The leading knowledge platform for the financial technology industry
The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

Rates, Curves and Derived Data Management Remains a Neglected Area Following the Crisis, Says Xenomorph

Xenomorph, the analytics and data management solutions provider to global financial institutions, has today released its white paper ‘Rates, Curves and Surfaces – Golden Copy Management of Complex Datasets’. The white paper describes how, despite the increasing interest in risk management and tighter regulations following the crisis, the management of complex datasets – such as prices, rates, curves and surfaces – remains an underrated issue in the industry. One that can undermine the effectiveness of an enterprise-wide data management strategy, says Xenomorph.

In the wake of the crisis, siloed data management, poor data quality, lack of audit trail and transparency have become some of the most talked about topics in financial markets. People have started looking at new approaches to tackle the data quality issue that found many companies unprepared after Lehman Brothers’ collapse. Regulators – both nationally and internationally – strive hard to dictate parameters and guidelines.

In light of this, there seems to be a general consensus on the need for financial institutions to implement data management projects that are able to integrate both market and reference data. However, whilst having a good data management strategy in place is vital, the industry also needs to recognise the importance of model and derived data management.

”Rates, curves and derived data management is too often a neglected function within financial institutions”, says Brian Sentance, CEO Xenomorph. “What is the point of having an excellent data management infrastructure for reference and market data if ultimately instrument valuations and risk reports are run off spreadsheets using ad-hoc sources of data?”

In this evolving environment, financial institutions are becoming aware of the implications of a poor risk management strategy but are still finding it difficult to overcome the political resistance across departments to implementing centralised standard datasets for valuations and risk.

“The principles of data quality, consistency and auditability found in traditional data management functions need to be applied to the management of model and derived data too”, adds Sentance. “If financial institutions do not address this issue, how will they be able to deal with the ever-increasing requests from regulators, auditors and clients to explain how a value or risk report was arrived at?”

Related content

WEBINAR

Recorded Webinar: Managing the transaction reporting landscape post Brexit: MiFID II, SFTR, EMIR

The transaction reporting landscape has, for many financial institutions, expanded considerably in size since the end of the UK’s Brexit transition period on 31 December 2020 and the resulting need for double reporting of some transactions to both EU and UK authorities. It has also changed dramatically following the UK government’s failure to reach equivalence...

BLOG

Lack of Equivalence Post Brexit Raises Costly Data Management Concerns

The UK has finally left the European Union. A trade deal was wrung out at the eleventh hour, allowing the two sides to trade with zero tariffs and quotas, but the financial services industry has been left hanging – with talk of an MoU around the regulation of financial services being reached by March 2021...

EVENT

TradingTech Summit Virtual

TradingTech Summit (TTS) Virtual will look at how trading technology operations can capitalise on recent disruption and leverage technology to find efficiencies in the new normal environment. The crisis has highlighted that the future is digital and cloud based, and the ability to innovate faster and at scale has become critical. As we move into recovery and ‘business as usual’, what changes and technology innovations should the industry adopt to simplify operations and to support speed, agility and flexibility in trading operations.

GUIDE

Entity Data Management

Entity data management has historically been a rather overlooked area of the reference data landscape, but with the increase focus on managing risk, the industry is finally taking notice. It is now generally agreed to be critical to every financial institution; although the rewards for investment in entity data management appear to be rather small,...