Advantages of using Predictive Analysis Tools in Investment BankingBy CIOAdvisor Apac | Friday, November 30, 2018
In order to stay ahead of the competition curve, investment banks are now in pursuit of leveraging predictive analysis tools. Earlier, investment banks manually fetched important information from humongous amount of data on a regular basis to accomplish their objectives. However, by adopting predictive analysis tools, investment banks have been able to revamp customer experience and uplift the functionalities in their processes. These banks use predictive analysis tools to gather useful insights from all the available datasets. With the implementation of big data tools, massive blocks of data can be processed within seconds and the processed output can be used to address the queries of the millions of clients. By deploying these tools, the investment banks can make better predictions now and reduce risk anomalies in the process.
Having understood the advantages of using predictive analysis, investment banks are taking initiatives towards either investing in smaller predictive analysis start ups or acquiring them. Although banks plan to use predictive analysis tools on a daily basis, it will take time for them to completely employ these tools owing to several challenges, one of which is skill gap. Investment banks encounter problems while recruiting right people especially when it comes to hiring people with hold knowledge of such technologies. The industry witnesses lack of highly-experienced and efficient professionals in this complex field. Undoubtedly, when all these predicaments will be addressed and predictive analysis will be deployed on large scale, investment banks will experience a surge in the quality of solutions they provide.