Dutch Data Science, part 3: Finaps

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For the third installment of this series I visited Marlies van Sonsbeek (CEO) and Andrew Hagens (Chief Innovation Officer) of Finaps in their beautiful office in the south of Amsterdam.

Company Overview

Finaps is a young innovative company founded at the end of 2010 by two former ABN-Amro colleagues. Not surprisingly the initial focus was on financial institutions, but since then Finaps broadened their scope to other industries such as government, NGO’s, and healthcare. Finaps started out as a dedicated Mendix partner mainly building solutions (portals, case management, workflow) and mobile apps for the financial services industry, hence the company name. Marlies joined the company early on as an advisor, but quickly became infected with the companies’ energy and became their CEO at the beginning of 2012. Though Mendix was (and still is) the main development platform, Finaps adopted a wide range of technologies to deliver class leading solutions to their customers.

The people at Finaps are all, as Marlies calls it, ‘young smart professionals’ with an innovative and creative mindset and focused on delivering results. A core competence across the team, consisting of around 30 people today, is the ability to quickly deliver working business solutions. Finaps always works on projects or solutions with a team. One of the perks of Finaps is the location of their office, and the office itself: Located in one of the most beautiful areas of Amsterdam they occupy a classic office building close to the Vondelpark and the major Amsterdam museums.

Hackathons

The partnership with SAS is explicitly mentioned as a key differentiator in providing analytical capabilities to end users which results in democratising analytics. According to Marlies, SAS offers the best analytics platform on the market and is driving much of the success of the Finaps solutions. The partnership also allows both parties to cooperate in many projects. As an example of this, SAS and Finaps team up in hackathons and are able to deliver cutting edge solutions in a very short time frame.

One of the cool projects below is a result of one of these hackathons which a combined team recently won. Even though technology is important to build and deliver solutions to the market, the focus is on applying this technology, and never on the technology itself. The same approach is taken when it comes to AI: It only makes sense when it’s embedded as part of a solution, providing a seamless user experience.

Cool projects

One of the coolest projects so far was called ‘Sir Botsalot’, which is a chatbot supporting HR questions in an organisation. The chatbot is context driven and is using a multi-step approach in providing a usable answer to the user. SAS’ decision engine is called whenever the chatbot cannot directly provide a good answer, and also to redirect the user to the best suiting employee based on the conversation.

Another cool project was the one built during the hackathon at the University Medical Centre of Utrecht (UMCU), one of the largest academic healthcare institutions in the country. Together with SAS, Finaps won the overall competition and is now productising their solution for cardiology and rolling out to other hospitals as well. Part of the solution was based on text analytics where ICD10 codes are being derived from the diagnostic text entered by physicians. Also for UMCU Finaps and SAS are building a solution to predict sepsis for the neonatology department and provide guidelines for the right antibiotics.

Continuous Challenges

It’s probably no surprise anymore if you’ve read the first few installments of this blog series: Hiring is named as the number one continuous challenge. Finaps is competing for talent in a very busy market but usually wins people over by their culture, team, and creative approach in building solutions. Their catch phrase: “Do you want to matter or do you want to be a number?"

Second challenge is convincing (potential) customers of the added value of innovative solutions; the big corporates are still risk averse, in spite of stating that they want to innovate.

The future of AI & Machine Learning

Finaps doesn’t see AI and related technologies as products, or a technology that will change products: The entire society is going to change. AI will become invisible and fully integrated in every product or service we interact with. In a couple of years, we won’t even know the difference anymore between e.g. human interaction and communication with chatbots. AI is not, or should not be, a driver to replace people but a means to give people freedom. There are risks as well: De-humanising society and potentially widen the gap between digital haves and have not’s. But they also realise that no one knows exactly what’s going to happen.

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My take

It’s hard not to be impressed by the energy and creativity when meeting with Finaps. Their clear vision, focus and proven track record in developing analytics driven (mobile) apps make them, in my opinion, a natural choice as a partner in that still highly innovative area. That, combined with their ability to think outside the box, apply whatever technology is needed to solve a problem, and keeping an open mind for even better ways to do things ensures a bright future for the company.

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About Author

Jos van Dongen

Principal Consultant

Jos van Dongen is a consultant, author, speaker and analyst. Jos has been involved in software development, business intelligence (BI) and data warehousing since 1991 and is the (co)author of three highly acclaimed (open source) BI books and numerous magazine articles. Over the past years he has been the lead architect for a wide collection of analytical solutions in a variety of organisations, both profit and non-profit. Jos speaks regularly at national and international conferences about new developments in BI, Analytics and Data Science. After being an independent consultant for over 15 years he joined SAS in May 2013 as a principal consultant. In his current role he advises customers on various topics such as Data Visualization, Data Science, Machine Learning and Internet of Things.

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