MDOTM: Artificial Intelligence in the Asset and Wealth Management Industry

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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99bros focuses on AI and multimedia to innovate insurance

99bros has recently joined the ranks of the insurtech start-ups and scale-ups belonging to the Fintech District community. To better understand its business, we interviewed Founder and CEO Claudio Cancellieri.

What does 99bros do and who is it aimed at?

99bros is a digital insurance brokerage platform which, thanks to an integrated system of artificial intelligence, multimedia content and specialised consultants, allows customers to choose the solutions best suited to their risk profile, managing the choice and subscription of policies quickly and easily online. We mainly target people under 40, individuals and families, offering the best solutions for car, motorbike, scooter, bike, home, life, health, accident, supplementary pension policies, and more.

How has it grown in recent months?

After the acceleration in Luiss Enlabs and the related funding received from LVenture Group and Lazio Innova in 2020, we are now on the market with the aim of increasing our customer base to be able so as to refine our machine learning algorithm better and better and to be able to offer our solutions to a wider audience, perhaps even outside of Italy.

Have you done or would you like to do any open innovation projects? What kind and with whom?

We don’t have any on the horizon yet, but we would like to do some with car manufacturers, for a very innovative service that has been running through our heads for a while ….

How is your team structured?

Our team is very “concentrated” and is made up of just five people: Roberta, who takes care of all the operations, Claudio, the CEO, Stefano, the CTO, Marco, who is the Sales Consultant, and Fulvio, who takes care of Marketing.

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MDOTM, AI-Driven strategies for institutional investors

MDOTM is the European leader in developing AI-Driven strategies for institutional investors. We work closely with our clients such as Banks, Family Offices, Insurance, Wealth and Asset Management companies to provide them with reliable, robust, and bespoke models that enhance their investment decision processes. We interviewed CEO Tommaso Migliore to find out more about the goals and future plans of this fintech, which uses the advantages of artificial intelligence to change the world of finance.

What is MDOTM’s mission?

Our mission is to bring the scientific method into the world of investments, and we do so by exploiting the latest breakthrough technologies as well as advanced statistical techniques. This allowed us for the creation of rational and unbiased models that are able to build more robust and efficient portfolios. In this context, data is the fuel for our engine: every day we collect and clean the huge volume of noisy market data. Then, we use our proprietary technology called A.L.I.C.E. (i.e. Adaptive Learning in Complex Environments) to detect the signals and patterns hidden within the data, in order to develop actionable investment strategies that exploit changes in market inertia and risk premia.

What are the benefits of investing with AI-based models?

In the last decade, the internet has democratised access to information. As a result, today instead of information scarcity we face the opposite problem: information overload. This trend has been particularly relevant in the financial markets, which have become increasingly complex. To remain competitive, it has become essential to exploit advanced Machine Learning techniques in order to be able to capture signals within huge amounts of data and transform them into effective investment strategies.

Artificial Intelligence supports us in building portfolios that are reliable, unbiased, tailor-made, and able to adapt to the constant changes in the markets. Thanks to their capacity to continuously learn from market data, AI-driven models can adapt to never-seen-before scenarios and update their knowledge as new data becomes available. Furthermore, data collected is transformed into actionable portfolio management insights that do not carry any emotional biases.

How has MDOTM grown since its creation?

MDOTM was founded in London in late 2015 when Tommaso Migliore and Federico Mazzorin – graduates in Finance and Physics respectively – developed their first investment model for financial markets. Starting from personal savings invested in their investment strategy, the company grew exponentially throughout the years.

In 2017, MDOTM was the only European fintech selected to join Google’s acceleration program in Silicon Valley and, nine months later, we closed a €2 million funding round. This allowed us to grow across geographies and hire key industry experts for our team, currently composed of 30 people based between London and Milan. A new office is set to open in New York in 2022, to boost our global expansion.

Our technology is constantly improving, driven by continuous efforts towards Research & Development: overall, roughly 75% of our revenues are invested in that area. Our ability to innovate has been recognised nationally and internationally by institutions like Google, the Italian Financial Innovation Association (AIFiN) and NTT Data.

Are you following any Open Innovation projects?

We strongly believe in the power of synergic collaborations and open innovation, and we embrace it from different perspectives. On the one hand, we partner up with established institutional investors to help them innovate their investment process with our state-of-the-art technology. Using our AI-driven methodology, we are able to provide them with adaptive and unbiased portfolios that best meet their investment constraints. On the other, we collaborate with the major Italian and European universities through our research centre: the MDOTM LAB. Here, university professors, Ph.D.s, and talented students bridge the gap between economic theory and real-world practice by pioneering new strands of research, at the intersections between Behavioural Finance, Portfolio Management and Artificial Intelligence. This allows us to integrate our internal R&D findings with external research insights to stay at the forefront of innovation.

How is your team composed?

Through the years, MDOTM experienced a continuous rapid growth, recently turning into a scale-up after its initial start-up phase. MDOTM’s team faced an analogous expansion trend, and it is expected to double its size by the end of 2021. Our people reflect our approach, which is deeply rooted in science. As such, MDOTM’s team is made of creative innovators, scientists, and industry veterans with backgrounds ranging from finance and statistics to computer science and physics. The different divisions work side by side in an effort to build the best AI technology for investment decisions that major financial institutions can rely on.

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Premoneo and its AI engine for fintech and insurance

Premoneo is a company specialising in the development of custom artificial intelligence solutions to support companies in strategic forecasting and segmentation activities. Starting from the data provided by clients, and depending on their depth, it uses different types of mathematical and statistical models and as well as also artificial intelligence, machine learning and deep learning to analyse demand in real time and to be able to understand changes in customer behaviour.

The ultimate goal is to maximise the client’s profits. “What differentiates us from other companies is that we combine both human capital and our technology to ensure that our clients receive comprehensive support to maximise their results,” explains Marco Alò, CFO & Co-founder of Premoneo, saying that going further to explain that “for us, the pandemic has been a real watershed. Previously, Premoneo was focused on two markets, crowd and ticketing, offering dynamic pricing solutions, but in recent months it has created a new engine to support clients in new markets such as retail, banking and insurance and even energy. Through our engine you can better understand your customers by analysing the probability of abandonment, and their value over time and then create targeted offers on different products,” explains Alò. “Thanks to this new engine and this expansion of markets we have reached a pre- Covid level of turnover.

Most of Premoneo’s pricing projects are part of a broader innovation and digital transformation projects involving a variety of players including strategic consultancies and technology providers. Success requires collaboration between the various players involved, and our software allows for the integration of the various technological solutions in order to get the solution on the ground and allow the project to succeed,” adds Alò. “In this sector too.We are looking for opportunities in this sector also in where which we can make our technology available to improve the offering to the end customer.”

Premoneo’s three founders are all under the age of 35 and have heterogeneous skills: Federico Quarato is a professional journalist specialising in corporate communications in the financial sector, Massimo Dell’Erba, CTO, he is a software engineer and one of the experts in artificial intelligence in Italy. Marco Alò has a background as an analyst at MedioBanca. This trio is supported by a team with complementary skills ranging from data analysis to modelling and programming.

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BID Company, the data boutique for banks and insurance

BID is an innovative company that wants to tell the, as yet, unwritten story of data. BID is a true data boutique because it does not offer algorithms on the shelf but accelerators to customise the needs and requirements of customers in generating valuable insights and making useful business decisions.

Its goal is to ensure that everyone has access to advanced knowledge that stimulates critical thinking and helps to ethically improve the future. It proposes itself to all those companies looking for a roadmap of solutions in the world of analytics and AI. Since its inception it has been working in the finance context helping banks and insurance companies but has also developed solutions for healthcare, pharma, energy and the more luxurious world.

BID Company was born in 2016 from an intuition of Walter Ballardin who, after twenty years of experience in the financial context on analytics issues, founded a company that combines technical skills with functional ones to translate valuable insights generated by data into a comprehensible and actionable business language.

At this stage, BID Company aims to become the reference partner on analytics and AI issues by increasingly consolidating its clientele in the Italian market, distinguishing itself with a flexibility-based approach based on three main aspects. The customisation of technological solutions on the basis of the business value generated, agility from the earliest stages of implementation of these solutions, and the transfer of knowledge that enables customers to become autonomous in the management of these complex solutions.

To date, BID Company collaborates with leading universities in Italy, including the Cattolica University and the Milan Polytechnic, and develops machine learning and deep learning models to solve daily problems in banks and insurance companies. For marketing, it develops predictive models to optimise the customer’s journey, in the world of control system models for analysing atypical behaviour against the risk of fraud, and in Behaviour Analytics engagement models to maximise people’s potential and get them to express it this within the company.

In the context of open innovation, it uses APIs to make its algorithms accessible to all interested parties. For the future it plans to continue to invest in open innovation and continuously improve its algorithms to develop valuable solutions for banks and insurance companies.

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From California Loop AI Group, specializing in cognitive computing

The LOOP AI group was created in 2012 in San Francisco and has extended its area of activity to Europe and Asia with the aim of accelerating the transition of traditional companies into smart companies capable of enhancing work teams also employing non-human potential, cognitive robots. In fact, as Andrea PITRONE, Chief Customer Success Officer and Chief Product Officer, says:”Traditional companies can no longer compete with smart companies, companies that use cognitive robots, not only because of the cost reduction that follows the use of this technology, but also because of the higher level of quality of products and services that can be delivered”.

Among the awards received by this company, the inclusion in a report by IDC in January 2020 placed them among the top ten providers of general purpose artificial intelligence platforms and software along with Amazon, IBM, Microsfot and Saleforce.

LOOP AI group is the only provider that can deliver a fully unsupervised cognitive platform via integrated hardware and software appliance called LOOP Q, which can learn and read any human language or business jargon. LOOP Q enables the rapid development of cognitive robots that support, empower or automate key business processes performed by humans. The main target of LOOP AIGroup are both large companies and small and medium-sized enterprises: “we approach them with very different business models – explains Pitrone – with the aim of enhancing the human capacity for learning and reasoning of enterprises.

Although the company is young, it already has a good number of large account clients at a global level in banking, insurance and telco, but intends to grow further both in Italy and abroad, “focusing on SMEs and establishing targeted partnerships with other certified partners, i.e. system integrators able to develop cognitive robots and advisors using our innovative technology”.

As far as the team is concerned, LOOP AI Group has some important figures, the so-called veterans who have been working for about 20 years in the world of artificial intelligence with development activities, research, exploration in very sensitive areas, including military ones,and have invented and developed the LOOP Q technology. In the company there are also resources that have matured a solid professional experience in one of the main consulting companies at a global level. “We have an expert team of advisors that cover the competences of cognitive computing as well as strategy, marketing and software development of enterprise applications – explains Pitrone – and we also have several certified partners that allow the scale up of the development activities of cognitive robots at customers”.

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Banksealer is ready for open innovation with insurances

Banksealer is a spin-off of the Polytechnic of Milan. This last, drawing from academic research in artificial intelligence and machine learning, has realized technology transfer by applying algorithmic results on a platform to subsequently build behavioral models useful for fraud identification and decision support. CEO Alvise Biffi tells how 2020 was and what his plans are for 2021

What does Banksealer do and who does it target?

The Banksealer platform identifies fraud by working on the analysis of the behaviour of the subjects participating in the process under examination. The typology of the controlled process can be multiple: passive cycle, active cycle, goods, e-commerce, digital payments, system access log. The platform operates with a white-box machine learning approach. The solution is addressed toward corporations, banks, insurance companies, public administration, subjects operating in the world of e-commerce and in general subjects operating in B2C logic. The system is also suitable for the control of internal processes of large organizations.

How has your business changed with the arrival of the pandemic? How has it impacted both quantitatively and qualitatively on your work?

The pandemic has certainly increased market interest in solutions like Banksealer. The sudden increase in “home working” has widened the attack surface in corporate subjects and consequently there has been an exponential increase in fraud attempts, many of which unfortunately are successful. Despite the increase in demand, we have seen a marked slowdown in the commercial sales cycle. The pandemic has lengthened contact and decision-making times and reduced the budgets of a large proportion of our potential customers, so although demand is growing, conversion times have lengthened due to market uncertainty.

What are your plans for 2021?

Having registered a very strong increase in demand in the corporate target, in particular for the passive cycle, we are completing the standard integration of our platform with the main ERPs directly in the Cloud. We have been selected by Microsoft for their international startup program and we are working on the integration of Banksealer among the extension dynamics directly available in the Microsoft marketplace in order to simplify in a plug and play logic the installation of our product for all their customers.

Have you done, or would you like to do, any open innovation projects? With what kind of players?

We are carrying out a project of experimental application of our algorithmic engine together with one of the main international players in the trading of raw materials. One of the main strengths of our engine is its adaptability, so we are available to new experiments for all areas of application of dynamic analysis through behavioral models. For example,with insurance players, there are several possible applications not only for anti-fraud but also for recommendation logic. We would like to find partners to start an experimentation in open innovation logic.

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Interview with Damien Philippon, co-founder of Zelros

Damien Philippon, COO & Co Founder of Zelros, tells us in this interview what his artificial intelligence solutions company offers in the insurance field. Zelros is operational in three countries for now, France, Germany and Italy, and is based in Milan, Italy.

Watch the video to find out how this fintech operates, what are the values with which it was built and how its team of talents is formed, which you can be part of too, if you want, as they are looking for new people

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Artificial intelligence in the future of fintech

Artificial intelligence is becoming an increasingly important player and is transforming and strengthening many sectors of our ecosystem, including the financial and insurance ones. We asked Francesco Basciani, data scientist of IBM and expert in the subject, what could be the possible developments in fintech and which new job opportunities could arise. Basciani is also one of the mentors in our mentorship program offered for free to the startups of the community. If you want to know more click here. But first, read the interview!

AI is developing fast but there is still great unexpressed potential. What are the biggest challenges for “unlocking the potential of AI” in 2020?

The application of AI models within companies is bringing benefits in terms of process automation, improved customer service and the discovery of previously unknown insights. The main ingredient to make profitable and proficient use of AI, is certainly the most important data. The more data you will own and the more you will be able to make it consistent and easily usable, the more you will be able to develop a data-driven approach within the company.

A limit we find today, however, is the non-applicability of AI in strongly regulated contexts where, in many core processes, the objective cause-effect relationship of the phenomena is required. This is one of the themes of the future: to make AI explainable. If we overcome it, there will be a great development of Augmented Intelligence.

What problems does the AI solve in the financial world today?

The application of AI in the financial and insurance sector is also allowing to improve the quality of services to the customer and reduce time and costs through better management of risk and fraud. The fields of application are many, from capital trading to fraud detection. On the latter, many traditional players are opening up to the use of increasingly innovative techniques to anticipate and discover new fraudulent patterns. This is a great challenge for the future.

And, which ones could it resolve, or contribute towards resolving, in the future?

In general, the fields of applicability of IA are numerous. With the advent of the 5G, the explosion of the IoT and increasingly simple access to large computational resources, the problems that the AI can help to solve are many and varied. The most important issue will surely be understanding the role of AI in the process of improving services such as Robo Advice, anti-money laundering or fraud detention (increasingly advanced).

This evolution also has an impact on new job opportunities. How do the profiles that companies have to choose with the necessary skills have to change?

Surely soft skills are becoming increasingly important in the labor market because of the high speed with which technologies are changing. For this reason, a strong analytical ability will be increasingly required, together with a strong curiosity and a great ability to seize the opportunities that innovation offers.

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OpenAI: interview with Gennaro Calì

OpenAI has joined the Fintech District community to grow and become one of the leading players in the industry. Gennaro Calì talks about the activities and projects of this startup.

What does OpenAI do?

OpenAI is a company that builds and develops artificial intelligence solutions. Through virtual advanced 3d assistants, easily integrated via API in internal systems of companies and thanks to powerful management of big data, it allows for incredible customer experience. These solutions in fintech facilitate the achievement of objectives such as centrality and customization of the offer through a series of insights and analysis of the behavior of the end customer. A set of data also helps to optimize processes, reduce costs and create a competitive advantage over other players.

What are your most recent projects?

The most recent news regarding open Ai is without doubt the arrival among the finalists of the Auriga Fintech Award and the creation of a new solution supporting social media management and content management through artificial intelligence with a specific focus on the automation of lead generation. This helps get more customers to our customers

Why did you choose to join the Fintech District community?

Open AI has become part of the Fintech District because we believe that their community, services, and team are an excellent and fundamental partner to share, grow and seize opportunities in a market in which OpenAI wants to be a protagonist.

What are your internationalization goals?

In the context of internationalization, given the consolidation and visibility that we are obtaining at a national level, we are looking at other interesting markets in addition to European ones. For example, those of the Arab Emirates and the Asian part. We are also evaluating potential partnerships in the USA.

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