Posts categorized "TimeScape"

Internal model approval, risk management and regulatory compliance

Achieving regulatory approval can be challenging if we consider that regulators are concerned about both the risk calculation methodology in place but also the quality, consistency and auditability of the data feeding the risk systems used for regulatory reporting.

The data management project at LBBW (Landesbank Baden-Württemberg), for example, was initiated to support LBBW’s internal model for market risk calculations, combined with the additional aim of enabling risk, back office and accountancy departments to have transparent access to high quality and consistent data.

This required a consolidated approach to the management of data in order to support future business plans and successful growth and we worked with LBBW to provide a centralised analytics and data management platform which could enhance risk management, deliver validated market data based upon consistent validation processes and ensure regulatory compliance.

More information on the joint project at LBBW can be found in the case study, available on our website. Any questions, drop us a line!

Posted by Sara Verri | 22 September 2011 | 6:21 pm

More formal management of instrument valuation needed

Xenomorph has today released its white paper “Instrument Valuation Management: management of derivative and fixed income valuations in a multi-asset, multi-model, multi-datasource and multi-timeframe environment”.

The white paper expands on the “Rates, Curves and Surfaces – Golden Copy Management of Complex Datasets” white paper Xenomorph published recently (see earlier post) and describes how, despite the increasing importance of instrument valuation to investment, trading and risk management decisions, valuation management is not yet formally and fully addressed within data management strategies and remains a big concern for financial institutions.

Too often, says Xenomorph, valuations (and the analytics used to process input and calculate output data) fall between traditional data management providers and pricing model vendors. This leads to the over–use of tactical desktop spreadsheets where data “escapes” the control of the data management system, leading to an increased operational risk.

Whilst instrument valuation is certainly not the primary cause of the recent financial crisis, the lack of high quality, transparent valuations of many complex securities resulted in market uncertainty and in the failure of many risk models fed by untrustworthy valuations.

“A deeper understanding of financial products reduces operational risk and promotes quality, consistency and auditability, ensuring regulatory compliance”, says Brian Sentance, CEO Xenomorph. “Clients’ requirements have evolved and portfolio managers, traders and risk managers recognize that it is no longer sufficient to treat valuation as an external, black-box process offered by pricing service providers”, he adds.

Nowadays, regulators, auditors, clients and investors demand even more drill-down to the underlying details of an instrument’s valuation. It is therefore important to implement an integrated, consistent analytics and data management strategy which cuts across different departments and glues together reference and market data, pricing and analytics models, for transparent, high quality, independent valuation management.

“Our TimeScape solution provides a valuation environment which offers rapid and timely support for even the most complex instruments, allowing our clients to check easily the external valuation numbers, based on their choice of model and data providers”, says Sentance. “Otherwise, what is the point of good data management if the valuations and the analytics used are not based on the same data management infrastructure principles?”

For those who are interested, the white paper is available here.

Posted by Sara Verri | 4 May 2011 | 12:41 pm

Rates, curves and derived data management remains a neglected area following the crisis

Xenomorph has 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.

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 recognize the importance of model and derived data management.

Rates, curves and derived data management is too often a neglected function within financial institutions. 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. 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?

For those who are interested, the white paper is available here.

Posted by Sara Verri | 24 February 2011 | 5:45 pm

"Cut and Paste" Valuation Services

You can talk about more robust modelling, more stringent scenario testing and even moving everything onto an exchange, but unless we move the principles of good data management (in my view: consistency, security and quality of all types of data) into the front office then we will continue to get front-office mis-marking as described in this article in the FT.

Thanks to Ralph Baxter from Cluster7 for highlighting this article for me and those of you interested in this topic of operational risk and spreadsheet mis-use should maybe go along to EuSpRiG this year, and maybe take a look at a paper Xenomorph presented at a previous conference.

Posted by Brian Sentance | 4 February 2010 | 9:49 am

OTC Valuation by SGSS

Given all the recent attention that OTC derivatives have received (see Geithner letter), then a topical update on the work we have done with Societe Generale Security Services (SGSS) on OTC and structured product valuation services has been written up on Securities Industry News. The work involved extensive integration with Mysis Summit, where our TimeScape data and analytics management system is used to provide "Golden Copy" of market, reference and derived data for the derivative products being valued. The section on TimeScape says:

"The Summit FT solutions are integrated with SGSS' market data software tool TimeScape, licensed from London's Xenomorph in November 2007. This produces a "golden copy" of end-of-day prices from 15 different information suppliers. The unit also processes information related to 70 different currencies and 5,000 volatility surfaces, which give three-dimensional views of how much and fast a security can move up or down. With Summit's product, each surface can include between 200 and 500 data points."

From talking to some of the SGSS team at our recent user group, the thing they most seem to value about TimeScape is its ease of use in describing and managing any kind of product, allowing product and market data specialists to use and customise the system without the need for specialist technology knowledge. This echos some of the things that were said about TimeScape after a demo to Lab49 last year. 

Posted by Brian Sentance | 20 May 2009 | 6:52 am

High Performance Spreadsheets

Another article about the operational risk generated by the usage of spreadsheets within the financial markets (see earlier posts), appeared in the April issue of Waters Magazine.
 
The articles highlights how spreadsheets are largely used within financial institutions and suggests that the current regulation requirements for more transparency and ad-hoc risk management might push the proliferation of spreadsheets even further. The articles also refers to the progress and improvements made by Microsoft in recent versions of Excel to increase the security of spreadsheets.
 
Xenomorph has worked closely with Microsoft on hosting its time series database within SQL Server 2008. The case study we have written together describes how SQL Server 2008 offers integration within Office Excel 2007 so that whilst the spreadsheet is still the end-user viewing tool, operational risk is reduced by engaging Excel 2007 as an analytics and reporting tool and not as a mean of storing data.
 
Our TimeScape solution offers more than 700 easy to use add-in functions to Office Excel 2007 and we are currently working on the use of Excel Services, part of Microsoft Office Share Point Server 2007, to further enhance the centralized approach to spreadsheet.
 
If you are interested in how Xenomorph solves the problem of spreadsheet management, then take a look at our (newly updated) website. Here we explain how to solve the problem and how Xenomorph Spreadsheet Inside technology can bring unstructured spreadsheet data and complex calculation within a centralized data management system, increasing transparency and reducing operational risk.

Posted by Brian Sentance | 8 April 2009 | 1:35 pm