88% of financial institutions believe they would lose competitive edge; 79% believe profits would decrease through poor/flawed models
MathWorks, the developer of MATLAB and Simulink, today releases research into the business value and importance of data and models in financial services. Buy- and sell-side industry participants at major financial institutions stressed the importance of models both in terms of alpha generation and risk mitigation.
The full report from MathWorks is available to download here: www.mathworks.co.uk/financereport.
Highlights of Key findings:
• 88% of financial institutions believe they would lose their competitive edge, 79% believe their profits would decrease, and 54% believe risk would be increased, if they were operating poor models – for example, flawed or outdated models
• Slow model development will result in firms lacking the agility to respond to market changes, and ineffective risk management , say 82% and 74% of firms, respectively
• Quality of data (67%), smart models (54%), and speed of execution (50%) are the most critical elements of a successful trading strategy
• 59% of financial institutions are looking to increase levels of automated trading; 67% of sell-side and 46% of buy-side firms are looking to increase levels of automated trading
• Only buy-side respondents believe automated trading models have had their day, and 31% of buy-side firms are looking to move towards alternative trading models
• 54% of financial institutions are looking to improve the execution times of models
• Cost (65%) and risk (62%) are the biggest concerns of integrating models into business processes
• It is currently taking ‘months’ (51%) to integrate models into business processes. However, the buy-side would like to cut this down to ‘days’ (75%); the sell-side ambitiously wants to reduce this time to mere ‘hours’ (40%)
• 83% of financial institutions are trying to speed up the process of model development
The data deluge
• The biggest issue associated with the data deluge is data quality, with 68% of respondents citing it as a challenge. Creating effective models (57%) and data variety (38%) were also among the main three issues facing financial services
• The actual volume of data is not a core challenge for financial institutions, with only 32% citing it as problematic
• The datasets being dealt with are, in general, not as large as externally perceived: 49% of financial institutions are dealing with datasets in gigabytes; 28% with megabytes
Steve Wilcockson, industry manager – financial services, MathWorks said: “Models are integral to the success of financial services – 88% of financial institutions believe they would lose their competitive edge if they were operating ‘poor’ models. Yet models and the processes that surround them are not always Board-level priorities. Financial executives should take time to understand processes around developing and implementing models, and enable financial engineers to improve reliability and transparency in risk, trading, valuation, forecasting and other numerical finance activities.”
The research report, entitled ‘Modelling and Analysis in the wake of the Global Financial Crisis: Perspectives from the Financial Services’ collates the findings of a survey conducted at MathWorks financial services event, MATLAB Computational Finance Conference.