About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Know Your Partner – Cicada on Counterparty Data

Subscribe to our newsletter

Following on from the risk data work it had conducted with clients, including a global insurance company, Cicada’s strategic alliance with risk management vendor Algorithmics – signed last spring (Reference Data Review, May 2003) – marked a milestone in the company’s foray into the world of risk. While Algo brought to the table its suite of risk management systems, Cicada was to focus on data integrity, cleansing data where necessary and facilitating the integration of internal and external data sources.

As it began work with clients, Cicada found that it was increasingly focusing on the quality – or lack of it – of partner data: the descriptive information relating to a firm’s counterparties and potential counterparties. Firms, it seems, have a poor grasp of precisely whom they are trading with, and this can be a major obstacle to the secure settlement of transactions, either electronically or otherwise.

According to Richard Bennett, vice president, Europe, for Cicada – and former Algorithmics executive – partner data involves establishing an understanding of the legal entity structure of the firms an institution does business with.

That, he says, involves looking at where processes reside within an organization, where perhaps certain trades are made in London but settled in Hong Kong, for example. This also includes linkages between counterparties and counterparty structures. “The idea is to get a clear view, from a risk perspective, of the exposure you have,” he says. The results have repercussions for many areas of the business, including client account management, risk management, trading and back office, and client relationship management.

This focus on knowing your counterparty has been driven by a number of factors. A major one has been the collapse of Enron. A large number of financial institutions had direct exposure to Enron. But when, wanting to get a picture of their overall exposure to the bankrupt energy conglomerate, they dug a little deeper, their financial controllers found much broader exposure, resulting from Enron’s use of SPVs (Special Purpose Vehicles) and the issue of certain securities by different subsidiaries.

Another driver of the need for a process to manage partner data is the growing complexity of the business. The corporate landscape is constantly changing, making it difficult – and even more essential – to keep on top of whom one is dealing with.

Finally, a raft of new regulatory measures has raised the bar in terms of requirements for institutions, among them Sarbanes-Oxley, the Patriot Act and, perhaps most importantly in the risk area, Basel II.

As with other areas of reference data, Cicada prefers to think of partner data management as a process, rather than embracing the concept of the Golden Copy as an end-all. “It’s difficult to get one copy of the data to fit all downstream applications,” says Bennett. Moreover, there is no single source and, once collected, the data doesn’t sit still. So, while some of the partner data requirement may be bought in from outside – from business information suppliers such as Standard & Poor’s or Dun & Bradstreet – much of it will be generated internally.

The difficulty of putting the two together and managing the result on an ongoing basis is good news for Cicada. “Each firm, in practice, is completely different,” says Bennett, “on an overall data quality management basis. We have been doing this ourselves for some time and thought we could get more leverage through the relationship with Algo. Clients want a combination of process, cleansed data and analytics.”

This generates two indicators – loss-given defaults and probability of default – that need to factored into a firm’s overall credit view, a crucial requirement of Basel II. This view is essentially a picture of a firm’s risk of operations, the risk it faces each time it opens its doors in the morning.

Cicada and Algo are now offering both risk data and managed risk solutions, or a combination of the two, initially to Algorithmics’ existing client base. “Implementing any risk solution is long, laborious and expensive, with a low level of certainty of outcome,” says Bennett. “One of the objectives is to give a certainty of outcome, and to do that in a way that is fully integrated into the Algo suite means a reduced set-up time.” Bennett expects overall return for clients to improve as the two partners gain more expertise through market experiences.

In partnering with Algo, Cicada was looking for a risk vendor with the “right footprint” – both geographically and with respect to user types. Algo has clients both sides of the Atlantic and beyond, primarily in the banking and brokerage businesses. This presence has helped Cicada differentiate itself from others offering similar services in other segments, such as Barra within the buy-side community and RiskMetrics in the asset management, hedge funds and treasury areas.

So far, he says, the business is getting a warm response. Cicada and Algo pitch their services to the chief risk officers within financial institutions and their teams. Bennett says a number of bids have been made, adding that the Basel II timeframe is a substantial factor in determining the timing of such projects.

Currently, the Basel II requirements are slated for introduction by the end of 2006. This implies that firms will need to have systems in place by the end of 2005, in order to collect the required year’s worth of data in order to comply. This, in turn, suggests a decision-making period over the next 18 months. That schedule could be sent off course, however, if Basel II’s timeframe is delayed, which is to be determined next month.

Either way, sooner or later, firms will be required to apply counterparty descriptive data to their overall credit risk positions. Cicada hopes to be waiting in the wings when that happens.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Taming the Private Markets Data Beast: Solving for Valuation, Integration, and Reporting in Alternative Investments

Available On-Demand Institutional activity in private markets has surged as organisations’ traditional investment theses have been upended by global economic volatility, geopolitical instability and fee compression. In their search for better risk-adjusted returns, they have found a rich seam of alpha from private equity and credit, real assets, venture and hedge funds, as well as...

BLOG

Testing Industry Perceptions at Data Management Summit London

Every year at the A-Team Group Data Management Summit we take the pulse of the financial data and tech industry on a range of critical topics of the day. We do this through audience participation questions during the day-long event, urging delegates to interact with speakers and other participants via remote voting on salient questions....

EVENT

Data Management Summit London

Now in its 17th year, Data Management Summit (DMS) London returns In April 2027, to explore how to use data and AI to drive measurable business outcomes reliably, repeatedly and at scale.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...