When it comes to UI and UX, Mara Dumitru, our Senior Product Manager specialized in user-centered design, is convinced that “less is more”. Find out why and how this is especially beneficial for digital asset and wealth management in our interview with her.


Elinvar: Just for us to catch up, could you briefly explain what UI and UX are? And what is the difference between them?

Mara Dumitru: UX stands for user experience design and has to do with the functionality of the digital or physical product. While UX aims to solve a problem, UI stands for user interface design and represents the visual output.

More concretely, UX covers user research, where we learn about users’ behaviors and needs and interaction design, where user flows are defined and represented in wireframes and prototypes, which are ideally tested before moving to the UI phase. Here, the visual design of the product is embodied through the use of colors, typography and layouts.

However, separating the two and ensuring that the UX is validated before even considering the UI is vital. One can easily get sidetracked and lose sight of the problem that needs to be solved by diving into aesthetics before having created wireframes and validated user flows.

Mara Dumitru, Senior Product Manager

This is not to say that UX is more important than UI. On the contrary – they both play an essential role in the success of a product. However, separating the two and ensuring that the UX is validated before even considering the UI is vital. One can easily get sidetracked and lose sight of the problem that needs to be solved by diving into aesthetics before having created wireframes and validated user flows.


Services and their apps – I am thinking of Netflix, Spotify and Instagram – are not just competing among their peers, such as Netflix vs. Amazon Prime, but on a more general level: Every app and every service on my phone wants to have my attention and time. To what degree does this apply to digital asset & wealth management, and how does UI/UX react on this development?

The success of a product or service is not necessarily achieved if users spend significant time on it. Some products can also deliver true value that is expressed in short but regular interactions, where meaningful information is delivered to the user in a delightful and easily comprehensible way.

Regarding digital asset & wealth management, I believe one example is that our partner’s clients need a sense of reassurance when they ask themselves how their portfolio is performing. Our application thus solves a problem i.e., provides an answer to the users’ questions, allowing for a meaningful insight that is easily accessible without any information overload, at any time the user requests it.

However, users will ultimately recommend a product that brings a benefit to their life – which can be effortlessly providing a sense of reassurance on demand, allowing for more carefree time, and we all know that time is valuable to anyone.


Is there anything that is particularly unique to asset & wealth management in terms of UI/UX?

In the offline world of asset & wealth management, potential investors usually need to go through significant paperwork and physical meetings in order to open an account. Then, once onboarded, all further communication is also primarily paper based.

Now, in the digital era, we have the opportunity to not only onboard investors significantly faster and completely online, but also to extend this service for people who would not think of opening an account offline. By presenting only the most relevant information first, and providing additional information when the user requests it via interactions (information on demand), we can bring value to a wider spectrum of users: investors with relatively limited finance knowledge can either quickly understand the state of their portfolio, or feel engaged to gradually digest more information by requesting it. At the same time, users with significant finance knowledge can choose to have a quick but meaningful insight, or delve into the details whenever it suits them. Last but not least, user engagement can greatly be improved by providing individualized interactive data visualization tools throughout the user journey.


Elinvar is a B2B2C company: We are developing a product for a business client that is used by an individual investor. Is this especially challenging in regard to UI/UX? How do you collect user stories, critiques, etc. when your counterpart is another business, too?

In fact, our partners are also our users, as they are utilizing our platform to manage their investors and processes. Before developing larger features, we organize workshops with them, in order to learn about their offline practices and understand how we can support and improve their processes digitally. We also validate our user flows and wireframes with them, before implementing the final designs. Regarding existing features, as we are in constant contact with our partners, we receive regular feedback on how they use our platform and integrate it in our iterations.

Linking our data-driven approach with qualitative feedback allows us to understand the full picture.

Mara Dumitru, Senior Product Manager

Due to our B2B2C approach, the feedback from our partner’s clients is mainly data-based, generating tremendous insights into our product and the user behavior. However, we also receive the clients’ feedback via our partners who maintain very good relationships with their clients and pass the most relevant findings and suggestions to us. Linking our data-driven approach with qualitative feedback allows us to understand the full picture.

In addition, we also use internal tests, where we test the understanding of content on certain onboarding steps with relevant users, but we also analyze the interaction of features, which can actually be tested by anyone who is not working directly with the product or wasn’t involved in the design process. Interaction design testing is just as valuable with non-target users as it is with target users. Here, our purpose is to ensure that the actions that the user needs to do are unambiguous and can be done effortlessly.


Building on the prior question, how do you measure the success of UI and UX changes and developments?

When thinking about onboarding new investors to the platform, the conversion rate is our measure. Moreover, we analyze the time it takes for investors to go through the steps and aim to shorten the process while providing clear and relevant information that ultimately leads to the user completing the process. While – as a BaFin licensed portfolio manager ourselves – always making sure we’re fulfilling all regulatory requirements

In addition to data-driven analysis, we’ve also integrated qualitative feedback that has helped us to provide our partners with insights in order to understand the “why” behind the “what”. With these insights, our partners and we know whether people spend a period longer than is average on a certain page because they are interested in the content, or because they feel confused or lost. An important difference!

Concerning onboarded users, success is also defined by their regular usage of the product and the feedback we receive from our partners. The same goes for our partners who use our platform and provide feedback to us directly.


Like many other tech companies, Elinvar is working with an agile production framework. In what respect is this challenging for an UI/UX designer, and what are the definite advantages?

When talking about challenges, I would say that it’s sometimes difficult to keep up with the fast development cycle. But at the same time, the speed is also the massive advantage, allowing us to constantly receive and implement feedback. We can release small iterations faster, test them and analyze how they actually perform, and then iterate and ship again. From a design thinking perspective, agile is the most appropriate framework that allows for continuous feedback integration and optimization


What are your previous experiences to Elinvar and how would you compare them to Elinvar? What are your greatest learnings?

Before having joined Elinvar, I worked in the travel and online food industry. Admittedly, the domains are very different, but in all positions, I had the same intention: use digital means to help create a product that provides value to people. What I have learned in all the positions I’ve held is that you really need to understand the users of your product. You never know what users want or need, unless you get to know them.You won’t understand them, unless you empathize with them. Therefore, it is absolutely necessary to find out how people use products offline and what challenges they are facing.

Testing and data are key in validating ideas, and great products result from multiple iterations, both before and after launch.

Mara Dumitru, Senior Product Manager

When it comes to building a product, I believe the greatest learning is that you should get detached from your initial ideas and be willing to let go and try a different approach. Testing and data are key in validating ideas, and great products result from multiple iterations, both before and after launch.

Digitalization is not an end in itself. Digitalization enables increased customer benefit and more efficient processes – two important prerequisites for long-term competitiveness. This is made possible, among other things, by increasing and using organizational knowledge, which comes about through the correct collection and evaluation of data. Event sourcing has great advantages for the handling of financial data and especially transaction data.

[This article was published first on IT-Finanzmagazin.]

Many players in asset management, in particular, are currently looking for the ideal strategy to digitalize their processes. When deciding on the right technology or the right partner, the approach to data collection and analysis should therefore also play a relevant role. Event sourcing is such an approach, which, if properly implemented, brings many advantages for asset managers and banks.

Event sourcing makes it possible to combine regulatory requirements with modern data analysis. In particular, asset managers and banks benefit from the comprehensive insights into the behaviors of clients made possible by event sourcing. This makes it possible to determine and verify the best strategy for an investor.

Sebastian Böttner, CTO & Co-Founder

A centuries-old accounting method for the digital age

The principle of event sourcing is simple: every transaction, every interaction, every change in a data record is recorded as an event in an event store. Old values are therefore retained, and only new ones are added. With repeating the events, changes can be traced transparently at any time.
The approach, which, in many functionalities, is similar to blockchain technology, dates back to a centuries-old accounting method. Due to falling data storage costs and new data storage options such as the cloud, it has become increasingly attractive in recent years and is now used by IT specialists for the digital processing of sensitive data in various industries.
Several advantages speak for its use in the financial services context and especially in investment:

    • Automated Audit Log: With event sourcing, each individual entry (event) is invariably stored – this corresponds exactly to the definition of an audit log. Because the events are always used to picture the current state of the system (aggregate), you can even prove the correctness of the log.
    • Time Travelling: In event sourcing, the status (e.g. asset statement) is calculated from all individual events. Since all events are stored, it does not matter until when the process is continued. This means that the state can be calculated at any time.
    • Delta can be determined over any period: Because you can go back to any point in time, it is also possible to determine a delta between two points in time. This allows you, for example, to show the yield for any period of time.
    • Testing over the entire history: The status of the system is determined from all events. If the state for a new version of the system is identical to the previous version, it can be assumed that this version works correctly.

Event sourcing is also exciting in other areas such as behavioral data, as it can generate information that would not be available without this approach.

Sebastian Böttner, CTO & Co-Founder

Whilst ensuring data protection on the highest level, data can be evaluated effectively. The user behavior can be analyzed, and future user wishes can be anticipated and fulfilled at an early stage. The knowledge generated by event sourcing ensures an organizational advantage and a good basis for long-term customer loyalty. Also, customers expect their service provider to use the information they share with them to continuously optimize their individual solutions.

However, the approach also poses challenges that must be considered during implementation:

  • Event Sourcing vs. Command Sourcing: Event sourcing can easily be confused with command sourcing during implementation. In this case, commands are saved instead of events. This approach loses several advantages of event sourcing.
  • Performance: The processing of all events at each start leads to longer and longer start times in the long run. Snapshots can improve performance, but they increase the complexity of the system.
  • Modification of the data set: It happens again and again, that data has to be adjusted in retrospect. In principle, this is not possible with event sourcing. Instead, new events must be created, usually with a different type. The change is therefore many times more complex than a simple update in the database.

Conclusion: Powerful but difficult without an experienced partner

Event sourcing is an extremely powerful approach that can be used for financial services through a modern digital platform and offers many advantages, especially in the area of investment. However, the challenges associated with the scope and irrevocability of the recordings require an individual consideration and implementation of the approach in the contest of one’s own digitalization. In order to keep focus on their core competencies, asset managers and banks should, therefore, seek a competent technological partner who has the necessary expertise and uses event sourcing as a fundamental approach to the digitalization of processes.

Artificial Intelligence is embedded in popular culture with incredible authors on the topic such as Asimov, Heinlein, and many many others writing on the topic. It is arguably only in the last 10 years, however, that we have seen the technology starting to have use cases that show a real promise to stand the test of time. Indeed, previous false springs for AI have caused a strong whiplash and lead to ‘AI Winters’ in the 70’s and 90’s.

Is this time going to be different? How can we tell? In this article, which is the first of larger series in the topic, Elinvar’s Director International, Niall Bellabarba puts AI under the spotlight. By highlighting some of the recent developments in the field and providing some key information, Niall identifies ‘fluff indicators’, some items that might indicate truths and, finally, what might come next.

Fluff, Fluff, and More Fluff

Artificial Intelligence is an area with massive investments and is becoming ‘mainstream’ with self-driving cars and voice-powered assistants like Cortana or Siri. The presence of the topic so centrally in popular culture and media is causing an inflationary pressure on news outlets to reduce the burden of proof, sensationalize and generally over-state the short-term potential of this technology and possibly not reflecting enough on the longer-term impacts. Here are some fluff indicators a prudent reader should look out for:

Vertical vs Horizontal AI

The technology is currently best as ‘vertical’ as incapable of automating processes that are well defined and doing so to great precision. For instance, keeping a car on the road even in presence of heavy traffic or listening to audio waves and answering an (ever increasing) range of voice commands are examples of ‘vertical’ task.

From this form of intelligence, no other form of intelligence can originate. To be even clearer, an extreme example: a self-driving car is not going to start studying stock market fluctuations. If within the media one were to witness a hopeful ‘halo effect’ of intelligence ‘spreading’ horizontally to another area the reader should see this as a fluff indicator. ‘Horizontal’ intelligence is orders of magnitude harder as the intelligence would need to learn skills it was never originally intended to have.

Complexity overplayed

Suspicious eyebrows should also raise when technical complexity and buzzwords are overplayed and a clear use case from the technology is not readily presented. Given the vertical nature of the technology right now, the end use case should be simple. A self-driving car is (as fascinating as it is) clear to grasp, but if technical complexity appears to be the only discerning feature of a proposition within the media or a company website then it is unlikely any substance resides under the bonnet. In a commercial context, it is possible the use case is still in development and for business IP reasons it is not ‘published’ but if the complexity does not quickly disappear once ‘in person’ interactions commence the fluff flag should be raised.

Providing guarantees when Failure & Research is the name of the Game

In this ‘media-propelled but nascent industry,’ it is tempting to over promise and offers guarantees to future clients. Such guarantees should be taken with a pinch of salt, as the reality is that even within the most advanced and big budget, firms do fail in releasing functioning AI-based products.

For this reason, if a firm is truly in the AI space but is providing a guarantee of success also when not fully aware of key items such as the real business objective, the underlying data size or quality or the time available to produce results, then one should be highly suspicious.

Foundations of Facts

If the opposite of the above were to be witnessed, this would be an encouraging aspect to be worthy of further attention. Therefore, one should look for simple and narrow applications, technical complexity explained relatively simply and strong caveats around its applicability or possible error rates. Beyond this, there are other characteristics that should be encouraging:

Quick Demo & Happy Customers

Nothing speaks louder than the power of this technology than the ability to go through the use case personally to witness the ‘a-Ha’ moment. To this end, videos and online demos should be strong factors for encouragement. Just as vitally, nothing speaks louder than a happy customer who can in his own words explain the business rationale or the return on investment the product, service or change the technology brought to his / her company.

Technical complexity quickly broken down

In the event the technical innards where an essential part of the proposition (this would need a simple explanation in itself), then this explanation should be succinct and verifiable.

There are a finite number of Machine Learning engines and schools of thought (see Master Algorithm, by P. Domingos). If the innards of an AI proposition are explained by clarifying: the Machine Learning technique being adopted, if the starting point was an open source library or if everything is an ‘in-house’ build and the key items that will cause the ML engine to fail. Finally see and meeting the teams of Computer Science PhDs propelling the firm in is paramount. This area is one where, without this intellectual capital, the firm is not likely to be a serious AI player.

Using Vs Building

In many areas of human progress, we ‘stand on the shoulders’ of our predecessors and in the AI field this is even more true. In the voice recognition and natural language processing sphere the room for improvement over readily available open source solutions is near zero. This implies that all players in the AI / virtual assistant / chat bot space are with near certainty using ‘off the shelf’ technology and in the event they were not, they would be at a massive technological disadvantage versus those who do.

A strong fact indicator would be a firm that is quite open to the fact it uses AI technology for business purposes but does not intend to pass off as having an AI core competence to build this further.

This aspect of ‘only using’ AI technology does not make the firm any less of an AI firm because the correct usage of these still requires advanced technological skills and understanding. Indeed, it is a signal of earnest, as it is clarifying its internal core competencies. Collectively, we should hope for a massive proliferation of using AI firms and 20 to 50 large global players building AI technology.

Predictions are hard; especially about the future

In this section, we try to extrapolate the trends of the last years into the future. Also given the financial industry focus of Elinvar and its clients, it seems appropriate to list some predictions on the impact of AI on the financial world.

More Use Cases, More Hype, More Knowledge

The ‘mainstream’ use cases will become increase exponentially, currently, we haven’t even finished the proverbial ‘tip of the iceberg’. These will propel more media frenzy which will in the short term probably cause more confusion over ‘horizontal vs vertical’ AI abilities. However, in the medium term, as this technology becomes more ‘day to day’, we should expect more-widespread knowledge and inability to create headline-grabbing (and largely misleading) statements as is possible today.

Rising China & Hunt for Talent

It can be expected that China will rise and (eventually) technologically overtake most, if not all, Western nations in this area. Though currently there is no such superiority, the disparity of volume of investments (public and private), University publications and valuations for FinTechs indicate (to me at least) the long-term future of AI is in the East. Given the economic and geopolitical returns of deploying this technology in the financial sphere, we should expect at some point Chinese acquisitions of Western firms even with strong valuations.

In this context, the hunt for talent will further globalize and increase. The stars of AI will be Machine Learning PhDs, and predictably they will choose their careers paths in-line with academic and economic growth opportunities. We should expect even stronger competition among tech companies to attract the strongest minds and company managers in this space.

Robotic Beta & Human Alpha & eventually entirely AI based

Within finance, we can expect vertical automation brought forward by digital advisory automation firms (such as Elinvar) to become endemic, considerably more so than is the case now. There are few financial sector firms that use investment processes which could be described as AI based, but this will (in time) come.

In time, more elaborate AI-based models will emerge, but as to their success, only time will tell. Some examples: usage of pattern recognition across trading patterns to exploit signals of insider trading and ‘follow them’ (see Venture Beat) or using virtual traders that ‘live or die’ based on their fund performance allowing the new traders to learn from ones who ‘died’ (see Euklid). These are not even a beginning to what will come and what could be created.

For some investors, the human interaction will still be necessary in the key stages of financial decision making. Therefore, it is likely client advisors will be assisted through AI applications developing tailored investment strategies for their clients.


Despite the above might not be the message in the mainstream media (and possibly a disappointment after reading so far into this), the topic of AI is largely inappropriate for the vast majority of firms. Most firms are not even remotely ready for the adoption and usage of advanced technologies like AI. The extent of the usage of Robotic Process Automation RPA is further proof that firms are resisting true end to end digitalization as such they would record and automate with manual legacy processes that should long ago have been removed and streamlined or entirely digitized.

AI without a Digital foundation is like fitting F1 tyres on a Donkey.

Niall Bellabarba, Director International

Therefore, as the demand for AI on a customer side with mainstream applications will increase, the pressure on businesses to ‘skip’ generations of tech will increase as well.

At Elinvar we see that the winners will be the ones that come to the conclusion that it is not realistic for them to develop and maintain a core competence of technology and therefore choose to focus on their own core competencies, while partnering with digital & technologically native ventures to help them effectively compete in 2020 and beyond.

Many software companies use APIs as key component of their business. But what does the abbreviation actually mean and what does it offer?

 API stands for Application Programming Interface and describes interfaces that can be used for the secure and fully automated exchange of data between two systems or partners. More precisely, it enables a program to be connected to another software system.
APIs are continually attracting attention through their use in numerous web-based applications. Interfaces belong to every system such as operating systems, databases, hardware or program libraries. These interfaces make it possible for external developers to develop programs for operating systems like iOS or Windows. With multiple services being integrated across platforms, APIs play a vital role in creating adaptable environments for developers and users alike. APIs enable systems to directly talk with each other and thus allow a fast and secure exchange of information.

Keep tabs on your information flow with APIs

Still, not all APIs can be used by everyone. They always come with documentation describing their various possibilities and conditions of use. Companies have different approaches to opening up their platforms, ranging from enabling only selected partners to access their APIs to all access approaches. Bigger examples for the latter alternative are Apple and Microsoft who opened their systems widely for other developers. Platforms like Elinvar, however, open their systems only to selected partners mostly those required for specific tasks performed within the platform, such as APIs with the custodian bank or identity verification platforms.

What do Netflix and digital asset management have in common? An intuitive, user-friendly interface

Most asset and wealth managers are well aware of the impact digitalization is having on their industry. One major issue is the private investors’ growing expectations of their portfolio management. Today, private investors measure their banking and investment products against the apps they use on their smartphone every day. Netflix, Twitter, and Airbnb clearly lead the way in terms of usability and design. This new expectation can be turned into an opportunity. Keeping up with the technological advancement by maintaining and improving financial expertise will be the key success factor for asset & wealth managers in the next years.

Staying up to date with the Elinvar platform

This is the playing field the Elinvar platform competes in – it enables asset & wealth managers in the digital age, by leveraging on their financial expertise and customer focus whilst providing a platform to digitalize their business. Elinvar is a state of the art platform, built on a microservice structure that communicates through APIs. Therefore, the platform itself consists of many different services that are working together, communicating through API’s. This makes every part of the platform flexible, which is why Elinvar can constantly adapt to changing technological and infrastructural needs.

A good example of the platform’s adaptability and use of APIs is the integration of the Elinvar platform with specific custodian banks which are used to safeguard the investor’s assets. People investing with an asset manager via the Elinvar platform do not need to check their bank account to get an overview of their assets. APIs connect to the custodian bank with Elinvar via which private investors have access to their assets under management – easy to use and highly individualized. This allows investing individuals to stay up to date on their assets and investment strategies by visiting just one portal. This connection also eases the work of the asset managers themselves: Orders that are triggered on the platformn are immediately checked and automatically sent to the custodian bank for execution.

Outstanding user experience and regulatory compliance – from a single source

APIs not only ensure the integration of services into the Elinvar platform, they also lay the foundation for a seamless user experience. When it comes to their investment, the individualized Elinvar platform is the go-to point for the private investor. Saving time and the need to check several accounts, Elinvar offers an optimal and adaptable user experience.

Elinvar is fully BaFin-licensed and therefore guarantees for the regulatory compliance of its platform – including API integration. This reduces the bureaucratic effort of the asset & wealth manager, creating freedom and space to concentrate on their core expertise: creating value for their customers.