The Big Data era and its challenges – Some concrete examples in Finance and Insurance
March 21st, 2018
Big Data, Smart Data, Open Data … there are many current trends around data, and rightly so, because the way we access and use data is about to revolutionize the business world.
Regarding Big Data, the unresolved issue was about data management and especially finding new solutions to increase storage capacity and analyze large volume of data. Today, no matter how much information you have to manage: this is no longer a problem thanks to new storage process, such as the distributed algorithms developed by Google for instance, but also thanks to new calculation methods. We can now consider having solved most of the technical barriers to move from “classic” data to Big Data.
The key consequence of this technical mastery is the nearly limitless value creation. Big Data will enable the retail sector as well as banks and insurance companies to have a more precise knowledge of their customers in order to improve their services and optimize their production. Taking the example of the e-commerce sector: the goal will be to follow a client on internet to find out about his preferences, his buying habits and to offer him targeted advertisements that aim at triggering the purchase. This precise knowledge of the customers is a way for companies to understand and anticipate their expectations, sometimes even before they are aware of it. In Banking and Insurance, beyond a better customer knowledge, stakes are multiple: risk or market movement anticipation, fight against fraud… Algorithms, computing power, speed and artificial intelligence will be the key components of this new paradigm.
How can the collected data be used in the banking and insurance sectors? How to move from BI (Business Intelligence) to the Big Data era? Discover our white paper which aims at giving an overview of the issues related to Big Data and especially thanks to some concrete use cases in Finance and Insurance.