Celent: Low rates of STP endemic in back office
10 October 2018 Boston
Image: Shutterstock
Low rates of straight through processing (STP) are endemic in the back office, a new research report from Celent in collaboration with Xceptor found.
The reasoning behind this endemic is the heavy reliance on human processes, which has been the norm, the report revealed.
As trade reconciliation, settlement, allocations, and payments utilise digital tools and firms automate these processes, large cost reductions are being made, Celent found.
The report found that in US equities, costs have dropped by 33 percent over the last five years as data and automation projects in these areas took hold.
Additionally, an ever-increasing set of over-the-counter products are being cleared, which is driving a much more data-driven approach. This approach has required significant work in migration of workflows and new connectivity.
Automation of collateral flows between counterparties and clearinghouses, as well as rapid affirmations and confirmations across the equity, foreign exchange, rates, and commodity product, has also been increased.
Celent concluded: : “Growing digitalisation of trade and client lifecycle means a need for a new and scalable solution, and many financial institutions are already working on it. Accessing this data, from asset class performance to client behaviour, is a key initiative for many players.”
“The challenge is how to harness the data coming from different sources and formats to generate meaningful insights in the most rapid time possible. Advanced data and machine learning can only be leveraged after the data is correct and robust.”
The reasoning behind this endemic is the heavy reliance on human processes, which has been the norm, the report revealed.
As trade reconciliation, settlement, allocations, and payments utilise digital tools and firms automate these processes, large cost reductions are being made, Celent found.
The report found that in US equities, costs have dropped by 33 percent over the last five years as data and automation projects in these areas took hold.
Additionally, an ever-increasing set of over-the-counter products are being cleared, which is driving a much more data-driven approach. This approach has required significant work in migration of workflows and new connectivity.
Automation of collateral flows between counterparties and clearinghouses, as well as rapid affirmations and confirmations across the equity, foreign exchange, rates, and commodity product, has also been increased.
Celent concluded: : “Growing digitalisation of trade and client lifecycle means a need for a new and scalable solution, and many financial institutions are already working on it. Accessing this data, from asset class performance to client behaviour, is a key initiative for many players.”
“The challenge is how to harness the data coming from different sources and formats to generate meaningful insights in the most rapid time possible. Advanced data and machine learning can only be leveraged after the data is correct and robust.”
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