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Retirement Solutions Should Harness Investment Science and Technology to Shockproof Plans


Humankind has made huge strides in technology. Big data and data analytics, artificial intelligence, machine learning and deep learning are being used in various daily applications and industries. But when it comes to retirement schemes, we appear to be stuck in the past.

The leading solution that private retirement planners have come up with is a spectrum of well-diversified risk/return investment portfolios drawn from 1950s financial technology, or at best a series of target date funds, where risk-taking follows a predefined ‘glidepath’. A recent innovation has been the enabling of the same solutions at lower cost using technology, or robo advisers. Surely we can do better.

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This article was originally published on Asia Asset Management

Prof. Ong Shien Jin is a Professor of Practice at the Asia School of Business (ASB). His research interests are in Finance & Analytics. Shien Jin’s background spans finance, tech & academia. He started his career as a Quantitative Strategist at Goldman Sachs Asset Management Fixed Income, specializing in mortgage-backed securities.

After Goldman Sachs, he joined the tech industry as Special Assistant to the CEO at, the #1 online job portal in South-East Asia. Prior to ASB, he was a Visiting Senior Research Fellow at the National University of Singapore (NUS). Shien Jin holds a Ph.D. in Computer Science from Harvard University and a Bachelor of Science in Mathematics from MIT.

He can be contacted at