Arcesium

We're proud to share that Arcesium has been nominated for two categories in the A-Team Group's 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 𝗔𝘄𝗮𝗿𝗱𝘀 𝗨𝗦𝗔 𝟮𝟬𝟮𝟲: ✨ Best Buy-Side Data Management Platform ✨ Best Sell-Side Data Management Platform If you've worked with our platform, we'd appreciate your vote before nominations close this Friday at 12PM ET 👉🏼 https://bit.ly/4yncaXZ A-Team Insight, from A-Team Group #DMIAwards #DataManagement

Sell-side firms are moving back into private credit, structured products, and digital assets. The market case is clear. The operational prerequisite rarely gets the same attention. In the latest edition of The Look Ahead with Ted, Ted O'Connor examines the instrument data problem that determines whether re-entry into a non-standard asset class is operationally viable or just strategically aspirational — and what the firms scaling successfully are solving before the business arrives. Read the latest edition to see why infrastructure readiness is what separates the firms that scale successfully from the ones that don't. #BankingTransformation #DataStrategy #FinancialServices

Most insurance asset managers know they have a data problem. Fewer have identified where it actually starts. It starts at the instrument identity layer. When different market data providers classify the same security differently, every rollup becomes a negotiation. Two teams. Same security. Different capital charges. That is not a data inconvenience. It is a regulatory risk. The common workaround is Excel. It creates competing truths and weak auditability. It does not scale. Start with the operating model challenge. Then understand the root cause underneath it. Arcesium's Phil Bodenstab on the insurance data challenge: https://bit.ly/3ThStRq and Arcesium's Phillip Silitschanu on the reference data hurdle at the heart of it: https://bit.ly/4vwjX3g

Every insurance asset manager runs one of three operating models. All three are struggling with the same data challenge. →

Insurance asset managers are not chasing alpha. They are managing trillions in assets against regulatory obligations that leave no room for data errors. One Arcesium client recently consolidated data from 20 different source systems. NAIC requirements. Complex legal entity structures. Public and private asset classes converging. The same deal arriving from different managers under different names, creating duplicate records that undermine reporting accuracy. The data requirements are growing faster than most firms' foundations can absorb. Arcesium's Phil Bodenstab on why insurance investment data is uniquely complex and what it takes to get it right. Link in the comments. Is your firm's data infrastructure keeping pace with your regulatory obligations?

Most firms know what can go wrong with AI in production. Fewer have a framework to prevent it. Fewer still have both working together. That is the gap where the next competitive edge is opening. Governance without discipline is just documentation. Discipline without governance is just risk. The firms building both into how they deploy AI are not just getting agents into production. They are pulling ahead in ways that will be very hard to close. Two pieces on what it takes to build both. https://bit.ly/3TbIwVz https://bit.ly/3T95Jru

Matthew Katz will be joining Hedgeweek® on July 15 to discuss where AI adoption in hedge funds really stands, and why owning the tools isn't the same as using them. A few of the questions we'll get into: ☑️ Two-thirds of managers say staff use AI regularly. One in ten reaches for it operationally. What's behind that gap? ☑️ Why does adoption depth fall as firms get bigger? ☑️ Many firms don't measure AI's value at all. What does good measurement look like? This is going to be an interesting one. Register here: https://bit.ly/4ydVxy4

73% of asset management executives say AI is critical to their organization's future. Most are still stuck in pilot. The gap is not capability. It is discipline. The firms closing that gap are not chasing the latest model. They are applying the same four principles to every agent they build and earning the right to expand autonomy only after each one proves reliable in production. That is how a pilot becomes infrastructure. Arcesium's Dmitry (Mitya) Miller on the framework that takes AI agents from prototype to production. Link in the comments. Which of the four principles is your firm finding hardest to get right?

World Cup prediction market volume just hit $5.4 billion. Kalshi says its long-term goal isn't retail betting. It's becoming a next-generation derivatives exchange. In a new byline for The TRADE News, Arcesium's Phillip Silitschanu asks the question institutional investors are starting to sit with: what would it actually take to use these instruments to hedge risk, not just speculate on it? Read the full piece here 👉🏼 https://lnkd.in/eCKfFwfF

We talk a lot about operational infrastructure as a competitive advantage. But infrastructure is only as strong as the people building it. Q2 was a quarter of investment in those people. We welcomed interns across our global offices, came together to talk about what's next after our recent acquisition, prioritized wellbeing, and learned alongside the tech community. A few moments from the quarter. #LifeAtArcesium.