The Big Challenge for Data Science in Investment Banking
Investment banking institutions have been much slower to embrace data science techniques when compared to their retail counterparts who regularly use analytics to evaluate churn, make product recommendations, and more. Legacy systems and legacy thinking have long held investment banks back when it comes to analyzing and extracting deeper insights from the wealth of data they collect. These systems have limited the speed and sophistication of recommendations to customers to manage risk and even build new, valuable data products. New competitors who are leveraging data science are changing this landscape.
The continuous adoption of data science in order to collect and analyze large sums of data continues to revolutionize organizations across all industries – and that includes the investment banking sector.
Investment Banks, like many other industries, face the risk of disruption by upstart companies, such as LearnVest and Mint, leveraging data to build new products and services. In order to compete with these upstarts, these banks will need to turn their insight into production analytics to mitigate the risk of disruption.
As we move into the future, there’s no doubt big data will continue to transform and shape the financial services industry as a whole. Here’s a look at how data science is creating huge changes in the investment banking sector.
Data Allows more Accurate and Timely Decisions
The success of an investment bank depends on optimizing various business decisions in a day which are based on data that changes quickly with every activity. For this reason, many decisions must be codified and executed automatically.
From risk management to capital allocation, improving the quality and flexibility of these decisions can help drive profitability. For example, one major European investment bank estimated it could save upwards of $1 billion per year in capital allocation costs if it were able to have a more real-time view of capital needs across lines of business.
Big data systems allow investment banks the ability to enable real-time decision making.
