Big Data to revolutionize Banking, Insurances and Financial Services

By 26 July 2019 No Comments

How can BIFS companies differentiate themselves using Big Data technologies?

Banking, Insurance and Financial Services (BIFS) evolve today in an increasingly complex situation, facing high regulations and the emergence of new competitors, like fintechs as well as GAFA and BATX. BIFS must also deal with a growing volume of data. While mastering Big Data is a difficult challenge, it also represents an immense development opportunity which could allow BIFS to differentiate themselves from all their competitors.

In fact, Big Data promises are numerous for this industry, from fraud detection to a better customer understanding and management, to the development of new offerings. With Big Data, BIFS could optimize their internal processes, to maintain or even increase their market share and enhance their positioning with innovative competitors. This is one the reasons BIFS are the companies investing the most in Big Data ($50 billions between 2010 and 2015 [1]) .

Business Intelligence (BI) and Analytics technologies offer many solutions that enable BIFS to achieve these objectives. BI is modernizing itself and allows an autonomous and decentralized data analysis, while analytics help companies to develop important descriptive, predictive and prescriptive capabilities to make better decisions and have a better governance.

To succeed in developing effective BI and analytics solutions, BIFS need to increase the use of analytics tools in all their departments: if analytics tools are widely used by BI experts, business analysts and data specialists, only 20% of so-called ‘citizen data scientists’ use them [2]. Also, BIFS need to adopt some practices that will allow them to fully exploit data opportunities.

In this context, how BIFS can overcome all these challenges and ensure analytics fulfil its promises?

Download our white paper “Banking, Financial Services, Insurance: getting the most out of data” here.

[1] Accenture
[2] Dresner Advisory Services 2017 Advanced and Predictive Analytics Market Study

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