The Value of Personalized Guidance
We explore if providing personalized guidance around optimal portfolio risk levels and spending amounts can improve expected retirement outcomes.
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David Blanchett, PhD, CFA, CFP®, is a Managing Director, Portfolio Manager and Head of Retirement Research for PGIM DC Solutions. In this role, he develops solutions to help improve retirement outcomes for investors, with a specific focus on defined contribution plans. He is also responsible for portfolio management across all PGIM RetireWell™ solutions, including the PGIM Target Date funds and Retirement Spending Portfolios. Prior to joining PGIM, David was the Head of Retirement Research for Morningstar Investment Management LLC. He is currently an adjunct professor of wealth management at The American College of Financial Services and a Research Fellow for the Alliance for Lifetime Income. He was formerly a member of the executive committee for the Defined Contribution Institutional Investment Association (DCIIA) and the ERISA Advisory Council (2018-2020).
David has published over 100 papers in a variety of industry and academic journals. His research has received awards from the Academy of Financial Services, the CFP Board, the Financial Analysts Journal, the Financial Planning Association, the International Centre for Pension Management, the Journal of Financial Planning, and the Retirement Management Journal. In 2021, ThinkAdvisor included him in the IA25 for "pushing the industry forward.” David earned a BS in finance and economics from the University of Kentucky, an MS in financial services from The American College of Financial Services, an MBA from The University of Chicago Booth School of Business, and a PhD in personal financial planning from Texas Tech University.
We explore if providing personalized guidance around optimal portfolio risk levels and spending amounts can improve expected retirement outcomes.
Our analysis suggests plan sponsors should actively consider revisiting the funds available to participants and adjusting the options accordingly.
We explore asset class coverage gaps in DC core menus and quantify the portfolio implications associated with these gaps.