Nearly 81% of the financial firms existing today concede that data is their most tactical asset, next to people, processes and technology. In accordance to that, the realization of deploying sophisticated analytics is also beginning to bear fruit in the brains thriving in the financial sectors.
Advanced Analytics in the financial services market is estimated to mature from $3.65 billion in 2013 to $6.65 billion in 2018, at a Compound Annual Growth Rate (CAGR) of 12.9% from 2013 to 2018. In terms of regions, North America is estimated to be the biggest market in terms of revenue contribution, while emerging economies such as Middle East and Africa (MEA), and Latin America (LA) and Asia-Pacific (APAC) are anticipated to practice increased market traction with high CAGRs, in the due course.
It is likely that 24% of high-growth companies plan to upsurge their expenditure by at least 20% over the next two years, compared to just 7% of low-growth companies. The most forward-looking analytics functions at high-growth companies are spread across sales (24%), finance (22%) and marketing (14%), while at the other firms, the finance function itself has conquered most of the part.
Analytics when bombarded with financial services, explodes into a diverse set of analytical solutions.
FLIPPING THE SIDE
Fastest growing financial companies are 2 times in the cards to be centering on data and analytics in revenue-enhancing areas, such as marketing and sales. They are gradually more investing in data for the upside potential, rather than obsessed by the risk and regulatory agendas. The laggards, in contrast, are more often engrossed on compliance- related data management initiatives and they are purely attenuating the potential of growth that analytics can offer.
It’s high time that the firms flip the side from dying to living. Making that flip entails greater development in data and analytics. Those that have comprehended the God word called, ‘Analytics’ have already moved farthest away by beginning with descriptive, risk and marketing analysis to predictive and big data analytics.