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Tuesday 17th November 2020



The reliability and accuracy of reporting is key to ensuring confidence in the financial sector, yet there is limited regulation on data quality and the software used, a lack of consistency and no agreed documentation of modelling. This is in contrast to medicines and medical devices, where there are auditable processes in place with the requirement to demonstrate the source of data used and the need to show documentation of the workings of the software. This is important because of issues related to the efficacy and safety of medicines, such as how to collect reliable evidence, what the longer term effects of medicines are and how to keep medical data secure.

Mathematical and, in particular, statistical techniques provide rigorous approaches to evaluating quality of data, models and software. This event explored and compared the use of standards and approaches to regulation in medicines and medical devices with those in the financial and pensions sectors and consider what improvements could be made.

Aims and Objectives

As well as providing a useful comparison of standards and approaches to regulation in the medical and financial sectors, this workshop will provide an overview of the different expectations of regulatory bodies. It will look at approaches to assessing the quality and validity of data, statistics, computing and mathematics in the financial sector which differ substantially from those in the health sector.  Speakers explored these issues, with a focus on pensions, investments and fraud. The talks looked at risks in the financial sector, ethics, handling uncertainty and achieving transparency which is important for trust. The final session was be a discussion of methods to investigate how regulation could be more efficient and effective.

Some specific issues that were explored are:

  • Empirical basis for inputs into projection software and the transparency of the rationale for assumptions used in projection software
  • The choice of software
  • Handling of uncertainty
  • Sensitivity analysis
  • Risk and de-risking.

This event was of interest to those working in finance, quantitative finance, economics, actuarial mathematics, statistics and data science.

The event was developed and delivered in collaboration with the Royal Statistical Society and its Finance and Economics Special Interest Group.

This paper from University College London may be of interest to registered delegates. 

Registration and Venue

The workshop took place virtually via Zoom.

In Collaboration with