Giles Elliott, Head of Business Development, Capital Markets, TCS
There is a saying in our industry that the easiest way to differentiate yourself is when things are going wrong.
But, data and how we use it is possibly the one area where it is truly possible to stand out. We have often focused on automation ahead of insights in the back-offices, and while the target of real-time statuses and close to market deadlines are critical, so is the need to generate unique insights and client experiences.
An example of an area in focus is CSDR and the likely rise in buy-ins and associated claims. We expect to see far more focus on the assessment of individual actions that lead up to these events, and attribution of fault, an area that is rarely clear cut. Prevention is better than a cure, and this is encouraging a raft of tools that actively avoid this scenario – from using AI to correct mis-formatted instructions and maximize windows for matching and escalation, to improving transparency on shared multi-party data, through to enhancing the evaluation of mitigation options including different borrowing channels where real short positions exist.
We have a lot of valuable data in the back-office that can be leveraged when trading or settling a technically short position. For example, where stock is on loan, the analysis of the probability of timely return can be made including factors like the point in the settlement cycle and notice periods, the counterparty in question, market liquidity, and the performance of the market itself. These can be used to influence decisions taken both at the point of trade through to the escalation path taken by operations.
Back-offices will be truly transformed when the insights held in our data directly influences the decisions that front-offices take.
SIFMA and TCS BaNCS present a Live Event on 'How can Digital Technologies Harness Data to Transform the Back-Office?' on 4th August 2020, 1:00 PM ET/ 7:00 PM CEST/ 10:30 PM IST. Read more to register for the Live Event.
Disclaimer: Views or opinions represented in this blog is based on author’s own research and does not represent TCS BaNCS.