IFRS 17 researcher; Economic Scenario Generator software designer; Least Squares Monte Carlo proxy modeling technique pioneer

Steven Morrison and his team of actuaries and quantitative analysts generate modeling techniques and tools for insurers. Based on his research and advisory work on developing modeling methodology, insurers can project their financial statements, determine risk and capital assessment, and make sound decisions. Currently, Steven’s focus on IFRS 17 specifically helps insurers understand and communicate profits.

The University of Edinburgh
MSc, Financial Mathematics
University of Glasgow
PhD, Theoretical Physics
Moody's Analytics | Economic Scenarios

Economic Scenarios: Moody's Analytics provides internally and globally consistent economic, regulatory, and custom scenarios.

International Financial Reporting Standard (IFRS) 17: Insurance Contracts

International Financial Reporting Standard (IFRS) 17 Insurance Contracts: The Moody’s Analytics suite of software solutions, models, content, and services helps support the new requirements of IFRS 17 Insurance Contracts.

Moody's Analytics | Regulatory Capital

Regulatory Capital : Moody’s Analytics insurance regulatory capital solutions help insurers comply with Solvency II and other similar regulatory regimes.


Econometric Modeling: Fully transparent econometric and statistical models to assess performance of geographies, financials and various asset classes.

Liability Valuation: Process of valuing a company's liabilities for financial reporting purposes.

Economic Risk Assessment: Quantitative economic assessment to help you understand the impact of forward-looking changes on the performance of your business and portfolios.

Published Work

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

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

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

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

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

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