How SMAC impacts Financial Services

The dilemma most of us, as Business Managers in Indian Financial Services, have faced through the last decade was - "Should Technology be driving business or should Business be driving Technology?" As we introspect on the developments in the last one year and take stock of where we stand in 2015, the obvious answer stares us in the face - “Big Data" today has become the critical differentiator of all successful organizations in the financial services industry in India. Indian CEOs and Business Leaders swear by the disruptive power that Big Data unleashes in transforming businesses. Big Data is high volume; high velocity and high variety information assets that require new forms of processing to enable enhanced decision making, insight, discovery, and process optimization. Social, mobile, analytics and cloud - referred to as SMAC is driving the growth of Big Data across the financial services domain. Indian financial services is embracing this SMAC technology in digitizing its business and transforming business models at a rapid pace.

Big Data is characterized by the following:

Volume: prefers to the large quantity of data. It’s estimated that 2.5 quintillion bytes (2.3 trillion gigabytes) of data are created every day. By 2020, we are expected to create 40 zettabytes (43 trillion gigabytes) of information.

Velocity: refers to the speed of data inflow and the rate at which this data needs to be processed. By 2016, it is projected there will be 18.9 billion network connections – that’s almost 2.5 connections per person on Earth.

Variety: refers to the diverse types and formats of data generation sourced from various mechanism e.g. Social networking, videos and feeds. 30 Billion Pieces of content are shared on Facebook every month. 4 Billion+ hours of videos are watched on YouTube each month and 400 million tweets are sent per day by about 200 Million monthly active users.

Veracity: refers to the data sourced from varied places that require testing of its quality. Uncertainty of data quality used to make decisions has till the introduction of Big Data, constrained the accuracy of analysis of such data.

Big data includes structured and unstructured data. Structured data is relatively easy to analyze. Unstructured data that includes voice, video, email and documents are difficult to analyze. Hadoop, the most popular tool - is an open source, distributed data processing platform that is designed to store and analyze Big Data across several thousand nodes.

Use of Big Data in pro-actively identifying, understanding and managing financial and operational risk can enable us to be more risk- aware, and ensure confident decision making at all levels in the organization. The applicability of Big Data in Capital Markets has opened up significant opportunities for the industry. Some of the examples are:

1. Credit Risk: Big Data empowers us with better predictive power, detect early warning signals by observing client’s ongoing behavior and take corrective action in time. We can develop risk profiles of new customers based on range of data including customer credit reports, spending habits, social media profiles and credit card repayment rates in a matter of seconds

2. Market Risk: Big data helps in complex credit counter party risk quantification, improved balance sheet optimization, and collateral management including real time exposure simulation for new client trades and market prices volatility changes

3. Operational Risk: Big data helps in enhancing trading surveillance controls and prevent frauds and forgeries in dealing rooms. It enables retrieval of instant snapshot of dealer activity including information from mobile phones, chat room sites and even door swipe cards.

4. Regulatory Risk: Big Data provides real time actionable insights that can improve the existing process in Anti Money laundering and allow for advanced statistical analysis of structured data and advanced visualization and statistical text mining of unstructured data. It can quickly draw hidden links between transactions and uncover suspicious transaction patterns.

Big Data when used to its full potential, can improve our reactive and predictive capabilities and present opportunities for pro-actively addressing process and risk, in our business operations. Big Data is considered the new wave and revolution in the IT industry , where social media, mobile, cloud and big data have joined hands to make the IT industry in financial services break out of the domination of legacy applications and promise customers that we will " deliver more, faster and at a much lower cost." The industry has embarked on a significant journey of transformational change and the power of reactive and predictive analysis will open up significant opportunities for the financial services industry.
- As told to Jasmine Kohli