Page 132 - Building Big Data Applications

130 Building Big Data Applications

machine learning help organizations create consistency and a personalized experience
across channels over time and give them a competitive edge.
None of this is net new except the changes in innovating the underlying infrastructure,
improved efficiency of streaming processing layers, deploying extremely faster networks,
and innovating cybersecurity and distributed data processing with neural networks.

The coming of age with uber banking

In 2015, an article appeared in Washington Post which read like this, “The neighborhood
bank branch is on the way out and is being slowly phased out as the primary mode of
customer interaction for Banks. Banks across the globe have increased their technology
investments in strategic areas such as Analytics, Data & Mobile. The Bank of the future
increasingly resembles a technology company”. Technology is transforming Banking and
it is leading to dramatic changes in the landscape of customer interactions. Today we live
in the age of the hyper-connected consumer. As millennials enter and engage in banking,
they are expecting to be able to Bank from anywhere, be it a mobile device or use internet
banking from their personal computer, at all times and have access to all services.
As former Barclays CEO Antony Jenkins described it in a speech the global banking
industry, is under severe pressure from customer demands for increased automation and
contextual services. He said “I have no doubt that the financial industry will face a series
of Uber moments,” he said in the late-November speech in London, referring to the way
that Uber and other ride-hailing companies have rapidly unsettled the taxi industry”. The
outcome of these mounting pressures over the last 8 years from 2010, has led to
banking trends migrating to becoming more contextual, social, and digital to respond
to changing client needs.
The financial services industry segments including banks, mortgage, insurance, and
other associated industries have been facing an unprecedented amount of change driven
by factors like changing client preferences and the emergence of new technologydthe
Internet, mobility, social media, etc. These changes are immensely impactful, especially
with the arrival of “FinTech”dtechnology-driven applications that are upending long-
standing business models across all sectors from retail banking to wealth management
and capital markets. The new market of a major new segment, millennials, use mobile
devices, demand more contextual services, and expect a seamless unified banking
experience, something similar and aligned to what they experience on web properties
like Facebook, Amazon, Uber, Google or Yahoo, etc.
A true digital bank needs to identify all the key areas where itis capabilities will need
transformation to occur. Some of these include the following:

Offer a seamless customer experience much like the one provided by the likes of
Facebook and Amazon, a highly interactive and intelligent applications stack that
can detect every customer’s journey across multiple channels
Offer data driven interactive services and products that can detect customer prefer-
ences on the fly, match them with existing history and provide value added