RD e-book Blog 1 website.png

Reference data and financial transaction processing

This blog highlights a discussion point from our comprehensive eBook: “Reference Data: The Essential Guide”.

In terms of oiling the wheels of financial transaction processing, reference data plays an increasingly critical role in the smooth running of global financial markets. Touching on every part of the transaction lifecycle, it is estimated to account for up to 70% of the data required to execute and settle financial transactions.

Reference data is the essential information that underpins all financial transactions, providing the DNA or ‘official’ identification of the traded instrument itself, and the names and location of the parties involved. It is the important ‘finer detail’ that identifies and specifies the asset classes, products, counterparties and other information associated with a financial transaction.

The long-and-the-short-of-it is that wrongly labelled products cause transaction failures; in the worst case scenarios, feeding faulty data into ‘the system’ can result in more devastating systemic failure, as the outage of UK’s Air Traffic Control system so aptly demonstrated. Beyond failed trades, in terms of operational risk, back office recording and reporting through myriad internal and external process workflows are essential links in an efficient transaction lifecycle. As such, there are operational, financial, commercial and regulatory risks associated with poor reference data management.

Better data, better data management

  • Improve operational efficiency, customer service and business relationships

  • Reduce business costs and risk exposures

  • Enhance competitive offerings in a busy marketplace

  • Avoid the pain of regulatory non-compliance

If follows, then, that robust reference data management supports effective risk management. Credit risk exposure, for example, is linked directly to accurate counterparty information; reliable product classification facilitates better management of market, settlement and reporting risk, and operational risk is now a mandated element of a regulated firm’s overall risk calculations and associated capital adequacy provisions.

At the same time, banks, institutions and buy side firms operate in a highly competitive environment, with enormous capital and resource pressures, in a challenging economy and associated market volatility, rising interest rates, high inflation and overall, a very much higher cost of doing business.

As the number of financial markets, assets, issuers, products and participants continues to grow - potentially by 100 times in the next decade - with an associated increase in data volumes and complexities, the impact of reference data on financial markets will be even more important in the years to come.

To find out more about reference data trends and challenges, download our comprehensive eBook “Reference Data: The Essential Guide”.


Reference Data: The Essential Guide

As the number of financial markets, assets, issuers, products and participants continues to grow, our latest guide explores the increasing impact of reference data on financial markets.

Related Insights

  1. Article
    Data normalisation - standardising the presentation of data to ensure it is consistent across required fields and records - is an essential component of effective financial data management, enabling reference data in particular to be recognised, interrogated and incorporated into required data workflows much more easily, and minimising the risk of reconciliation and compliance ‘fails’.
  2. Article
    Not only is there a requirement to report additional information, EMIR Refit also places enormous emphasis on enhancing and harmonising the quality of the data itself to support end to end validation and data reconciliation obligations, and to mitigate the risk of misreporting - and having to report associated reporting failures.
  3. Article
    Big isn’t necessarily always best when it comes to data services delivery and it’s important for financial firms to weigh up the relative pros and cons when considering what makes the most sense for them to support their data management needs.