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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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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On February 21, the Fintech District community is meeting the Silicon DrinkAbout community to answer the question “How is AI gonna change our 2019?“. To provide different points of view and ideas to reflect upon, we have involved three startups working with these technologies: Finscience, Kellify and Userbot.

We asked all three of them how AI will transform our lives in the coming months, here are their predictions. You will discover the whole picture by participating in the event. Sign up HERE

3 questions for Marco Belmondo – Finscience
1) How present is AI at present in our daily life?
It is like a process of evolution of the species that started in the industrial sector and has now arrived in the B2C. What has changed over the years is the purpose of AI: from substitutive to collaborative. I often talk about “New technological Humanism”, on February 21st I will explain better what I mean.
2) In 2019 what developments do you foresee and in which areas?
There will be an increase in the B2B also based on data collected in the B2C. To develop new products and services, companies need to know exactly what customers are asking Alexa or Google Home. AI will be increasingly present in the investment world thanks to “quantamental” models (half fundamental, half quantitative) that show the growing convergence between the digital revolution and the financial world. The challenge is to take advantage of synergies between these two worlds.
3) Finscience works with alternative data. What are they?
Alternative Data are non-traditional, really “big” and often unstructured data coming from social media, blogs, forums, e-commerce platforms, maps, etc. We need specific skills and cutting-edge technologies to work with this data. For example, thanks to AI, data from different sources can be combined to make important investments and also to prevent potential strategic risks. With Alternative Data we monitor not only the “main signals” but also the “emerging or weak signals” that provide precious insight on developing trends not yet evident in the financial market but require the use of software capable of eliminating background noise and fake news.

3 questions for Francesco Magagnini – Kellify
1) In which sectors are AI more present in this moment?
Consumer electronic multinationals are increasingly using devices connected and managed by the AI. In the healthcare sector, patients are subjected to robotic surgeries, diagnostics and remote assistance; facilities in which AI is increasingly present. In the future I imagine it will go beyond simple speech recognition and automatic execution of tasks, starting to understand the purpose and intention behind each command.
2) In 2019 what developments do you foresee and in which areas?
2019 will be the year of technological convergences. AI, IoT, Robotics, Quantum Computing and Blockchain will be integrated into standard processes that will bring unprecedented productivity and usability gains. The cars will become “mobile space”, suitable for relaxation or for a business presentation, for targeted shopping and guided by the AI or for a new savings step
3) How do you use AI with Kellify?
Thanks to AI and Deep Learning we can transform unrelated markets, typically illiquid – art, vintage cars, collector’s items and wine – into alternative asset classes. In 2019 we will release our APIs, making our product available to the Challenger Banks and the Open Banking Platform.

3 questions for Danilo Rubicondo – Userbot
1) How will Al change our life in the next year?
AI, as an emulation of complex cognitive faculties, will not enter into our daily life soon. The Machine Learning algorithms that allow automating smaller domains are however very common since 2010, in eCommerce platforms, for example, or in speech and facial recognition algorithms.
2) In which sectors will AI have the greatest impact in 2019?
The field of natural language and virtual assistants will have a very strong expansion thanks to the exponential increase of IoT devices. I expect a similar trend for devices that observe the surrounding environment and interact automatically, used for alarms or cars for instance.
3) How do you use Userbot and how will you use AI?
Userbot develops virtual assistants able to guide the user in the resolution of a request, similar to human operators in the customer care or front office. AI assistants are fast, tireless and work 24/7 but need to be recalibrated by an expert when the scope changes a lot. In 2019 we aim to make our AI increasingly able to perceive change autonomously and adapt to it dynamically, without human intervention.

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Artificial intelligence is penetrating every sector and that of finance is certainly not one of the last preparing itself to be transformed because of it. Together with Alessandro Vitale, author of the book “Artificial Intelligence” published by Egea and part of the series on digital innovation edited by Talent Garden, we want to explore the binomial “artificial intelligence & fintech” trying to imagine the challenges that await us.

To whom is the book addressed and with what purpose did you write it?

The book is designed for managers and business people who want to better understand what AI is to be able to introduce to their organization. There is a lot of technical literature on the AI but something was missing which would address all the other important issues for the company, for example how processes are impacted. To write it, I was inspired by the books found in the bookstores of airports, those with which a Manager can have a good idea on a theme in the space of a round trip, which is actually the reading space available in this day and age.

What subjects did you deal with and from which point of view?

The book consists of 10 chapters to be read independently, each linked to a keyword. The first 4 chapters (Artificial Intelligence, Applications, Machine Learning, and Data) are the basis for understanding what AI is and how it works. The second part enters into the heart of managerial choices; we talk about People and their relationship and reactions to AI, the Skills necessary to develop and use it, how the Processes change in the company, how the Design of products and services changes; what Risks are introduced and the ethics that should guide us, such as Begin and choosing the first use case.

Give us three examples of AI applied in the world fintech insurtech?

There are applications, such as the robo advisor, which take advantage of the progress of Artificial Intelligence, in which Italy also plays a role together with excellences such as Deus Technology. Tractable is a UK startup which uses image recognition to estimate damage to cars just like an expert does. Included are also chatbots, also processed by my company Conversate, with examples like Mario, the chatbot developed by UBI Banca to support the merger of the Good Banks.

Opportunities and risks given by AI to the fintech sector

AI allows you to improve the service to your customer and do this more efficiently. Cleo, starting with 2 people and 10,000 pounds, after 18 months had a chatbot used by users with half a billion savings, users who used Cleo instead of their bank’s app and to whom Cleo aims to sell financial products and collect commission in the place of the bank. Depending on whether you are a startup or an incumbent, or rather, depending on the company’s approach to innovation, AI can be either an opportunity or a risk to the business.

How will AI transform the fintech sector according to you within the next 5 years?

As the futurist Roy Amara said, “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run”. The impact in the short run will be less than the current hype but in the long run it will certainly exceed the expectations. A recent Harvard Business Review article says “Over the next decade, AI will not replace managers, but managers who use AI will replace those who do not.” Acquiring these skills and bringing them into organizations requires time and effort; the sooner you do the sooner you will be able to help build the future and not suffer because of it.

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Last week in the second round of our “Talking Heads” format we hosted the WiMLDS community to talk about machine learning and data science. We have discovered how these themes can influence the present and future of the fintech sector. It was also an opportunity to deepen the activities of this reality that has just started writing its Milanese chapter and is also open to collaborations and initiatives also shared with interested companies and startups and that share its mission.

Here is the interview with the two referents of WiMLDS Milan,Claudia Volpetti and Carlotta Orsenigo, speakers at the meeting together with Katarina Milosevic (Generali)

Machine learning in finance and banking: 3 examples of already existing applications and one that you are looking at

Machine learning plays a prominent role in several financial applications from trading, where complex algorithms are used to optimize trading decisions, to credit scoring, with the aim of predicting the creditworthiness of individuals or companies, and fraud detection, to identify new potential security risks.

Which activities would you like to carry out in the Milan area (meetings, workshops …)?

WiMLDS (Women in Machine Learning and Data Science) is an international community of women interested in machine learning and data science. The WiMLDS Milan Chapter, the first Italian chapter of the community, was established at the beginning of 2018 as a local Meetup group in Milan as the Italian reference point of the international WiMLDS community which currently counts 25 chapters spread all over the world. WiMLDS Milan’s mission is to create opportunities for women interested in machine learning and data science as well as engage in technical and professional conversations in a positive, supportive environment by hosting talks, technical workshops, networking events and hackathons. WiMLDS Milan is organized by Claudia Volpetti and Carlotta Orsenigo who are members of the Machine Learning and Big Data Analytics research group at the School of Management of Politecnico di Milano. On the meetup page “Milan Women in Machine Learning and Data Science” you can find updates on the forthcoming events and meetings.

How can you contact a fintech company that wants to commit itself to decreasing the gender gap in the sector? What actions can it take? What would you propose to do in a joint collaboration with you?

Companies interested in WiMLDS events can join us on the MeetUp community or contact directly the organizers Claudia Volpetti and Carlotta Orsenigo at Politecnico di Milano. Companies can support initiatives by hosting meetings, workshops and technical sessions or helping WiMLDS in organizing hackathons related to the machine learning and data science domains.

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Talking Heads meet WiMLDS is the second round of our new format launched before summer discussing digital strategies for Fintechs with Derev, Hoopygang and Plick. This time the Fintech District community meets a new reality that has just started writing its first chapter in Milan. We interviewed one of the two Italian organizers, Claudia Volpetti. Make sure you don’t miss the 12th of September to meet her and listen live to what she does.

What is WiMLDS and what is its mission?

WiMLDS is an international community of women interested in machine learning and data science. WiMLDS’s mission is to support and promote women practicing, studying or interested in the fields of machine learning and data science. We create opportunities for women to engage in technical and professional conversations in a positive, supportive environment by hosting talks by prominent female or non-binary data scientists and engineers, technical workshops, networking events and hackathons. We are inclusive to anyone who supports our cause regardless of gender or technical background. However, in support of our mission, priority for certain events and opportunities will be given to women.

When did it arrive in Italy?

The WiMLDS Milan Chapter was established at the beginning of 2018 as a local meetup group of the international non-profit community of Women in Machine Learning and Data Science. This is a group for women who are interested in Machine Learning and Data Science

Which kind of activities does it do?

We meet to share knowledge and working experience in these fields, with the purpose of building a community of professionals. Our meetings are open to anyone and any support to our events is welcome. The WiMLDS Milan Chapter is organized by Carlotta Orsenigo and myself who are members of the Machine Learning and Big Data Analytics research group at the School of Management of Politecnico di Milano. On the meetup page “Milan Women in Machine Learning and Data Science” you can find any update on the forthcoming events and meetings. The one organized with the Fintech District is our next event.

What will we talk about at the meeting organized by Fintech District on the 12th of December?

More and more companies are using data science and machine learning for optimizing their business processes. This event, jointly organized by Milan WiMLDS and FinTech District, will host data science and machine learning professionals and researchers and who will share their experience in these fields describing applications used in finance and entrepreneurship. The presentation of WiMLDS will be followed by Carlotta Orsenigo’s speech on the theme “Green or non-green? Detecting sustainable crowdfunding campaigns via text mining “and that of Katarina Milosevic on” Forex forecasting with Deep Learning “. The meeting will end with a moment of networking

Make sure you have a place at the meeting, sign up here. If you wish to stay uptodated about news, events and initiatives of the Fintech District, subscribe to our newsletter HERE