Knowledge Base Articles

Building a Cutting Edge Digital Life Insurer via OutRank® - the Financial Simulation Engine

HAYAH Insurance recently partnered with Kidbrooke® to build engaging, self-service investment journeys with OutRank®, the financial simulation engine driving HAYAH’s new goals-based financial planning experiences. HAYAH Insurance, established in 2008 and headquartered in Abu Dhabi, is the UAE’s newest and most exciting insurance company, specialising in life and medical insurance and savings products. Here HAYAH Insurance talk about the exciting partnership they have embarked upon with Kidbrooke.

Skandia case study III: Using OutRank to Enhance their Investment Customer Journeys

Skandia, the Swedish life insurance company, has ramped up its initiatives in using technology to improve the overall experience of its customers. The goal is simple – developing a digital space to offer touchpoints relevant and meaningful enough to drive engagement across all of Skandia’s channels.

Personal Accident Insurance: Would My Savings Suffice?

Today’s case study examines a real-life experience of a Swedish family who struggled to receive adequate help from the local wealth management service providers.

Skandia Case Study II: Building Channel-Agnostic Wealth Experiences

Skandia strives to build communication channels in a digital space that would match the physical experiences in engagement levels and even improve the service quality in a way that has not been achievable before.

Beyond Modern Portfolio Theory: Expected Utility Optimisation

The modern wealth management industry still relies on the 50-year-old approaches to portfolio management, widely popularized by Markowitz's Modern Portfolio Theory (1952). Despite heavy criticism within the academic circles, the alternative methods remain undeservingly overlooked in practice. In the context of the modern leap for hyper-customization, we look into one of the alternatives to Modern Portfolio Theory in greater detail - the Utility-based approach.

Part I - Portfolio Construction - Parameter & Model Uncertainty

There is a number of challenges associated with portfolio construction based on historical data. This three-part article series explores some of the most common issues attributed to the model-based portfolio optimization: the sensitivity to changes in data, large variations in portfolio weights and the bad out-of-sample performance.

Hierarchical Clustering: Prediction of Systematic Underperformance

As machine learning methods grow in use and popularity, we explore yet another dimension of wealth management that our experts consider fit for applying such frameworks. In this article, we deploy hierarchical clustering to find more consistent ways of predicting the relative future performance of funds.

Part III: Asset and Liability Management Using LSMC - Allocation Optimisation

In the third and concluding article in the ALM using LMSC series, we focus on analyzing the optimal asset allocations in the context of changing asset classes as well as finding the optimal allocation by maximizing the risk-adjusted net asset value. The estimates based on the LSMC method are then compared to the estimates obtained from the full nested Monte Carlo method.

Blog Articles

Exploring ALM in Life Insurance: Strategy, Risks, and Innovations

In this interview, Hans Sterte, a seasoned economist, and Senior Partner at House of Reach, shares his rich insights from a career spanning over three decades in the realms of economics, asset management, and strategic investment. Tracing his journey from government institutions to leadership roles in major Swedish pension funds, Hans delves into the intricacies of Asset and Liability Management (ALM) within life insurance companies, highlighting its evolution and current challenges.

Bridging Gaps in Consumer Duty

The purpose of the UK’s latest regulatory update goes beyond additional reporting and addresses the value created by wealth management and insurance businesses. It aims to set a higher standard of care and deliver better consumer outcomes throughout the customer journey. The overarching principles set out to change how products and services are evaluated, priced, explained and supported, and it should transform the relationships within wealth management value chains.

Enhance Mutual Fund Grouping Using Machine Learning

The methods used to recommend mutual funds to customers vary greatly between companies. Often the recommendation techniques used rely on using metadata of the mutual funds, such as region, category, or investment objective. By grouping using these properties investors are given an overview of funds with similar classifications and can select funds from the groups they are interested in. And while grouping mutual funds in this way may provide investors with a convenient way to explore funds that align with their preferences and investment strategy, this method of recommendation has some potential limitations and risks.

Key Trends in Wealth Management Q2 - 2023

As we tread midway to 2023 and discover what it may have in store for wealth management organizations, you can expect to see this focus area remain with most wealth managers giving their channels and CX solutions a much-needed overhaul. Consumer expectations are going to keep getting increasingly digital oriented.