INSURANCE SOLUTIONS

Research & development

Overview

Moving the industry forward

We’re not just providing services to the insurance and financial industries. We are driving those industries forward into a future with innovative research providing greater predictability, more precision, and less risk. From advanced financial modelling to claims reserving calculations and biometric risks prediction, our innovation in mathematical, computational, and actuarial techniques is helping our clients succeed.

Mortality modelling

Understanding mortality is fundamental to the insurance industry. We are designing new techniques and improving traditional ones to create greater accuracy and deeper understanding of mortality drivers in an ever-changing population.

Claims reserving

Accurate claims reserving can free working capital and improve long-term solvency. We use advanced mathematical techniques to explore and improve this critical element of actuarial practice.

Capital and financial modelling

Growing regulatory and market complexity combine to challenge traditional modelling approaches. We use the latest computational technologies and statistical innovations to break through the barriers and produce stochastic economic scenarios that are not only accurate but deliver useful insights to the business.

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Innovations in research and development

Products

Milliman research and development products

Financial modeling & industrialization

Integrate

Automate and accelerate actuarial modeling and reporting with a powerful, cloud-based solution.

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Economic Scenarios Generation

Milliman Economic Scenario Generator

The Milliman Economic Scenario Generator is a cloud-native economic scenarios generator that provides advanced modelling capabilities for both risk-neutral and real-world applications. The Milliman Economic Scenario Generator delivers secured regulatory compliance as well as production efficiency through its reactive web interface and integration-ready API.

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Insight

Milliman research and development insight

White paper

Modeling financial losses from a ransomware attack using a causal approach

With ransomware attacks on the rise all over the world, regulators are keeping a close eye on the reimbursement of ransoms by insurers.

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Milliman Economic Scenario Generator

Modeling financial losses from a ransomware attack using a causal approach

Impact of COVID-19 on best estimate mortality assumptions

Reducing the number of scenarios used for stochastic ALM valuation

Cosine densities approximations: Applications to swaptions pricing

Impact of credit data for the valuation of insurance liabilities

Building a high-performance in-house life projection and ALM model: Architecture and implementation considerations in Python

An epidemiological model for silent cyber accumulation risk assessment

Modeling the impact of climate risks on mortality

Calibration accuracy of three variants of the Libor Market Model

Mortality trend prediction using machine learning

Efficient computation of Solvency Capital Requirement using Multilevel Monte Carlo Methods

The impact of carbon risk factor on equity dynamics

Estimating long-term implied volatility for the valuation of insurance liabilities

Alternative asset classes: Why and what to model, and considerations for risk management

Modeling the pandemic risk

A realistic modelling of the dynamics of equity volatility

Sensitivity analysis for model risk management

Neural network calibration of the DDSVLMM interest rates model, and application to weights calculation

Challenges in the calibration of real world models within Economic Scenarios Generators

LSMC Surgery

A review of the Solvency II equity shock

Setting discount rates under IFRS 17: Getting the job done - Paper 3: Some practical considerations for reference portfolios

EIOPA’s Market and Credit Risk Comparative Study: Key takeaways

Cloud computing and machine learning uses in the actuarial profession

Setting discount rates under IFRS 17: Getting the job done—Paper 2: Setting the approach

IFRS 17: Deriving the confidence level for the Risk Adjustment: A case study for life (re)insurers

Setting discount rates under IFRS 17: Getting the job done

My working day as reserving actuary in 2060- or not

Automatic extraction of COVID-19 epidemiological parameters using Natural Language Processing

Living forever with Solvency II: A closer look at mortality stresses

The cohort effects that never were

Pandemic risk modelling in Solvency II internal models: Example of COVID-19

Individual claim reserving models: Adding value

Reliability issues in the construction of national mortality tables for the general population: What you should know

The future of (individual) reserving

Actuarial R&D – why do it, and how?

Individual claim reserving models: parametric vs non-parametric models

Mortality data correction in the absence of monthly fertility records

COVID-19 outbreak: what can actuaries learn about mortality?

Multivariate Hawkes process for cyber insurance

Nonparametric adaptive inference of birth and death models in a large population limit

A new inference strategy for general population mortality tables

Mortality data reliability in an internal model

Individual claims reserving: a survey

Improving HMD mortality estimates with HFD fertility data

One-year reserve risk including a tail factor: closed formula and bootstrap approaches

Economic Scenario Generators: a risk management tool for insurance

Signature based validation of real world economic scenarios

Jacobi Stochastic Volatility factor for the Libor Market Model

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