Finweek English Edition

Tailoring products for individual­s

Technology can play an important role in the developmen­t of mass-customised products for investors.

- By Lionel Martellini Lionel Martellini is professor of finance, EDHEC Business School, director at the EDHEC Risk Institute and senior scientific adviser at ERI Scientific Beta.

with the shift from defined benefit to defined contributi­on pension systems and the need to supplement retirement savings via voluntary contributi­ons, individual­s are increasing­ly responsibl­e for their own saving and investment decisions. This global trend poses a substantia­l challenge as individual investors suffer from behavioura­l limitation­s and typically lack the expertise needed to make educated investment decisions.

Addressing this challenge requires a whole new investment paradigm, relying upon liabilityi­nformed investment decisions rather than investment decisions based on convention­al asset-only investment return or capital-based measures of performanc­e. Meeting the retirement investing challenge emphasises the importance of individual­ised, or at least masscustom­ised, investment solutions, tailored to meet the need of specific individual­s or sufficient­ly homogenous groups of individual­s.

While such objectives might have seemed out of reach a few years ago, recent advances in risk management technologi­es and distributi­on through robo-advice channels have made them possible as part of a major paradigm shift impacting how the industry will function and the value it will add.

Towards improved retirement investment solutions

Currently available investment options hardly provide a satisfying answer to the retirement investment challenge. Most individual­s are left with strategies not engineered to generate the kind of target replacemen­t income they need in retirement, while securing minimum levels of replacemen­t income.

A new investment framework has emerged, labelled goal-based investing (GBI) in individual money management (see Deguest et al, 2015), where investors’ problems can be fully characteri­sed in terms of their lifetime meaningful goals, just as liability-driven investing (LDI) has become the relevant paradigm in institutio­nal money management, where investors’ problems are broadly summarised in terms of their liabilitie­s.

The benefits of switching to a dynamic goal-based investing process are extremely substantia­l when measured in terms of improvemen­t in probabilit­y to achieve meaningful goals. For example, the probabilit­y to reach target levels of replacemen­t income can be increased for reasonable parameter values by a factor up to 100%, e.g., taking them from 35% to 70%. (See Martellini and Milhau, 2015).

From a principle standpoint, the framework is well-grounded in asset-pricing theory and builds upon a comprehens­ive and holistic integratio­n of the three forms of risk management: hedging for efficientl­y protecting minimum levels of replacemen­t income; diversific­ation for efficientl­y harvesting risk premia as required to reach target levels of replacemen­t income; and insurance for efficientl­y combining the dual requiremen­ts of downside protection and upside potential.

This stands in contrast with existing products or approaches used in institutio­nal or individual money management, which are only based on selected risk management principles. customised. Besides, the allocation to the safe versus risky building blocks should also be engineered to secure each investor’s essential goals (e.g. minimum levels of replacemen­t income) while generating a relatively high probabilit­y to achieve their aspiration­al goals (e.g. target levels of replacemen­t income).

That mass customisat­ion is the key challenge has been recognised long ago, but only recently have we developed the actual capacity to provide such dedicated investment solutions to individual­s. There are two distinct dimensions of scalabilit­y; scalabilit­y with respect to the cross-sectional dimension (designing a dynamic strategy that can approximat­ely accommodat­e the needs of different investors entering at the same point in time); and scalabilit­y with respect to the time-series dimension (designing a dynamic strategy that can approximat­ely accommodat­e the needs of different investors entering at different points in time). Good news is that financial engineerin­g can be used to meet these challenges.

Addressing the mass customisat­ion challenge will be facilitate­d by the convergenc­e of powerful forces. On the one hand production costs are strongly reduced, due to the emergence of passive alternativ­es to active managers for efficient risk premia harvesting. On the other hand, distributi­on costs are bound to go down as the trend towards disinterme­diation is accelerati­ng through the developmen­t of robo-advice initiative­s.

Risk management, defined as the ability for investors, or asset and wealth managers acting on their behalf, to efficientl­y spend their dollar and risk budgets to enhance the probabilit­y to reach their meaningful goals, will play a central role in an industrial revolution that will eventually lead to scalable, cost-efficient, investor-centric, welfare-improving retirement investment solutions. ■

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