratios and more. Its high-performance query engine provides real-time analysis and what-if scenarios down to the most granular level.

Atoti Intelligence is the missing link that enables AI agents to interact directly to explore, drill down, and analyze metrics dynamically like a human analyst would, but faster and without errors. Atoti is not just a semantic layer; it’s open and extensible platform enables AI agents that can reason, explain, and act on financial data with confidence. Its open architecture means firms can use their preferred Large Language Models (LLMs) and AI agents, and Atoti MCP ensures analytics are exposed to the firm’s AI stack in a robust, secure, and auditable way.

Make AI work for your financial analytics safely smartly and at scale. Choose Atoti.

To find out more about how Atoti powered tools help you to make informed decisions click here to read a blog by Antoine Chambille, Chief Technology Officer at ActiveViam.

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What really stuck with me from this event were two things:

• It’s no longer about incremental LLM improvements as the main selling point. We can probably assume that, in their current form, they won’t make dramatic leaps anymore. What will really move use cases forward, and deliver results, is how easily data sources can be consumed and discovered by AI agents.
• In all banks, the main roadblock to AI adoption is regulation and the complexity of implementation, especially with technologies that keep changing. Anthropic now wants to “show how it’s done” — and maybe even take on part of the implementation themselves.

Anthropic’s demo focused on the work of a research analyst digging into an investment opportunity, pulling up stock prices, fundamental analyses, earnings calls from data providers like FactSet or S&P, and then putting together a summary with charts.

It’s pretty impressive to watch. One YouTube viewer even commented, “There will be zero edge in fundamental analysis soon.”

It’s a well-chosen use case too: it relies on data that’s easy for humans (and therefore the LLM) to understand, follows a fairly structured fundamental analysis process, and plays right into the LLM’s strength at summarization.

But can we take it further from those human-interpretable market datasets towards model-oriented quantitative datasets where arguably there’s even more to gain in terms of AI automation?

I’m talking about datasets with millions of trade-level rows, sensitivities, and risk-factor simulations:

• Granular market/risk data – highlighting the transaction-level or factor-level detail.
• Analytical datasets – built to feed risk engines, pricing models, or simulations rather than humans.
• Position and risk factor data – the raw building blocks for VaR, P&L attribution, stress testing, etc.
• High-dimensional financial data – emphasising the huge number of variables (risk factors, scenarios).

Humans (and AIs) can’t make sense of this raw granular data as is. First, you need to aggregate it into meaningful business groups and metrics that quantify performance or risk.

In this field, where the norm has long been either letting the business deal with raw data (tables and columns, exports, spreadsheets) or producing batch reports, Atoti brought a fresh approach that quickly became the gold standard in big financial institutions.

Atoti offers a high performance “semantic model” that lets business users analyze any metric by any business dimension, without mistakes and without waiting. All the hierarchies structuring the business are modeled and made available, along with all metrics from simple ones (SUM, COUNT, STD…) to complex ones (P&L Explain, VaR, Expected Shortfall, CVA, LCR, FRTB capital requirements…). Like a pivot table on steroïds, users can slice and dice metrics along hierarchies freely, instantly, and without errors. It’s Atoti that knows the business logic to calculate these metrics and how to roll them up from trade level and across hierarchy levels.

Why did I take the time to explain how Atoti works? Because this ability to add business meaning to trade-level data,and to provide explainability and actionability by calculating everything on the fly, was originally designed to help humans. But it turns out to be the key to really enable AI.

Let’s say we want to automate part of a risk analyst’s job when they sign off on the daily Value at Risk. We can tell (prompt) an AI agent what to look at, and in what order, just like we would explain it to a junior analyst. But then the agent needs to be able to access the VaR figures.

One idea could be to give the agent access to a database with the trades and P&L vectors. You often hear about LLMs being able to write SQL queries, so in theory they should be able to “handle it.” In practice, this only works for very common aggregations—like total sales per quarter. For more complex and less frequent calculations, AI isn’t reliable.

Instead, we could precompute a report with the VaR per book for yesterday and today, for example. This time, the VaR aggregation method is reliable and governed. The agent would be able to spot which books had a big change in their risk. But that’s as far as it goes—where the right approach would be to keep going, filter each problematic book and drill down by instrument, by region, and so on. With a static report, the agent is stuck and reduced to just commenting on it.

Now with Atoti: the agent connects to Atoti (to the Atoti MCP server to be precise, more on this later), pulls the list of dimensions (including booking) and measures (including VaR), which enriches its context. It can then match these business objects with what it’s being asked to do in its “risk analyst” prompt. The agent also learns how to query Atoti, reusing the hierarchies and metrics already defined and governed there.

With this new power, the agent can start from the “VaR per Book” view, spot the books that stand out, and then run all sorts of deeper analyses described in its prompt, querying Atoti again and again with different hierarchies, levels of detail, filters, and even other metrics correlated with VaR.

The result: a reliable agent that can actively analyze and truly save time for the human analyst. When we built the first prototypes of this concept with our clients, it was really exciting to see how quickly the agents understood the cube on their own — it felt like it “just worked.”

And this blog only scratches the surface; thanks to its speed and support for incremental data updates, Atoti is also great for scenario analysis and what-ifs. Imagine AI agents that can run these what-ifs on demand, just by understanding a business user’s natural language request — or even automatically include pre-deal checks to respond to a client’s RFQ.

By the way, we’re talking in the present here, not about a plan for the future.

Conclusion

Semantic layers have been around for a bit, but their role in agentic AI is about to make them indispensable. And in quantitative finance, only Atoti can handle real-world complex non linear metrics and what-if analysis, making it a true power tool for both humans and agents.

For heavy-duty analytics like risk, P&L, and performance in large financial institutions, Atoti isn’t just a bridge between data and AI, it’s the indispensable gateway to deploying AI agents that can take over today’s analyst workflows and free up talent for higher-value work. In this space, there’s nothing else like it.

This short post kicks off a blog series where we share our vision for AI in the analytical and operational workflows of large financial institutions, and how Atoti fits into the modern AI stack.

Discover more about Atoti 

Get in touch with ActiveViam

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