[January 02, 2018] |
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Big Data for Wealth Management - A Practical Guide for Successful Implementation - Research and Markets
The "Big
Data for Wealth Management - A Practical Guide for Successful
Implementation" report has been added to Research and
Markets' offering.
In recent years, financial providers have looked for ways to leverage
the power of Big Data by implementing new digital ecosystems intended to
take advantage of increased data volume. Unfortunately, many of these
projects have produced lackluster returns, if not outright failure.
This report analyzes why Big Data projects in the financial services
sector are often less successful than intended, and what wealth managers
can do to ensure that their Big Data initiatives stand a better chance
of success. The report profiles a group of 30 vendors who cater to a
range of Big Data needs of wealth managers and presents five case
studies and learning points on how the main Big Data needs are addressed
in different industries.
In addition the report identifies how the success and ROI of Big Data
solutions can be measured and provides a set of practical tools for
wealth managers who are looking to integrate a Big Data solution into
their existing digital ecosystem using a needs-based approach. The
report is based on personal interviews with leading vendors for Big Data
services in the financial services sector and in-depth research on their
offerings.
Wealth managers, banks, IT vendors and consultants will find
answers to the following questions:
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What are the characteristics of common data types of relevance to
wealth managers?
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Benefits of descriptive, predictive, and prescriptive analytics for
wealth managers?
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How to measure success and return of investment of Big Data projects?
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How to increase the retention and satisfaction of existing clients
with Big Data?
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How Big Data can support the acquisition of potential clients and ease
onboarding?
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How Big Data can help adisors function better and more efficiently?
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How to use Big Data for regulation, compliance, and risk detection?
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How does a Big Data scorecard and pre-planning checklist look like?
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How to map a needs-based Big Data strategy?
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Which are the five main needs that Big Data solutions can fulfill for
the wealth management sector?
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How is Big Data implemented successfully in other industries?
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Can a failed Big Data project be rescued? How?
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Which are the leading vendors for Big Data solutions in the financial
services sector?
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What do the leading vendors for Big Data solutions offer wealth
managers and what are the strength and weaknesses of their solutions?
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What questions should wealth managers ask vendors in selecting the
right solution for their needs?
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What are the most important actions wealth managers should take to get
most out of their Big Data plans?
Main Content:
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Status quo and trends in the use of Big Data by wealth managers
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Drivers for Big Data in wealth management and reasons for success or
failure
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The significance of Big Data for wealth managers
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Increasing the client satisfaction and acquisition through Big Data
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Supporting advisors and compliance through Big Data projects
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Five case studies showcasing how Big Data projects have been
implemented properly in various industries
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Profiles of 30 vendors who cater to a range of Big Data needs of
wealth manager
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Choosing the right vendor for the implementation of Big Data projects
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Strategic and practical actions for implementing successful Big Data
projects
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A vendor suitability index to help choose which vendor best fits to
which needs
The report includes more than 20 visuals including graphs, screenshots
and charts and comes with four additional sets:
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Stats Premier Set: Overview of the basic statistical
concepts at the core of Big Data in a way that is accessible and
helpful for wealth managers
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Key Insights Deck: an easy-to-understand 7-slide
presentation that summarizes key findings for quick sharing.
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Vendor Data Appendix Set: An excel dataset with
information on the 30 profiled vendor solutions including whether
there is AI/Machine Learning, Topic Specific External Data such as
social media data is included, whether the solution allows for
structured and unstructured data, and the integration approach.
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Big Data Scorecard Set: An interactive Excel Big Data
Scorecard that automatically produces a sample Big Data Scorecard
based on your individual input.
Companies Mentioned
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Aim Software
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Automated Insights
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Bmc Software
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Byallaccounts/Morningstar
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Cisco (News - Alert) Data Virtualization Platform
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Contix
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Envestnet/Yodlee
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Ernst & Young
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Factset
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Hedgespa
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Ibm Client Insights Solution
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Icapital Network
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Kensho
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Lucena Research
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Rage Frameworks
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Sigfig
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Smartlogic
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Wealthtechs
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Xignite (News - Alert)
For more information about this report visit https://www.researchandmarkets.com/research/hh2lm6/big_data_for?w=4
View source version on businesswire.com: http://www.businesswire.com/news/home/20180102005318/en/
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