Insights and News /

09 July 2020 6 min read

CSDR, the perfect opportunity for front-to-back collaboration to solve root cause inefficiencies

Mikhael Behzad

Mikhael Behzad
Manager | Financial services | London

Chris Dominy

Chris Dominy
Partner, expert in climate & sustainability, and capital markets

The UK government has recently confirmed that it will not adopt the CSDR Settlement Discipline Regime (SDR), however it still imposes a myriad of obligations in relation to the prevention and remediation of settlement fails in EU transactions.

With seven months until the SDR comes into force, on 1st February 2021, only 40% of organisations have completed a CSDR P&L impact assessment according to our recent CSDR market readiness survey1.

These potential P&L impacts mean that the cost of settlement fails is no longer the sole responsibility of the Back Office. Hence, reducing settlement fails should be a top priority for most organisations. In particular, firms need to review their front-to-back trading flows because root causes of settlement fails often emanate from processes, systems and teams in Front and Middle Office rather than being the result of issues within Operations.

These upstream root causes can be categorised into six key areas, as the diagram below illustrates. In this article, we will provide a brief view of the nature of settlement fails caused by front office booking model and system inadequacies, as well as the benefits that can be achieved from addressing these issues.


Trade Capture: incorrect trade bookings, e.g. as a result of manual trade entry, static data inconsistencies or issues related to settlement instructions, can lead to mismatches with the corresponding counterparty trade records.

Legal Entity Booking Model: organisations with complex legal entity structures tend to experience high volumes of breaks and errors within their back-to-back booking model. Increased regulatory scrutiny in light of Brexit has driven many firms to review and simplify their legal entity structure and mitigate the risk of misbookings. 

FO/BO Systems: root cause issues may also relate to fragmented systems architecture with poor Straight-Through-Processing rates, resulting in manual trade figuration and data uploads (and associated errors) between front office and downstream representation of the trade. In addition, known system functionality gaps may give rise to breaks and often result in “false positives” which could be avoided.

A number of CSDR workflow solutions currently available in the market may address some of the regulatory obligations pertaining to the management of cash penalties and mandatory buy-ins; however, substantial “quick win” and medium-term opportunities exist outside of this implementation effort. The significant risk to P&L has prompted a number of our clients to initiate end-to-end reviews of their front to back trading processes, in order to identify and remediate settlement fail root causes before they enter the cash penalty and buy-in realm.

The growing prospect of a no-deal Brexit at the end of the year further emboldens the need to address settlement fails root causes upstream and thereby alleviating some of the additional strains of implementing significant regulatory change in parallel.

Potential Benefits

We performed a trade capture and end-to-end booking model review for one of our clients. Outlined below are benefits the client realised within a short time frame from addressing some of the upstream settlement fail root causes:

  • substantial reduction in trade booking errors,
  • significant improvement of accuracy, timeliness and relevance of trade booking data, with clear root-cause and accountability of errors, and
  • cost saving and optimisation resulting in the prevention and active management of settlement fails at the root cause.

1 For further information on Baringa’s CSDR Market Readiness Survey July 2020, please contact

About the author(s):

Mikhael is a Manager within our capital markets business and Chris is a Partner within our Financial Services practice.

The authors would like to thank Michael Elter, Simon Gray and Roohi Mahapatra for their contributions to this article.

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