Update Magazine I/2019 › Download the complete magazine

1 The digital transformation of the financial sector

It is a trend that nobody can escape: the changes brought about by digital technologies. The financial industry is also deeply involved in efforts to deal with this digital transformation. For asset managers, the focus is on how artificial intelligence (AI), machine learning and alternative sources of data such as social media, Internet search engines, the news, blogs or satellite images can be used to outperform the market, and to achieve better portfolio results.

In order to outperform the market, investment experts will have to draw complex conclusions which they then use to develop an information advantage over the market as a whole. New technologies offer the opportunity to take advantage of data processing and interpretation, and optimise market assessments. Implementing this at Allianz Global Investors is the focus of the Digital Transformation Working Group.

2 AI is based on the processing of huge volumes of data

Two factors will be decisive in successfully applying AI. First: modern computers open the door with their enormous computing power, enabling us to process and evaluate very large quantities of data. The keyword here is “big data”, on which self-learning algorithms rely; the more data they receive, the more powerful they become. Second, and by extension, this involves machine learning. The “equities” asset class and multi-asset strategies show how these two factors can be integrated into the active investment process at Allianz Global Investors.

In the “equities” asset class, the focus is on using AI for the fundamental data platform and for factor investing. Allianz Global Investors has already integrated machine learning into several factor investing processes, although to date “big data” have been processed and evaluated only to a limited extent. The huge potential in this area needs to be further exploited. Currently, further focal points include natural language processing (NLP) and obtaining information from unstructured data such as news and business and research reports from sell-side analysts. Investment experts are reviewing different areas of application, and would like to expand capacity in order to support quantitative and fundamental research and investment processes.

The idea behind using AI for multi-asset strategies is to take advantage of new technologies in order to evaluate larger amounts of data, and to make it possible to design a more efficient portfolio using machine learning. In addition, Allianz Global Investors is investigating AI’s potential for improving pattern recognition so that it can more quickly detect any anomalies in large data sets. Additional milestones include optimising and automating processes in order to free up capacity to generate new ideas. Ultimately, all data should be combined at a central site where they will be available across all asset classes for direct retrieval, in order to prevent unnecessary duplication of efforts.

3 Modern technologies improve the quality of forecasts

In principle data, for example on macroeconomic trends, is also available to any other asset manager for use in drafting statements about medium-term developments in market trends. The Digital Transformation Working Group at Allianz Global Investors is specifically investigating how high-frequency data can be used to improve the quality of short-term forecasts, with the help of modern technologies and alternative sources of data. Because the capital markets are currently quite dynamic, investment experts are always looking for more flexible methods in order to better exploit market volatility, and to design more robust portfolios.

While digital transformation has only just begun in the financial sector, it is already well under way in other sectors – for example in the self-driving cars segment. Examples from other sectors generally have a positive impact on the further development of machine learning. Asset management can also benefit from that.

4 Allianz Global Investors Hackathon pits start-ups against one another

In order to gain a deeper understanding of the current level of development of AI technologies, in November 2018 Allianz Global Investors organised a competition, the first Allianz Global Investors Hackathon, in which four companies from Bangalore, Milan, London and New York competed against one another to solve the same problem. Today, most companies claim that they are working intensively on machine learning and similar technologies, and undoubtedly there are start-ups that offer such services in isolation. In this environment, the hackathon offered a unique opportunity to look over their shoulders as some of these companies implemented their technologies under real-life conditions.

The event in fact acted as a catalyst, allowing the company to think about AI now in a broader context. It also enabled Allianz Global Investors to gain a more in-depth understanding of the issue, achieving decisive progress on projects started in recent months. The hackathon was never expected to deliver turn-key solutions, but instead to provide impetus for further research and development within the company. The important thing here was to realistically evaluate the results, not least because research in new areas is never straightforward. The hackathon demonstrated how the company can approach the same problem in very different ways.

Allianz Global Investors places particular significance on taking an active approach, not only at this event, but also in the broader sense. Consequently, when integrating AI into investment processes, all actions taken should lead to decisions or assessments by the investment experts that differentiate the company from the market – in line with the brand’s “Active is” philosophy. After all, AI helps Allianz Global Investors to glean additional insights from complex data with the goal of creating portfolios that are differentiated from a market portfolio. Added to this is scalability: thanks to a complex system working in the background, the learning effect increases as the amount of data increases. This reflects an industrialisation of alpha, i.e., a fund’s excess performance compared to that of its benchmark. For a modern active asset manager this is essential in order to still be competitive in the market in five to ten years.

5 Interaction between people and machine is important

The “Active is” approach also offers potential for the client. Indeed, investment experts would also like to use the new technologies to give clients optimised access to the products and solutions of Allianz Global Investors – including through digital channels. At the same time, the economic advantages created by using AI in the active investment process should not result in people being replaced as part of the digital transformation. While it is true that the scalability of new technologies makes it possible to deploy staff more efficiently, this should not boil down to a decision between people and machines, but instead to intelligent interactions between the two. Using the latest technologies should give the people working at Allianz Global Investors more time to focus on the ideas of tomorrow.

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The volatility of fund unit prices may be increased or even strongly increased. Past performance is not a reliable indicator of future results. If the currency in which the past performance is displayed differs from the currency of the country in which the investor resides, then the investor should be aware that due to the exchange rate fluctuations the performance shown may be higher or lower if converted into the investor’s local currency.

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