Publication Date: 2023/06/22
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.
DOI: https://doi.org/10.5281/zenodo.8072789
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23MAY19821.pdf
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