How Advanced Big Data Analytics is Impacting Wealth Management
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How Advanced Big Data Analytics is Impacting Wealth Management

By Banking CIO Outlook | Friday, November 22, 2019

Investors and advisors have understood the essence of data analytics in wealth management and are steadily investing in delivering advanced data analytics solutions. 

FREMONT, CA: The sector of wealth management is rapidly transforming. Institutions are becoming increasingly concerned with their decision-making and implementing technology to support them. To achieve transparency to investment decision-making and risk management, data analytics is a valuable application. Innovations, such as machine learning (ML) and big data, support advanced analytics methods. Technologies also influence the analysis and interpretation of data-driven investment patterns. According to a survey, over the past three years, 86 percent of respondents have invested more and more on data and analytics. Here are some fields where data and analytics will shape the critical aspects of wealth management.

Data Analytics in Automation Phase

Wealth management companies are moving towards automated solutions that enable them to make productive use of their human resources. For example, companies use technologies such as natural language processing (NLP) and other methods to analyze voice and text data to increase the efficiency of basic functions. However, data analytics can make a significant contribution to this cause, as it is possible to use the historical unstructured data sets to eliminate any potential roadblocks during the automation phase.

Integrated Data Analytics 

To meet decision-making challenges, an integrated data analytics solution that derives insights from structured and unstructured data from across databases can be applied. The deployment must be a specific requirement for a consultant or a particular firm, covering all the essential business needs.

Data Analytics in Risk Management

Wealth management companies are working relentlessly to broaden their online footprints. However, the risk profiles change with an increased digital footprint and make the company vulnerable to new risk zones. To track and combat emerging risk areas, data analytics can be used effectively. For example, Robotic Process Automation (RPA) and internal audit checks and balances can be used to achieve compliance.

Therefore, data analytics provides wealth management companies with a new set of opportunities to tackle the rising complexities and vulnerabilities in the financial sector. An initial investment in data analytics solutions will provide the wealth managers and firms with both immediate and long-term returns.

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