HOW TO REDUCE BONDS SETTLEMENT FAILS AND MITIGATE CSDR FINES AND BUY-INS

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HOW TO REDUCE BONDS SETTLEMENT FAILS AND MITIGATE CSDR FINES AND BUY-INS

  • Riddhi Sen and Manuel Steiner
  • Published: 06 January 2021


The financial services industry has witnessed considerable hype around data science and machine learning in recent years. However, a quick Google search will confirm that there are very few concrete examples of it being put in practice in large institutions and delivering tangible results. 

Here at Capco, we strongly believe that data science can add significant value in financial services across multiple functions with high returns on investment. This latest series ‘Applied Data Science in Financial Services’ aims to highlight the common yet painful problems which Capco has solved using advanced Analytics techniques.  

Our second article focuses on a problem that is in the limelight nowadays: bonds settlement fails. On a yearly basis, banks must settle millions of trades. Bond trades failing to settle on the intended date not only causes a major issue for operational teams in terms of workloads of remediation activities, but with the new CSDR regulation expected to come into force in February 2022 (delayed from February 2021 due to the Covid-19 pandemic), this also threatens to impact the bank’s bottom lines through automated fines and buy-ins.

We have helped our client mitigate this problem by applying modern data analytics techniques that allowed them to identify quick wins.

Download our story to find out more.

CONTACT:  

Intrigued by our solution? Get in touch with our Data Science & Machine Learning capability lead, Riddhi Sen, or Capco’s UK R&D Lead, Jibran Ahmed