About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

SimCorp Releases Cloud Native Investment Analytics Platform

Subscribe to our newsletter

SimCorp has released a cloud native investment analytics platform offering a real-time attribution solution designed to meet growing demand for accurate and real-time performance analytics. This is the company’s first service on its Investment Analytics Platform, with solutions related to ESG attribution and risk attribution planned as the next set of releases.

The platform provides a cloud calculation service and is an integral part of SimCorp’s open ecosystem that is constructed on an API-first architecture. The modernised web front-end gives users fast, dynamic, and granular performance analytics.

“Our new investment analytics service enables users to perform advanced investment performance analytics on the fly, with calculations delivered in just a few seconds,” says Lars Ole Hansen, global product manager at SimCorp.

The performance attribution solution is inherently transaction based and uses data stored in the SimCorp investment management platform, which encompasses all asset classes, to achieve high levels of accuracy and transparency. The design puts all assets and transactions in the same system, meaning users don’t have to pull data manually from multiple sources to determine underlying exposures.

Ole Hansen comments: “Clients will need just one system to accommodate all aspects of performance measurement and attribution. This consolidation can result in savings on additional licenses and reconciliation efforts.”

Performance analysts using the SimCorp platform will be able to delve deeper into the details of investment returns and manage performance rules to trigger alerts for single days when returns appear suspicious or when asset weights approach predefined thresholds. Portfolio managers and client relationship managers will gain fast and flexible views of attribution factors and other success factors in their investments, enhancing decision-making and communication with investors.

Subscribe to our newsletter

Related content


Upcoming Webinar: Augmented data quality: Leveraging AI, machine learning and automation to build trust in your data

Date: 19 September 2024 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Artificial intelligence and machine learning are empowering financial institutions to get more from their data. By augmenting traditional data processes with these new technologies, organisations can automate the detection and mitigation of data issues and errors before they become...


Bloomberg Releases GenAI-Powered Earnings Call Summaries

Bloomberg has released AI-Powered Earnings Call Summaries, the company’s first generative AI (GenAI) product for terminal users. The tool enables users to decipher complex financial information and quickly extract key insights on topics addressed by corporate management teams, such as guidance, capital allocation, hiring and labour plans, the macro environment, new products, supply chain issues,...


Buy AND Build: The Future of Capital Markets Technology, London

Buy AND Build: The Future of Capital Markets Technology London on September 19th at Marriott Hotel Canary Wharf London examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.


Best Practice Client Onboarding

Client onboarding is central to the success of banks, yet it continues to present challenges and the benefits of getting it right are difficult to achieve. The challenges arise from siloed systems, manual processes and poor entity data quality. The potential benefits of successful implementation include excellent client experience, improved client acquisition and loyalty, new business opportunities, reductions in costs, competitive advantage, and confidence in compliance.