Another rising star of risk management share their thoughts on the four things set to change and advance in the financial sector. Thomas Bergermayer, Market Risk Manager at Erste Group, tells RiskMinds365 his thoughts on the future.
‘The next ten years in risk functions will [...] be quite unlike the last. The drivers of change will not be financial recovery and regulatory compliance, but technology-driven changes to banks’ business models and to the machinery of risk management. Ultimately, the transformation brought on by these developments could be greater than the cumulative changes of the last ten years.’
-Garside & Mitchell (2017)
Thoughts on upcoming developments in risk management are tightly connected to projecting the future requirements and necessary skills of a risk manager. Will dealing with application forms, documentation tools and Excel sheets still be the major part of the job? Or will the creation of algorithms, the investigation of complex data connections and artificial neural networks occupy most a risk manager’s working hours?
According to a study by McKinsey (Härle et al, 2015), currently half of the risk management staff is working on administrative tasks, such as credit processing, whereas only 15 percent are dedicated to analytics. Estimating ten years into the future, these numbers would have shifted dramatically, leaving 25 percent to the administrative tasks and 40 percent to number crunching and development of algorithms. Similarly, Garside and Mitchell (2017) also see administrative tasks shrinking to half their size and the percentage of strategic advisers increasing from 20% to 35%. So, who will belong to these up-and-coming groups? Often the trending classification “Data Scientist” is named in this context. While well-functioning IT areas are even more essential for successful banks in the future, the people handling the data are equally important.
But what defines a data scientist and is he or she still a risk manager as we know it? While some might view “data science” as a more modern label describing statistics, there are a couple of fields combined in this term. As Cheema (2017) describes it in his article, there are four main ingredients – data, technology, science and business.
Data & Technology
The aggregation and storage of data is more popular than ever and although banks are continuously increasing their capacities, they are facing the problem of creating data silos within their own organization. Without meaningful data systems and possibilities to connect information stemming from various source systems, these large piles of data are unusable.
The science component builds on the database, creating meaningful analyses and predictions. Deep learning and neural networks build on traditional statistics. In order to realise these innovations, a sound technological background is needed.
Business, the fourth component, should not be underestimated, as the best models are only truly useful if detected correlations have an economical background and resulting conclusions are actively explained and applied to the existing business.
Data scientists in risk management, as well as in the whole bank, work together and combine these requirements to overcome potential future challenges to the field. Self-learning models and neural networks will need time until they receive regulatory approval with the root problem being the inability to validate these new inventions using traditional methods.
In addition, while developments like Crowdsourcing might be able to boost technological progress, they also incorporate substantial additional requirements for privacy and data protection.
To conclude the opening remarks – as the area and definition of risk management will develop and change significantly over the next years, the operative people, the risk managers, will evolve as well.
The views expressed herein are the views of the author and do not necessarily reflect the opinion of Erste Group Bank AG. The information herein cannot be used to infer any opinion about the future financial position of Erste Group Bank AG. This document does not constitute an offer or invitation to purchase or subscribe for any shares or other securities issued by Erste Group Bank AG or any of its subsidiaries and neither it nor any part of it shall form the basis of or be relied upon in connection with any contract or commitment whatsoever. The information contained herein and this presentation shall not be further disseminated without written consent of the author.