Our research develops practical insights and tools that apply our expertise and technology to prevailing industry challenges. We hope this is useful, and please reach out to us if you would like to explore these topics any further.
Quantitative algorithmic and financial engineering, Data science,
Abstract. We propose a Traffic Light approach to backtesting Expected Shortfall which is completely consistent with, and analogous to, the Traffic Light…
Read moreCloud engineering, Data science,
Clients with a continuous, large stream of data coming in that needs to be processed really quickly and must always be up – regardless of hardware reliability…
Read moreCloud engineering, Technology re-platforming, Data science,
The open source big data processing framework Apache Spark has become the one-size-fits-all solution for big data and big calc problems. Chris Sawyer offers an…
Read moreBusiness process engineering and data organisation, Data science,
The convergence of new businesses models, new technologies and new regulations are giving many capital markets firms the impetus they need to resolve structural…
Read moreBusiness process engineering and data organisation, Data science,
Improvements to business process can deliver high-quality enterprise-wide data. The following five tests can improve your processes – the results of which could…
Read moreBusiness process engineering and data organisation, Data science,
Our hypothesis is that bad data is a symptom of poor organisational design; by implication, the by-product of a well-designed organisation will be normalised…
Read moreCloud engineering, Business process engineering and data organisation, Data science,
Big data is not a solution in itself; it’s a process accelerator – as is the case with most technologies.
Read moreBusiness process engineering and data organisation, Data science,
BCBS 239 is an unfashionable regulation. There are no calculation changes. No (clear) impact to capital charges. No specified new reports, no defined penalties…
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