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Dr. Steven Morrison is a senior director in Moody’s Analytics insurance research group. Steven joined Barrie & Hibbert in 2001 and played a leading role in the design and development of B&H's Economic Scenario Generator software. His recent research and advisory work has focused on applications of the Least Squares Monte Carlo (LSMC) proxy modeling technique to multi-period problems, in particular capital projection and projection of dynamic hedge programs in order to assess hedge effectiveness. He pioneered the use of LSMC as a tool for projection of insurance liability values and measurement of economic capital, publishing in industry journals on this topic. He has an MSc in financial mathematics and a PhD in theoretical physics.

Related Insights
Article

Profit Emergence under IFRS 17 - VFA

Steven Morrison’s second whitepaper, Profit Emergence under IFRS 17, turns its attention to the Variable Fee Approach (VFA). Explore his practical insights on financial risk and its impact on contracts with participation features.

November 2018 WebPage Dr. Steven Morrison
Whitepaper

Fast Projection of Reserve and Capital Requirements with Proxy Functions

An emerging business requirement for North American insurers is the ability to project forward stochastic reserve and capital requirements under various planning scenarios to a specific future date. In this paper we consider applying proxy functions to this task, using function fitting techniques described in our previous research paper Fitting Proxy Functions for Conditional Tail Expectation: Comparison of Methods.

October 2018 Pdf Aubrey Clayton, Dr. Steven Morrison
Whitepaper

Profit Emergence under IFRS 17

The paper discussed the importance of implementing a modelling framework to project IFRS 17 financial statements over time and under different scenarios

September 2018 Pdf Dr. Steven Morrison
Article

Profit Emergence under IFRS 17

The ability to project financial statements to understand their sensitivity to market risks, insurance risks, and methodology decisions is critical for an effective IFRS 17 implementation.

September 2018 WebPage Dr. Steven Morrison
Whitepaper

Fitting Proxy Functions for Conditional Tail Expectation: Comparison of Methods

This paper details alternative methods for fitting proxy functions to CTE, employing quantile regression in combination with OLS among other techniques. We compare methods according to quality of fit for an example portfolio of variable annuities.

March 2018 Pdf Aubrey Clayton, Dr. Steven Morrison
Whitepaper

Solvency In Sight - New Tools for Understanding the Impact of Investment Decisions on Capital

In this paper, we have considered the use of proxy models as a way of overcoming some of the operational and computational challenges associated with measuring future solvency under different market conditions and ALM assumptions.

October 2017 Pdf Dr. Steven Morrison
Whitepaper

A Primer on Model Efficiency Techniques for Valuation of Large Life Insurance Portfolios

This paper provides an introduction to various techniques for efficient calculation of the market-consistent value of a portfolio of insurance policies. Two standard approaches to portfolio valuation are considered: (1) Use of different scenarios through different policies; (2) Portfolio compression through the use of model points. Additionally, the use of proxy functions is introduced as a novel approach to valuation of individual policies.

April 2017 Pdf Dr. Steven Morrison
Whitepaper

Proxy Methods for Run-off CTE Capital Projection: A Life Insurance Case Study

In this paper, we show a practical application to forecasting capital requirements for real portfolios of participating whole life and annuity business, carried out in a joint research project between Moody's Analytics and New York Life Insurance Company.

October 2016 Pdf Dr. Steven Morrison, Aubrey Clayton
Whitepaper

Proxy Methods for Hedge Projection: Two Variable Annuity Case Studies

The challenge of projecting dynamic hedge portfolios for blocks of Variable Annuities (VA) with complex guarantees has proven to be extremely computationally demanding but also essential for obtaining hedging credit in reserves or capital calculations. Our previous research has argued in favor of proxy function methods such as Least Squares Monte Carlo as alternatives to full nested stochastic calculations, and we have demonstrated the successful application of these methods for hedging in simple option examples including path-dependent options. This paper extends previous work by considering actual VA products with guarantees of the kind offered by insurers in North America and Europe.

May 2016 Pdf Dr. Steven Morrison, Aubrey Clayton
Whitepaper

Quantitative Insurance Research - The unintended consequences of scenario post-processing in the valuation of insurance liabilities

In this paper we explore the use of scenario re-weighting as a method for post-processing scenario sets to reflect calibration targets without having to recalibrate the model. While post-processing techniques can be quite flexible in their ability to match targets, they may result in unintended changes to distributional assumptions that are not included in the set of calibration targets. Using simple examples, we demonstrate how a scenario set's ability to match a set of vanilla asset prices does not uniquely define the resulting prices of more exotic liabilities (or assets).

September 2015 Pdf Dr. Steven Morrison
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