Page 33 - Banking Finance July 2023

ARTICLE

impact that may be occurring. The Data Scientist utilizes a
Dynamic data storytelling in the Indian
churn analysis model to evaluate the effectiveness of
Banking sector
changes to the sales plan and marketing campaign.
Some examples of using interactive data visualization are:
Visualizing loan growth: It is helpful to see how loans
Learning
have grown over time across various categories like
The data gathered during the final measurement stage
personal, home, and business loans to understand the
offers valuable insight and feedback that can be used to
Bank's loan offerings better and make informed
improve future strategies. Depending on the feedback &
decisions.
insights gained from the churn model, adjustments and
Analysing credit risk: Credit risk analysis across various
refinements can be made to the business plan to optimize
regions and industries is crucial. This information aids
the approach further. This creates a positive cycle of
the Bank in effectively managing its loan portfolio and
constant improvement.
making well-informed lending decisions.
Robinhood Recap: An Example of a Exploring customer behaviour: One way for the Bank
to gain insights into customer behaviour is by analysing
Successful Data Story their account activity, including transaction frequency
Robinhood Financial is an online brokerage service enabling and type. This data can enable the Bank to identify
investors to trade stocks and securities without paying patterns and trends, which can then be used to create
commissions. In late 2020, the company launched a unique targeted marketing campaigns.
personalized experience for its users to revisit their investing
Mapping branch locations: To assist customers in
journey, complete with their most significant trades, key
locating nearby branches and provide insight into the
investing moments, and other market milestones. services offered, the Bank can implement a feature that
displays the locations of its branches throughout the
This unique feature has helped users understand their country.
activity and encouraged them to look closely at their
investment strategies. The data-driven customer experience
Conclusion
highlights the users' earned interest, dividends, and trade
The use of data-driven storytelling has the power to
returns and reinforces moments of explicit value.
significantly transform how we consume and analyse data,
Additionally, it promotes desired user behaviours. Robinhood
and revolutionize the field of Analytics. Interpreting and
is eager to drive brand awareness and new client acquisition
explaining data makes Business Intelligence accessible to all
through referrals and app adoption, ensuring brand loyalty.
users, not just those with data analysis training. In the future,
new data tools can provide data stories. Additionally,
combining data storytelling with Artificial Intelligence
predictions can lead to accurate predictions without
extensive configuration. Critical actions for the Financial
Sector are evaluating vendors with augmented user
experiences and implementing or enhancing data literacy
programs.

References:
https://www.gartner.com/
https://powerbi.microsoft.com/
https://online.hbs.edu/
https://towardsdatascience.com/
https://www.techtarget.com/

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