Sensitivity analyses are used in data analysis to determine how independent variables affect dependent variables under certain conditions. This gives researchers and data analysts the ability to see how sources of uncertainty within their data modeling may be contributing to overall uncertainty. Scientists have been using sensitivity testing to refine their mathematical models for years, but according to realtimecampaign.com, it’s only recently that business owners have begun to get on board with this technique.
How Companies Are Using Sensitivity Testing
Want to find out How Financial Companies Use Big Data To Make Decisions and what role sensitivity analyses play in that larger picture? It’s simple. Companies, including financial service providers, capture literal quintillions of bytes of data on their customers and the transactions they perform each day.
This data contains a great deal of information that can be used to improve services, analyze investment options, and advance cybersecurity practices, but it’s very difficult for data analysts to separate the clients’ most essential data from the rest. Performing a sensitivity test can help them narrow down the relevant data set and reduce the amount of time required to analyze it. This, in turn, helps to ensure that service providers are making well-informed decisions.
How It Works
It would be impossible to analyze the amount of data used by large companies by hand, and performing sensitivity tests would be equally difficult without the help of artificial intelligence (AI). AI-driven software programs can process an incredible amount of data extremely fast. Well-designed programs like Synario can thus reduce the amount of time required to analyze even an incomprehensibly large set of data from the weeks it would have taken with less advanced software to mere minutes.
The Importance of Rapid Stress Testing
Rapid stress testing uses computer-simulated scenarios to test how an investment portfolio or a financial institution will fare in a wide variety of situations. Stress tests are only helpful if those running them have access to relevant data, though. There are tons of variables that affect financial markets, and not all of them play an equal role in determining the robustness of a portfolio.
Sensitivity testing can be used to determine which data sets are most relevant and most likely to impact the financial institution’s performance. The ability to refine stress testing models allows companies to deepen their insight into risk exposure. While it’s important to consider every variable and possible outcome, the most catastrophic potential outcomes shouldn’t drive decision-making if they are only possible given a very particular and unlikely scenario.
The Way of the Future
Work for a financial service provider or another organization in this field that hasn’t yet gotten on board with AI-driven advancements in data analysis? Get the company on track by clicking here to learn about options. There’s no denying that big data analysis is the way of the future. Those unwilling to change will only get left behind.
The Bottom Line
The world is a complex place. So are its financial markets. Modern financial institutions need equally complex solutions to their problems, and sensitivity testing is one of them.