MAIA Technology’s Mark Veevers explains how the evolution of the asset management industry is leading to a ‘Quantamental approach’
Asset management is evolving. Bottom-up discretionary managers, which traditionally selected investments based on qualitative inputs, are increasingly employing quantitative methods involving larger and more sophisticated datasets to inform their decision-making.
While traditional quantitative investors would have hundreds, if not thousands, of positions, discretionary managers are using these datasets to build more concentrated portfolios in accordance with their fundamental investment philosophy. This approach to investing – facilitated by recent developments in technology – goes by several different names, but ‘Quantamental’ is the most common.
Managers following a Quantamental approach do so for various reasons. Some are trying to improve investors’ returns, while others use big data to limit their downside exposure in volatile market conditions. But all are using technology to analyse billions of data points to drive better outcomes for investors.
“One way managers can reduce risk or enhance returns is by running scenario analysis,” says Mark Veevers, chief executive at MAIA Technology. “By using technology and using data, they can evaluate their portfolio against a defined set of events that could occur in the market, which is a very common risk management approach.”
“For example, a client of ours was doing econometric back-tests that took days or weeks to run for very extended periods. New technology has allowed managers to quickly run back-tests across vast datasets for longer date ranges.”
Recent technological advances – such as improvements in data storage and data security – have helped fund managers move more of their processes online with a level of confidence that few could have imagined just a few years ago.
Developments in technology mean it is now possible to manage extensive datasets from a single platform, meaning there is a single source of truth. This increases efficiency by removing silos, reducing costs, and allowing every fund management professional to make investment decisions using the same data.
An approach driven by investor trends
While technology has made the Quantamental approach possible, investor trends are the real driving force of its adoption among discretionary fund managers.
For example, the growing appetite for funds prioritising environmental, social and governance (ESG) factors delivering responsible investment strategies has led to the emergence of new products relying on a vast range of new datasets.
“Firms are starting to take greater consideration around responsible investing, which has led to a rise in the amount of data feeding into the investment process,” says Veevers. “At the very least, it’s an additional set of datapoints for discretionary managers to consider.”
Managers must also demonstrate how their ESG investment process works, as clients are demanding greater transparency to ensure it meets their expectations. Every stage must be documented, from identifying potential investment opportunities to thorough ESG analysis and evidence of how an investment decision is reached. And this data must be stored and managed within the firm.
“The depth and diversity of different datapoints have focused firms on how they manage or control new datapoints and incorporate them into the investment process,” he adds.
While investors show a greater willingness to back fund managers that take a Quantamental approach, not all fund supervisors can make the move.
An API-led experience giving clients full control
Reliance on legacy systems and any ‘technical debt’ from underperforming systems mean that modern investment techniques are off-limits to some fund managers. Therefore, it is crucial that firms have the technology stack in place to support a hybrid style of portfolio management.
MAIA Technology was born within an asset management business, so we understand fund managers’ challenges and demands. It has been innovating since the company was launched in 2019.
The MAIA technology stack is entirely cloud-native, and the deployment and upgrade regime allows the system to be upgraded on a weekly basis with practically no input required from the client. The system provides exceptional scalability and flexibility, adapting as clients’ needs change.
The widespread adoption of API-led technology solutions means asset managers are no longer encumbered with various third-party interfaces that create barriers between the users and the data. However, while traditional REST (request response) APIs have become commonplace in the fund management industry, more responsive options are available.
MAIA Technology’s Client Gateway is an API-led solution that gives clients full programmatic control over every part of the system – from order-raising and compliance to order execution and data management – and exposes every datapoint and system function, making its data open and accessible. Client Gateway supports reactive integration, notifying clients as market or system events are triggered across the system.
“We provide a front-to-back platform that allows the management of large datasets – including the control and audit of those datasets – and implementing investment decisions,” says Veevers. “That includes order raising, integrated pre-trade compliance and risk, order and execution management, all on a single platform where managers only pay for what they use.”
Delivering value to fund managers
Our solutions include MAIA Systematic – designed for technology-led investment firms taking a systematic approach to execution – and MAIA Enterprise – which aims to guide users in large investment organisations with multiple integration requirements and diverse investment strategies across asset classes all the way through the trade lifecycle.
It does not matter how big your firm is: the MAIA platform is one of the fastest on the market and has been built to provide exceptional scalability and flexibility. Scalability and flexibility mean we can provide a bespoke solution for our clients and offer considerable value for money.
The key innovation of the MAIA platform is its distributed approach, combined with high performance messaging. Each individual software engine can run as an independent entity, without depending on a shared resource, such as a static database service. The platform’s proprietary protocol ensures large volumes of data are represented concisely, and the data flow is secure and high-performance.
This architecture enables us to process thousands of orders and millions of data points without impacting the user experience. Individual engines’ data caches ensure business decisions are actioned instantly, enabling complex compliance checks, aggregation of hundreds of thousands of trade executions, and immediate risk exposure calculations.
“At MAIA, we’re obsessive about providing excellent client service and can react quickly to client needs,” adds Veevers. “What’s critical for the investment manager is having access to a technology stack that natively operates in the cloud and can leverage these new architectures in a way that really delivers value.”