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The Role of Data Integration in Wealth Management

Big data in asset management is transforming the industry. As technology processes data more quickly than ever before, it opens up opportunities for advisors to uncover insights and client solutions that perhaps weren’t always obvious without the aid of wealth management data analytics.

Farm Bureau taps into this invaluable resource through its partnership with Royal Bank of Canada (RBC), offering advisors access to asset wealth management analytics via RBC Black, MoneyGuidePro, RBC Gateway and more. 

What Are the Types of Investment Management Data Analytics?

There are four types of investment management data analytics. They work in tandem to capture and analyze real-time information to help wealth management advisors make informed decisions for their clients. 

  • Descriptive analytics: This wealth management data strategy answers the question of what happened by gathering historical data of how funds, investments and portfolios have performed in the past.  
  • Diagnostic analytics: This analytics technique answers the question of why things happened, building on data from descriptive analytics to investigate the cause of certain outcomes.
  • Predictive analytics: Predictive analytics in investment management answer the question of what will happen, utilizing data from descriptive and diagnostic analytics to predict the future performance of funds, investments and portfolios.  
  • Prescriptive analytics: This technique answers the question of what should be done next. It collates the information gleaned from descriptive, diagnostic and predictive analytics to recommend future, solution-oriented actions.

How Does Data Integration Help Wealth Management Advisors?

Advanced algorithms are always learning and adapting from constantly changing data. Machine learning, for example, uses computers to read and analyze huge amounts of text from many different sources.

The data extracted from machine learning can include any of the following:

  • Topic modeling, which is the ability to summarize extensive amounts of text into theme-based topics easily understood by humans.
  • Intercompany momentum, which is the ability to pick up on subtle connections between companies that might go unnoticed by the human mind in order to analyze how the performance of one company affects another.
  • Sentiment analysis, which is the ability to determine tone — positive or negative — in vast amounts of text in research, news articles and reports.

Traditional methods of aggregating data do not offer insights like this in a scalable fashion. When advisors have access to sophisticated the right tools, they are well positioned to discover potential opportunities for their clients. The important thing to note, though, is that although data analytics might form the basis for active wealth management, active management is still that: active. An advisor’s experience, market knowledge and human judgment all play key roles in how a client’s assets are ultimately invested. 

How Does Data Integration Help the Client?

Wealth management data analytics allow advisors to anticipate not only the behaviors of their clients, but also their needs. Advisors can leverage this information into a tailored strategy that brings long-term benefits to a client’s financial future. And because asset management analytics create a highly integrated, dynamic workspace for advisors, it simplifies tasks and saves crucial time so advisors have more hours to put toward that all-important factor: relationship building.

Equipped for Success

Farm Bureau stands out because we provide our team with the support and technology to succeed. To get started, contact us.