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

A-Team Insight Blogs

SGSS’s Rose Elaborates on Challenge of Determining Fair Valuations

Subscribe to our newsletter

Société Générale Securities Services (SGSS) currently uses 13 data feed providers in order to price an average of 17,000 bonds on a daily basis, according to Olivier Rose, head of international projects data management for the firm. Although 80% of these valuations pose no problems for the securities services provider, 20% fall under the auspices of fair value and are therefore a significantly more challenging proposition.

The firm is currently reviewing its fair value strategy in light of the changes going on within the accounting space at a global and European level, says Rose. The main part of this work is reviewing the providers of evaluated prices on the market, of which there are many, and determining the differences between these vendors. “It is a very expensive process to search for the most relevant prices across the market,” notes Rose.

The biggest push within the market in the valuations space seems to be for more data around prices, especially those that fall under the fair value category, and SGSS is no exception. Rose indicates that an audit trail for historical prices is also important, as well as current prices, thus adding yet more strain on firms’ data management capabilities. “You may need to have access to pricing data about instruments that were traded a long time ago in order to meet both regulatory and client requirements,” he says.

This also means that both the front office and the back office both need to be on the same page with regards to pricing practices and data sharing. However, these teams are using the data for very different ends and there is a tension between the two spaces, notes Rose. The use of a central core neutral platform that can be used across the institution is therefore likely to be even more important going forward.

SGSS is certainly keen to be engaged in the debate about how best to approach data management as a whole, including valuations data. At FIMA last year, Rose also spoke about SGSS’s other endeavours to centralise its eight separate siloed data systems into one core central database across the business. He noted that the firm is currently far away from realising this goal but was hopeful that C-level buy in as a result of new risk management and compliance requirements would materialise this year.

Subscribe to our newsletter

Related content

WEBINAR

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

Date: 7th October 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes 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...

BLOG

12 Leading Providers of Semantic Layers in Modern Capital Markets Data Stacks

Reconciling fragmented financial data across disparate trading systems, risk engines and regulatory reporting pipelines is a challenge that frequently results in conflicting analytical outputs, costly reconciliation cycles, and elevated operational risk under frameworks like BCBS 239 and FRTB. The enterprise response has been a move away from continuous database consolidations towards centralised semantic layers. Positioned...

EVENT

AI in Capital Markets Summit London

Now in its 3rd year, the AI in Capital Markets Summit returns with a focus on the practicalities of onboarding AI enterprise wide for business value creation. Whilst AI offers huge potential to revolutionise capital markets operations many are struggling to move beyond pilot phase to generate substantial value from AI.

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...