How are ESG issues impacting the wealth management sector today? What has been achieved so far, what are the opportunities and threats, and what is still to be done?

It is no secret that sustainable finance is on the rise. A growing number of investors have shifted their assets into sustainable investments, and the younger generation of investors is demanding a society with a good conscience. While these pressures create certain constraints, the real added value comes from the fact that proper ESG integration simply leads to better outcomes, especially for mid-to-long-term investments. Nevertheless, taking ESG preferences and sustainability risks into account can significantly change asset allocation. Traditional mean-variance, factor-risk allocation, and total portfolio analyses rely heavily on assumptions and historical data-both of which are highly sensitive to ESG variance. Since regulatory and asset class disclosure requirements used to be very heterogeneous, many different ways of labeling financial instruments as green or sustainable evolved - less diplomatically put, this ended up being a lot of window dressing.

However, using intelligent quantitative measures such as big data analytics and artificial intelligence, enriched with deep ESG expertise, can provide a solution to the market. ESG risk assessment and quantification can uncover investment opportunities that competitors cannot see, creating additional sources of alpha for asset managers and increasing risk-adjusted returns for asset owners. Admittedly, improving technology and tools for a better client experience is a top priority for the entire industry. The goal is to provide a solution where investors can meet their individual investment preferences while achieving both a positive ESG impact and outperformance against relevant benchmarks. But whereas in the past financial regulation required financial institutions to focus primarily on the financial risk of their clients, wealth and asset managers are now being required to show increasing recognition that ESG factors - particularly climate change - are a material risk to manage. For this, both the end client and the wealth manager are shown the path to a triple benefit: an optimized risk/return portfolio, an optimized ESG and SDG portfolio, and minimized sustainable risk in the portfolio leading to medium to long-term outperformance.

As public and regulatory expectations continue to change, competitive banks are already taking advantage. According to the Global Sustainable Investment Alliances annual report, $30.7 trillion was professionally managed globally in 2018 under responsible investment strategies ranging from exclusionary screening to corporate engagement - a 34% increase in just two years.

This shift toward sustainable finance has evolved beyond socially responsible investing to include asset management and ownership. Unlike other plug-and-play software, ESG requires a careful strategy to unlock value. Only a systematic integration of ESG risks and opportunities will improve the selection process and create improved risk-adjusted returns. Bottom-up analysis must be conducted to identify positive drivers of change in a company that others in the market have not yet priced in. These results must enrich existing asset allocations to have a complete investment strategy incorporating ESG as a potential alpha factor.

What solution(s) does your company offer the market that addresses ESG issues, and how do they help wealth management firms manage their increasing obligations in this area?

swissQuant sets all efforts on anticipating and solving these pressing challenges before they impact business results negatively. As front-runners in end-to-end ESG integration, swissQuant allows wealth managers to gain a competitive advantage and benefit from holding an industry-leading position. By incorporating investor ESG preferences into the portfolio optimization process of growth and return, swissQuant re-shapes the core of wealth management by demanding the engagement of investors and encouraging them to define their contribution to the future. Alongside benefits such as greater compliance, access to behavioral data to enhance customer engagement, and faster reaction to market volatility, swissQuant’s technology is particularly useful where algorithms are powered by live data streams such as real-time equity prices. As a result, we developed and applied models to master complexity when, for example, different types of risks interact closely or influence one another due to different time horizons. One of our solutions that focuses specifically on ESG issues is our ImpaQt Wealth Management Platform.

ImpaQt is a scalable end-to-end advisory platform solution allowing wealth management advisors to give investment advice to their clients that is:

• In line with the Banks investment view
• Tailored to the clients’ individual preferences
• Compliant with regulatory criteria
• Ensuring best diversification for portfolios

With the ImpaQt Wealth Management Platform, data generation is standardized, sourcing data directly from the bank’s core system and enriching it with swissQuant’s Risk, Optimization, and ESG analytics, eliminating the need for an error-prone manual data gathering process. By integrating the bank’s investment philosophy into the ImpaQt Wealth Management Platform, individual investment advice is created at the click of a button, automatically taking into account all regulatory criteria and compliance checks and thereby generating an individualized yet scalable investment advisory process.

With the ImpaQt Wealth Management Platform, an executive can:

• Manage portfolios efficiently, consider sustainable risk and create outperformance with the preference driven portfolio optimization methodology
• Analyse and exhibit the ESG relevant factors on an individual client and preference driven level

Manage portfolios efficiently, consider sustainable risk and create outperformance with the preference driven portfolio optimization methodology • Analyse and exhibit the ESG relevant factors on an individual client and preference driven level

• Pattern recognition for strategic asset allocation
• Dynamic programming for multi-period portfolio optimization at Goal-based investing
• Big Data Analytics for the Trade Recommender Module
• Integral client-level ESG Score/SDG Analytics embedded in the ESG Portfolio Optimizer
• Artificial Intelligence-based sustainability reporting

This article was originally part of our Wealth Tech Views ESG Report. Click here to access the full report.