Authors :
Yashovardhan Saraswat
Volume/Issue :
Volume 8 - 2023, Issue 5 - May
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/mukdyd6w
DOI :
https://doi.org/10.5281/zenodo.8072789
Abstract :
Organisations across the world are
increasingly using Big Data Analytics for various
activities and benefits. Although the benefits of data
analytics may not be clearly visible inthe day-to-day life
of a business, the use of big data analytics techniques and
methods has a clear positive impact on the top and
bottom lines of the organizations. This study evaluates
factors in a customized methodology used by a mid-sized
asset and wealth management (AWM) firm that intends
to increase the benefits of its offerings by deploying Data
Analytics techniques. Evaluating the organizations in the
financial stream includes many aspects such as
Governance associated with Big Data Analytics in any
firm, distinctions in technology like hardware and
software of the product, etc.During the course of this
study, many challenges were encountered in terms of
data collection, validation, necessary approvals etc.
However, the results came in line with the said
hypothesis under consideration.
Prior to the advent of Big Data, Artificial
Intelligence (AI), and Augmented Analytics,
AWMsrelied on manual data acquisition and analysis.
All the processes from client acquisition, to
understanding client metrics based on demographics and
net worth were done on the basis of limited data
availability and complete human efforts. Today, Big
Data Analytics and AI, have democratized the way
AWMs operate. AWMs can nowmicro-segment their
prospects based on a wider range of data sources like
social media, news stories, and other public data sources.
Additionally, the service-based offerings have been
productized to meet the needs of a variety of customers
with diverse risk appetites in the form of model
portfolios. This study throws light on similar factors and
more.
The findings of the paper will benefit beginners
trying to understand the application of Big Data
Analytics in the financial sector, especially its
deployment in the Asset and Wealth Management
stream of finance and its applications thereof.
Keywords :
Big Data Analytics, AWM, Finance, Portfolio, Returns, Investment, Investors.
Organisations across the world are
increasingly using Big Data Analytics for various
activities and benefits. Although the benefits of data
analytics may not be clearly visible inthe day-to-day life
of a business, the use of big data analytics techniques and
methods has a clear positive impact on the top and
bottom lines of the organizations. This study evaluates
factors in a customized methodology used by a mid-sized
asset and wealth management (AWM) firm that intends
to increase the benefits of its offerings by deploying Data
Analytics techniques. Evaluating the organizations in the
financial stream includes many aspects such as
Governance associated with Big Data Analytics in any
firm, distinctions in technology like hardware and
software of the product, etc.During the course of this
study, many challenges were encountered in terms of
data collection, validation, necessary approvals etc.
However, the results came in line with the said
hypothesis under consideration.
Prior to the advent of Big Data, Artificial
Intelligence (AI), and Augmented Analytics,
AWMsrelied on manual data acquisition and analysis.
All the processes from client acquisition, to
understanding client metrics based on demographics and
net worth were done on the basis of limited data
availability and complete human efforts. Today, Big
Data Analytics and AI, have democratized the way
AWMs operate. AWMs can nowmicro-segment their
prospects based on a wider range of data sources like
social media, news stories, and other public data sources.
Additionally, the service-based offerings have been
productized to meet the needs of a variety of customers
with diverse risk appetites in the form of model
portfolios. This study throws light on similar factors and
more.
The findings of the paper will benefit beginners
trying to understand the application of Big Data
Analytics in the financial sector, especially its
deployment in the Asset and Wealth Management
stream of finance and its applications thereof.
Keywords :
Big Data Analytics, AWM, Finance, Portfolio, Returns, Investment, Investors.
