Changing Landscape of Finance with Big Data Analytics

Now a popular career choice for engineers and analysts, Big Data analytic training is making its presence felt in the Banking and Finance sectors.

Deep learning and Big Data analytics are the modern catchphrases in the business parlance. Without mentioning Big Data applications, there seems to be a vacuum in the realm of Information Technology and statistical methods. With advancements in quantum computing and computer vision, Big Data analytics has come within a close ambit of organizations looking to invest in Big Data Analytics training and improving their overall data management infrastructure.

Here, we explore the changing paradigm of Finance and related financial services industry with the advent of Big Data and Deep Learning technologies available for adoption at all-size enterprise levels.

Explosive Market Growth of Predictive Intelligence with AI

In 2016, the global Finance industry spent close to $130 billion into Big Data analytics and Predictive intelligence models in 2016. By 2020, this figure is projected to jump to a staggering $250 billion! A large part of that push is going to come from the ubiquity of Artificial Intelligence and Machine Learning algorithms forming the core of Big Data engines. Forecasting of financial data and reporting would be available real-time with better analytics presented in ‘data storytelling’ formats for all the portfolios and financial markets, including loans and insurance.

Augmented Capabilities into Cybersecurity

Cybercrime MO hasn’t changed much, but the speed at which they destroy business channels has intensified. One of the biggest challenges for the Finance industry hovers around cybersecurity. With Big Data intelligence, Finance cybersecurity teams can identify risks and fraud points with anti-money laundering guidelines.

With social media listening and neural networking technologies, Finance cybersecurity teams can significantly limit the damages with speedy recovery leveraging augmented Big Data capabilities and analytics.

Find Better Investment Markets with Profitable returns

Organizations can use financial data and analytics to gain invaluable insights into service trends, Marketing and Sales reporting, and Business Intelligence (BI). An estimated 89% of Financial organizations without any Big Data analytics training strategy run the risk of losing out on a potential investment deal, eventually losing the edge over the competition.

With Volume, Veracity and Variety (3V’s of Data), Finance sector enables the available computer programs to execute financial investments at speeds and accuracy that human financiers can’t match.

The Era of Chatbots, Intelligent Virtual Assistants and, Behold, the Robo-Advisors

Chatbots have made their ambitious entry into cloud contact centers, tele-marketing, website interactions, E-commerce and online trading already. But, in Finance sector, they are completely disrupting the paradigm of advising and consulting. Analytics powered by Big Data insights from leading Finance experts are translated to Robo Advisor communications.

Robo advisors translate and analyze the massive volume of Financial data to endorse investment and erect security measures to maintain consistent communication with minimal human interaction. This has reduced leakage of personal information to cyber criminals.

As Machines take full control of data centers, the Finance industry is slated to further transform dramatically by 2020.

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