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Embracing Automation and Collaboration Tools to Inject Reference Data into the Trade Lifecycle
Digital transformation in the financial services sector has raised many questions around data, including the cost and volume of reference data required by each financial institution. Firms need flexible access to the reference data required to ensure workflows can proceed without interruption. ‘One-size-fits-all’ bulk data licensing models are increasingly less fit for purpose. Emerging solutions…
Can ‘Observational Learning’ Help Improve Data Quality?
Data quality is a pre-requisite for financial institutions seeking to automate their operations. But given the huge volumes of transaction data, often in a wide array of formats, it is very difficult to achieve. Can newer AI-based techniques such as observational learning actually help or are they just hype? This white paper explores: What observational…
How to leverage the LIBOR transition to improve your data management game
The final goodbye to Libor has been described as the Y2K moment for data managers in financial services – and with the phase-out slated for the end of 2021, firms need to act now to ensure a smooth transition. The replacement of Libor with alternative benchmarks presents an immense challenge for financial institutions, especially given…
Adopting AI for Superior Reconciliations
Firms’ reconciliation and exceptions management processes are manually intensive, expensive and prone to error. With rising compliance costs and greater competition narrowing margins in financial services, firms are looking to streamline their reconciliations processes through automation, giving them the opportunity to reduce the number of exceptions they manage and the time it takes to deal…
Data as the Catalyst for Innovation in Asset and Wealth Management
Fund managers and wealth management firms are being squeezed between downward pressures on sources of revenues and upward pressures on costs. Firms are facing a migration to passive investment funds, with some research suggesting a one-third drop in active management fees by 2023. Meanwhile, the ongoing regulatory onslaught is adding to costs. Under pressure to…
Applying Emerging Technologies to Real-World Business Challenge in Financial Services
Today’s world of technology is evolving at lightning speed for financial services firms. Terms like artificial intelligence (AI), machine learning (ML) and distributed ledger technology (DLT) bandied about, technology conversations seem to be all about hype. The reality is that financial services firms need to understand the impact that these new technologies could have and…
Embracing Client Behavioural Analysis for Improved Business Outcomes in Fund and Wealth Management
Emerging innovative technologies are presenting financial institutions with a unique opportunity to better understand the needs of their clients and cross-/up-sell accordingly. Tapping into new data sets and advanced data management techniques, financial institutions are starting to perform the kind of client behavioural analysis common in other industries. Retail financial institutions like fund managers are…
Hitting the Reset Button On Investment Analytics
Investment managers are rethinking their approach to managing portfolio data and analytics in order to stay competitive. The operational and technological limitations of their legacy systems and platforms are making it difficult for many to differentiate their offerings and deploy new operational models. Moreover, the continued stress on cost reduction means they are under persistent…
Getting a Grip on Fragmented Risk Data – A Holistic Approach to Risk Information
This white paper is based on primary research by A-Team interviewing senior IT and Data Strategy managers at tier 1 and tier 2 banks. Risk management has been accepted as the new imperative for financial institutions of all types and sizes. But for Tier 1 and Tier 2 banks and brokerages, the complexity of their…
Syn~ Scalability Benchmark
Summary This document describes an exercise to measure the scalability and performance of the Syn~Settlements application upon a Linux/HP platform. The results recorded include: ~ demonstrated scalability consistent with a linear model; ~ peak throughput of the scalable system at 77K trades per hour; ~ demonstrated efficacy of quad-core processor architectures as a means of…