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J.P. Morgan Securities Services has enhanced its Fusion data management platform with the addition of performance reporting and portfolio analytics software from FactSet. The integration is intended to provide asset managers and owners with advanced data management, outsourced accounting, and analytics capabilities, freeing them to concentrate on investment insights and improved portfolio performance.
Fusion is the backbone of J.P. Morgan’s AI efforts for data and entitlements, which are led by its Chief Data and Analytics Office Teresa Heitsenrether. Acting as a fintech within J.P. Morgan, Fusion helped to roll out a large language model-based generative AI product, the LLM Suite ‘analyst in a box’ software, to 200,000 bank employees for tasks such as document summarization.
Companies are facing a sea of data made up of standardized data, normalized data and alternative data from private markets, making it difficult to distribute data-enabled insights to decision-makers in a timely manner, Cubillas Ding, Celent’s research director, capital markets and investment management, said.
“Even with established and well-understood data sets, efforts to consolidate and aggregate the book of record, performance and risk analytics have demanded substantial integration efforts and incurred high costs,” Ding said.
Fusion uploads and consolidates J.P. Morgan’s accounting and investment book of records (ABOR/IBOR) and third-party providers’ ABOR/IBOR and integrates them with FactSet for analytics, giving asset managers and owners a single view of their public and private investment data. Clients who outsource their performance operations under this integration use J.P. Morgan’s global support and governance model.
“FactSet provides support for J.P. Morgan’s client support and our two organizations have developed a joint operating model for the systems,” said Jason Mirsky, J.P. Morgan Securities Services’ head of data solutions.
Integrated platforms such as Fusion and FactSet enable buy-side data analytics, which for years had lagged behind sell-side analytics, to catch up by turning data into information and actionable analytics knowledge for investment decisions. For example, clients can analyze their investment performance to see what returns they are getting.
“This is where the combination of FactSet and Fusion plays a major role in making sense of the data from custodians, fund administrators and transactions and making this information usable,” said Jay Wolstenholme, strategic advisor, capital markets at Datos Insights. “Through decades of work, FactSet and J.P. Morgan have created a viable product that adds FactSet analytics and ESG benchmarking data to performance and risk data.”
The integration of Fusion with FactSet was prompted by J.P. Morgan’s institutional clients, who wanted to receive J.P. Morgan data using modern technology, Mirsky said.
“Instead of using File Transfer Protocol and e-mail, they wanted to get our data to where they could use it on cloud-based analytics platforms such as Snowflake or Databricks,” Mirsky said. “They wanted to do this through APIs or by using a virtual file system on their desktop.”
The bank’s clients also wanted a single holistic view of their portfolios across multiple administrators and custodians and to send that data to an analytics engine. A prerequisite for transaction and cashflow data to work together is that they are normalized or harmonized and use the same identifiers, Mirsky said.
J.P. Morgan’s response was to partner with FactSet, making the bank’s Fusion data management ecosystem work seamlessly with FactSet’s analytics, a process that took fifteen months. One attraction of FactSet was that many of J.P. Morgan’s clients were already using FactSet’s analytics engine.
While Databricks, AWS and Snowflake are generalist data warehousing platforms serving different types of corporate verticals, J.P. Morgan specializes in financial data. “We were able to take data from J.P. Morgan or third parties and transform it into the correct format, so that FactSet could do performance or ex-post risk or attribution-type analytics,” said Mirsky. Client data such as positions and transactions are fed into FactSet for analysis. The results are then sent back to the client’s architecture of choice. Making systems from different vendors work together was a challenge, Mirsky said.
Chris Ellis, FactSet’s executive vice president, head of strategic initiatives, said asset managers and asset owners are trying to reimagine their operating models using new technology and capabilities. “If you can maximize your performance, you’re going to attract assets and make your clients happy. Asset managers and owners also want to strengthen their relationship with their clients,” he said.
The new operating models asset managers and investors are looking for involve outsourcing responsibilities and capabilities such as running a separate IBOR and ABOR that don’t improve performance and don’t get managers closer to their clients, Ellis said. “What attracted us to partner with J.P. Morgan is that they’ve taken what used to be primarily custody but elevated it to custody and ABOR/IBOR.”
Celent’s Ding is seeing a growing trend particularly among leading sell-side banks, custodians and asset/fund managers to adopt modern investment data ecosystems based on native cloud enablement, APIs, and data mesh approaches. “These innovations aim to lower barriers for data exchange and promote more efficient ways of meeting the information needs of end-users. The Fusion-FactSet integration highlights the industry’s ambitions to address the broader requirements of end-users in areas such as portfolio performance, risk management, and ESG reporting, to ensure sufficient breadth and completeness.”
For asset managers and asset owners, this approach alleviates the burden of lengthy and potentially cumbersome integration projects. Additionally, if these data offerings are designed effectively, they enable clients to select and combine the curated data sets and analytics that are relevant to their organizational functions. This ‘switch-on access’ minimizes integration overheads, Ding said.