In 2021, MDOTM became the European leader in AI-driven investment strategies after raising a Series-B round and doubling Assets under Advisory (AuA). The company plans to open a New York office and expand its international operations. Representing one of the most active innovation hubs in Europe, Fintech District talked with MDOTM’s CEO Tommaso Migliore about how and where the industry is going. He also discussed how Fintech’s technology assists Asset and Wealth Managers, the rising popularity of Open Innovation partnerships with financial institutions, and the industry’s best practices for ensuring AI explainability and reliability in investments.
Tommaso, how can AI be used to improve the investment process? And how is it helping institutional investors improve their decision-making?
Making an investment decision is a very complicated and thorough process, you need to factor in a lot of information, and today, we live in an abundance of information. To get an idea, IBM estimates that about 90% of data has been created in the last two years alone, and this is not stopping any time soon. Quantitative approaches have been used for many years to support the investment process: from estimating expected risk and returns to building portfolios and managing risk. So why does it make sense to talk about Artificial Intelligence in investing? After decades of research, AI has grown to be a mature technology and has become the logical next step to bring a more adaptive and forward-looking way for managers to build holistic investment views by identifying information hidden in the noise of data. Today it can be used to build portfolios or enhance the strategic and tactical asset allocation.
Research shows that Open Innovation partnerships between Financial Institutions and Fintechs are rapidly growing. What makes them a win-win? And what are the key elements for success?
Over the last years, theAsset and Wealth Management industry has been on a journey of rapid change accelerated by massive regulatory shifts and a new competitive environment. And nowadays to compete you need to change and adapt even faster. Artificial Intelligence is bringing us into the assisted decision-making era, in which specialisation is crucial. This has led to the rise of Open Innovation partnerships, where fintech companies use their specialised know-how to develop new technologies and partner with financial institutions to support them in developing solutions that are more tailored and adaptive for end clients. Partnerships like these allow institutions to access cutting-edge technologies, acquire specialised know-how, shorten time-to-market, and reach new clients – making this a real win-win situation.
AI explainability and reliability have become a top priority, especially in investments. How did you manage to embed it into your proprietary AI? Could you give us some practical use cases?
Explainability is a non-negotiable aspect. In this sense, achieving explainability in Artificial Intelligence requires two main dynamics: the technology itself, and the internal processes. For example, when building ALICE® – our proprietary AI methodology – we embedded explainability right into the design of our systems. We didn’t develop the technology as ‘one big brain’, we developed it as a series of chains where the input is not necessarily connected with a respective output, it’s rather a series of inputs and outputs that ultimately connect together to create a final decision. This series of chains allows us to go back and track exactly what were the main drivers behind every decision that the technology makes. Regarding our internal processes, we have two teams. The first one being our R&D department of over 40 people, blending physicists, engineers, and finance experts who constantly supervise and enhance our AI. The second is the Mission Control team, which monitors the learning rate of our models and periodically meets with clients to explain the rationale behind ALICE’s insights to align their portfolios to the current market regime. This duet creates a process in which there’s a further effort to ensure that the technology is understandable and trackable.
Where do you think the Asset and Wealth Management industry is headed? What are your next steps?
What the last years have shown us, is that Artificial Intelligence and technology are here to stay. This industry is undergoing a massive change driven by increasing complexity and lower marginality. Technology has become the answer in order to cope with these dynamics. This is something not just in Europe, we’ve perceived it from our client base in the UK, Benelux, and the US – a real global-scale phenomenon. The future evolution of this phenomenon is twofold, on the one hand, client interaction will be completely digitalised, and on the other – thanks to Artificial Intelligence – assisted decision-making will be a must. The latter will allow for more adaptability and flexibility when it comes to making investment decisions, and will render the future of the asset and wealth management industry more adaptive, technological, and tailor-made for the final client.
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