This news service recently awarded Finvent Software Solutions, the firm behind the Klarity Risk Platform, and we spoke to Yannis Sardis.

This news service talks to Yannis Sardis, PhD, who is a director of Finvent Software Solutions, provider of the award-winning Klarity Risk platform. The firm was recently honoured at the WealthBriefingAsia awards. 

Please tell us about your business background
Sardis: I have 24 years of experience in the global financial markets. I am an investment strategy advisor to the board of Finvent Software Solutions. This firm, which has offices in Greece, the UK and Cyprus, offers multi-asset portfolio and risk management analytics for the buy-side investment industry worldwide. I have been a partner at a Swiss investment advisory firm, which acted as an outsourced chief investment officer for family offices and boutique institutions, and a partner at an investment management firm in London, which advised and managed capital via a selection of multi-asset quantitative strategies. I was a director and a member of the founding team of Salomon Smith Barney’s Wealth Management Group (Citigroup Capital Markets) in Europe, which focused on the provision of multi-asset investment and trading solutions to international high net worth private clients and institutions. I had the privilege to start my career path as a vice president at the fixed income arbitrage group of Salomon Brothers in London.

Please outline what Finvent Software Solutions aims to do and what its core target market is.
Finvent Software Solutions is a trusted provider of financial software applications and custom engineering services for the buy-side investment management sector. Its clients include private wealth institutions, asset and hedge fund managers, family offices, banks and foundations, in Europe, Asia and the US. Its award-winning KlarityRisk platform specialises in advanced investment risk analytics, customised stress-testing portfolio simulation, multi-level risk limits management and fixed income performance attribution reporting, providing its clients with a configurable risk system which facilitates the design, back-testing and validation of their proprietary investment strategies, across traditional and alternative asset classes.

Finvent is also the sole worldwide distributor of SS&C Advent, the leading provider of portfolio management and accounting solutions and services, and its products are integrated with those of SS&C Advent. Finvent is a partner of FactSet, the integrated data aggregator platform.

How long have you been working with Finvent and KlarityRisk and on which focus areas?
I have had the opportunity to work with the Finvent team in a number of investment risk related projects since 2017, which aimed to adapt the firm’s software solutions to the actual needs of the modern wealth manager. The focus of these projects ranged from strategic product positioning and segment-focused marketing to software solutions re-packaging and investment content creation, mainly for the firm’s multi-award-winning risk management platform (KlarityRisk) which is used by the mid-tier asset management segment for the design and validation of investment strategies.

Finvent’s expertise in the investment software engineering space positions the firm naturally to be a knowledgeable and resourceful partner who provides solutions to business either via its off-the-shelf product palette or via project customisation mandates.

A big issue for investors and advisors is how to maintain poise during times of uncertainty and when volatility appears to be increasing. What can technology do to assist?
Extreme market events are evidently more frequent than commonly thought of and their effects on portfolio performance should be diligently risk-adjusted to create a range of portfolio rebalancing scenarios for a wide spectrum of unexpected price shocks.

Investors cannot consistently predict imminent market reckonings and re-allocate capital into non-affected assets in advance. The defining characteristics of future change are the existence of wild volatility and the impossibility of predicting it. The mission of those involved in asset management is not to predict the future but to manage positions of high conviction within a disciplined risk framework.

Investors should continually assess their portfolios’ vulnerability to future price fluctuations, by simulating the behaviour and loss-tolerance of multi-asset-class portfolios for the “occasional” increase in stock price volatility. Such a process can be achieved via the use of a risk management software engine which allows investors and advisors to apply pre-determined investment principles and avoid decision-making driven solely by human emotions and intuition.

How can technology be used to guard against some of the behavioural biases and habits that investors are prone to, such as red-flagging times when markets are oversold/overbought, concentration risk, undue reliance on single sources of information, dangers of over-confidence, need to avoid undue “noise”?
Behavioural economics indicate that investors not only often appear not to be rational, but they are most often predictably irrational! We have all experienced the ‘Confirmatory Bias’, the process of looking for the evidence that agrees with our existing perceptions, or the ‘Loss Aversion’ bias, the fact that investors tend to dislike losses much more than they appreciate gains. Not only do we often fail to look at alternative views but we are ‘coded’ to distort new data-based evidence to suit our preferences.

Although investors cannot always encapsulate the latest scientific advances into their investment management practices, they can certainly use an advanced risk management system to establish a disciplined process that will govern the way in which they make decisions, thus protect their portfolios and firms from their own biases.

We cannot predict the size and timing of the next market downturn or the next crisis but we can mitigate the various portfolio risks via educated and open-minded risk-adjusted considerations. Investors should embrace a systematic investment approach which can allow them to ring-fence their portfolios from downside risks whilst they can partly be participating in the market upside.

The way people think about risk is changing because of the COVID-19 pandemic. In what ways are you seeing clients’ views of risk changing, such as time horizons and goals for achieving wealth?
Our information-thirsty and quick-results-oriented world assigns greater value to a popular conviction of future forecasts than to the intrinsic knowledge acquired by realised adverse events (such as a recent or a prolonged crisis). In the longer term, this fact creates collective herding behaviour and cognitive fallacies.

In finance, a decision-maker continually faces various risks that can drastically and speedily affect the value of a portfolio’s holdings. Although investors often display short-term reactive behaviour, most are not proactive in the long term in building a systematic decision-making process, applying a full set of risk methodologies that could identify whether a portfolio is getting closer to, or diverging from, a probability distribution of returns from normality.

As recent markets displayed, a robust risk management framework demands the implementation of scenario simulations where the distribution is extremely skewed towards tail events, situations that happen rarely. Such shocks could be caused by various macro-economic or idiosyncratic events, which can consequently spread widely to previously thought of as uncorrelated choices of assets. Vivid memories of crises that resulted in large losses of invested capital include the Black Monday of 1987, the Asian Crisis of 1997, the Russia Devaluation of 1998, the Dot-Com Crash of 2001, the Global Financial Crisis of 2008 and the (so far developing) Global COVID-19 Health Crisis.

We have discussed how no single measure/number can give an investor confidence that he/she is on the right path; this must be seen as part of a bigger picture and understanding of cross-asset correlations. Could you please elaborate? Are there examples of mistakes people have made by relying on one metric?
Indeed, the daily undertaking of evaluating a portfolio’s risk exposure to normal or Black Swan market conditions cannot be adequately covered by a single risk number and its variations. A first line of assessment can utilise the notion of risk built around the prediction of maximum potential portfolio loss over a certain period of time for a certain confidence level (aka Value at Risk).

However, to take a proper X-ray of a portfolio’s risk exposure, one should produce a risk decomposition analysis for an exhaustive list of categorisations such as asset class, sector, risk country, reference currency, issuer credit rating and underlying security holdings, thus effectively identifying any imbalances between individual position weights and their associated risk weightings.

In addition, one should run portfolio stress-test simulations to assess a portfolio’s tolerance to adverse market actions, via both simulations based on past historical crises and the adjustment of such “worst-case” scenarios to modern frameworks. This will allow user-defined changes to the portfolio’s driving risk factors.

Importantly, when investors or managers make changes to a portfolio risk factor, the risk engine should calculate and utilise the correlations of the reference asset class to the other portfolio assets, so that the final risk output represents a holistic stress effect of the portfolio to all factor changes.

Examples of market participants not applying comprehensive sets of risk factors to their portfolios are too many to list, mostly because the widely used performance-only-based views do not provide investors with an understanding of their portfolios’ vulnerability to future volatility fluctuations.

The necessity of using a holistic approach to risk assessment is amplified in our modern world with the growing number of diversified investment vehicles, fund types and less liquid alternative asset pools such as derivatives, private equity, private debt, real estate and tailored structured products. The ability to implement a multi-faceted portfolio risk analysis will enhance a portfolio manager’s confidence of the capital adequacy that an investment strategy or a firm need to retain in order to cover significant losses in detrimental market conditions.

Are the lessons of 2008 and other financial crunches sufficiently absorbed, or are you noticing repeat patterns? How do investors break out of bad habits?
The prolonged monetary easing employed by the world’s central banks and the government bailouts keep decreasing the sharpness of investors’ ‘reflexes’. As mentioned above, humans seem to be ‘hard-coded’ in a way that they would rather distort new evidence to suit their preferences rather than identify and painstakingly mitigate the risks that are embedded in their asset allocations.

The urgency that the average investor feels about not missing out a market rally, leads people to short-sightedness and long-term lapse of memory. However, understanding that these are human traits, we are not suggesting that people should always be conservative and risk-averse. Accepting that a large portion of portfolio losses are due to excessive leverage, trade entry at high asset valuations and over-concentration of positions, a robust risk management framework should be in place to assist investors identify the risk factors that underlie a multi-asset portfolio and stress-test the portfolio’s diversifying qualities.

Admittedly, it puzzles us that even professional investors often have no proper risk mitigation plan in place, as such cases resemble a driver taking his/her car for a ride without fully functional brakes.

What is your view of how private banks, wealth managers and family offices view and understand risks these days? Is the industry getting better and more professional, or are there remaining gaps and challenges?
To remain competitive, private banks, wealth managers and family offices try to modernize aspects of their investment operations. However, we feel that a disproportionate amount of human resources and working capital has been allocated to middle and back-office operations (producing a posteriori performance reporting) rather than to front-office decision-support processes (producing a priori risk-adjusted out-performance).

We understand that this emanates mainly from the increasing “real-time” client reporting demands that institutions face in a fast-evolving world. However, a primary focus of an investment operation should be to equip its front office decision-makers (and thus revenue generators) with the most complete and intelligent systems that will assist them to produce consistent risk-adjusted returns over longer time periods; this effort can be subsequently complemented by the production of performance and risk exposure reports, across all asset classes and customer types of a firm.

A multi-asset class, multi-currency risk management solution should provide a selection of metrics which identify and validate how much risk position one should take to realise a targeted portfolio performance level. Such a solution should be designed for:

-- The portfolio manager who wishes to be constantly aware of how extreme market movements and volatility spikes can impact the valuation of the firm’s investment strategies; 
-- The relationship manager who needs to give clients a holistic view of the portfolio management’s outcome, providing risk-adjusted performance and valuation figures; and 
-- The risk officer who wants to assess the market risk that the firm is exposed to, through predictive ex-ante risk metrics and advanced stress-testing scenario analytics.

So much technology spending in recent years has been on compliance and areas such as suitability. How much of this has benefited the end-client, and do you have concerns that so much money has gone into compliance rather than business growth?
A cynic could argue that despite the plethora of compliance rules that have flooded the market and the bureaucracy that has been created as a consequence (one can ask any private banker or relationship manager who spends immeasurable time in non-performance-producing activities), the end-clients are not better off in terms of the portfolio performance that is delivered to them.

However, it is a fact that these rules have sketched a framework within which clients can be more confident that the choice of asset and instruments composing their portfolios adhere with their actual investment preferences. In particular, we believe that smart client onboarding processes, where investment objectives, risk tolerance and instrument selection topics are properly addressed, is a vital (first) step towards a comprehensive, cost-effective and successful investment process.

On an enterprise-wide level, such a process paired with an asset performance and risk exposure assessment can benefit:

-- The compliance officer who wants to ensure that the group’s trading activity conforms with the pre-determined investment policy decisions and emerging regulatory requirements; and
-- The firm that wants to decompose its client portfolios or internally managed funds and gain visibility to the specific market segments which expose its portfolios to the biggest risks.

We believe that innovation should lead and regulation should harmoniously follow. 

Fast-forward five or ten years, where would you like to see the industry in terms of how people use technology around investment?
We would like to see adaptive investment risk technology frameworks that allow predictive models to factor in a client’s specific circumstances, for instance by taking into account an individual’s financial and non-financial risk attitude. This would greatly contribute to understanding the differences between people’s perceived and realised risk tolerance. We believe that behavioral sciences have much to teach us in this direction by utilising cognitive technologies applied to investment decision-making.

Our industry would also benefit by new ways of visualising data as well as by "deciphering" analytics in alternative and more conceptual ways. Complex and non-intuitive visualisation of risk most often prevents rational decision-making, especially when big data sets are involved.

Although we should always be open-minded and embrace any modern technologies that are projected to improve our decision-making (such as Machine Learning, Artificial Intelligence and Blockchain), we should be cautious of over-relying on overhyped technologies before they consistently start producing the results they promise. We should also closely monitor, and be equipped to mitigate, any unintended ramifications of mistaken predictions that new technologies may introduce.

Technology advancement should be the means to our selected end purposes, not our sole focus.