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Risk Management in The Digital Era – Challenges & Road Ahead

-Soubhik Ghosh

BE (JU), MBA (XLRI), FRM, CFA (L2)
Introduction
Digital is the new normal. Digital technologies have led the transformation in the way organizations create,
deliver & capture values. The scale and speed for the transformation have been substantial, so much so that
it can be termed as digital disruption. The impact is over-arching and is felt across all industries – financial
services, energy & utilities, FMCG, retail, media & entertainment- to name a few. The adoption of digital
technologies has got all the more fillip due the Covid-19 pandemic driven isolation and work-from-home
measures. Now a very critical board-meeting or a sensitive geo-political meeting takes place in google-meet,
a case that was unthinkable in pre-pandemic era.

While digital led transformation has opened doors to newer opportunities, it has also given rise to newer
risks associated with digital transformation. Identifying, understanding and addressing those risks will help
organizations build a readiness in managing those risks and maximize value from the business.

In fact, a thorough understanding of digital technology led transformation can also be applied to risk
management framework, enabling organization to take a more nuanced and balanced approach to digital
technologies.

Elements of Digital Disruption – Building Block for Digital Risk
Data Management
Let me start with a few example to illustrate how and to what extent data is generated.
 In 2020 on an average every human has created 1.7MB of data every second
 In 2020 we have created 2.5 Quintillion databytes per day, yes – 2.5 Quintillion means 2.5 followed by
a staggering 18 zeroes
 Over the last two years alone, 90 percent of the world’s data have been generated

Naturally, organizations will also have to deal with over-whelming data stream coming in its way. Any
organization will have to be ready with required infra, capability and capacity to deal with the 5Vs (Volume-
Velocity-Variety-Veracity-Value) of data.

Key elements of data readiness include – robust data governance mechanism, data storage infrastructure
and processing capability (Big Data) capable to deal with various types of structured and unstructured (text,
image, email, social media post etc) datatypes (Volume, Variety and Veracity), advanced analytics engine to
extract value from high-velocity data.

Robotic Process Automation
In this digital era of Big Data, an evolving enterprise risk function requires data collection from various
sources pertaining to various dept. The function of data collection and rudimentary processing of the same
can be automated by Robotic Process Automation (RPA), turning it into a sequential or parallel smart
workflows repeating itself seamlessly without intervention. In the age of 5V-data, it is imperative that
processing of data is done efficiently so that risk executives can concentrate on more value-added piece of
gleaning actionable insights at board level. As per a McKinsey study, ~30-45% of the respondents think that
RPA can bring down costs by more than 5-15%.

Advanced Analytics and Decision Automation Engine
After RPA helps data ingestion into the storage servers (supported by cost-efficient cloud architecture), then
we need capability to analyse the data.

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