Banking / Finance

Top 10 big data trends in 2016 for financial services

2015 was a groundbreaking year for banking and financial markets firms, as they continue to learn how big data can help transform their processes and organizations. Now, with an eye towards what lies ahead for 2016, we see that financial services organizations are still at various stages of their activity with big data in terms of how they’re changing their environments to leverage the benefits it can offer. Banks are continuing to make progress on drafting big data strategies, onboarding providers and executing against initial and subsequent use cases.

For banks, big data initiatives predominately still revolve around improving customer intelligence, reducing risk, and meeting regulatory objectives. These are all activities large Tier 1 financial firms continue to tackle and will do so for the foreseeable future. Down-market, we see mid-tier and small-tier firms (brokerage, asset management, regional banks, advisors, etc.) able to more rapidly adopt new data platforms (cloud and on-premise) that are helping them leapfrog the architectural complexities that their larger brethren must work against. This segment of the market therefore can move more rapidly on growth, profitability and strategic (conceptual/experimental) projects that are aimed at more immediate revenue contribution, versus the more long-term, compliance and cost-dominated priorities that larger banks are focused on.
The market for data software and services providers is moving closer to a breaking point where banks will need to adopt, on larger scales and with greater confidence, solutions to manage internal operations and client-facing activities. This is not unlike the path we have seen cloud technologies take.
Here are some predictions about how big data technologies are evolving, and how these changes will affect the financial services industry:

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