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The Next Big Think: Marc Schillinger

Interview: Marc Schillinger, CEO eCollect AG for the series “Next big think”

Jan. 20, 2021

Marc Schillinger has been working in the receivables management industry for more than 20 years. Before he stepped in as a CEO and Co-Founder of eCollect, he spent five years on the board of the Lowell Group — the second largest debt collection company in Europe — with a turnover of around one billion euros. For over 15 years at Lowell, Marc was responsible for sales, business and corporate development in eleven countries. During his time, the company was sold several times and he worked with various private equity companies, all of which he still values ​​very much.

The lack of willingness to change in the corporate world has prompted Marc to form what he calls an “industry challenger” in the face of eCollect. The startup implements receivables management processes in a modern and digital way in order to improve the customer journey and create more value.

How have you decided to join eCollect and what is it so special about your startup?

I have felt the need to be an entrepreneur again, which inspired me to dive deep into the tech scene. The reason why I ended up at eCollect is that my corporate customers used to ask me for a one-stop-shop solution for the holistic receivable management process. Such solution hadn’t existed at that time and that made me look at FinTech companies. eCollect offered the best prerequisites for my vision in the tech area and we quickly came to an agreement, both professionally and personally.

We are headquartered in Switzerland, with operational hubs in Essen, Germany, where the multilingual call center is situated and Sofia, Bulgaria, where our tech hub is located. We are currently working with around 45 employees.

When I started at eCollect, I reorganized the organization and the platform. eCollect used to be a digital debt collection company with small online customers. In order to launch a modern and digital value chain for international corporations of all verticals, we have converted and further developed the Tech Eco-System into an end-to-end Receivables Management Platform. The company then specialized in tailor-made AI and machine learning communication with debtors and started offering service components that cover the whole receivables management via one ultra-modern AI platform: from invoice creation, over dunning, incl. multiple payment methods to pre-legal and legal collection. The platform processes the service modules in different countries, in local currencies and multi-jurisdictional across boarders.

This process currently exists in whole Europe this is our unique selling point (USP). There are providers who are active in debtor management and there are providers who are spcialized in classic collection. But there is no other provider who maps the entire process chain on an all-in-one cross-border platform.

We offer our services internationally and already process invoices, reminders and debt collection cases for our clients in more than 30 countries, with an option for white-label collection with our client’s branding.

Our next step is to make the platform blockchain-compatible. In the next six to twelve months, we want to address the topics of tokenisation and smart contracts in the area of ​​collection.

What significance does Artificial Intelligence have for eCollect?

I come from the receivable management area and this was always my main focus. When we include a debt collection portfolio, the AI ​​selects the individual process steps for the respective debtor. For example, if we have successfully led a customer through the debt collection process, let’s say for Marc Schillinger, there is a special domain Marc Schillinger — it’s called event-based processing.

In the traditional industry, most of the process still goes through calls and letters. In contrast to that, we are work digitally and in a modern way. We select in advance what is the best strategy for each debtor. Our AI approach extremelly reduces process costs and the KPI “cost-to-collect ratio”. We select the the communication channels (email, SMS, WhatsApp, Viber, letter or call) and the stylistic tools (jargon, colors, formulations) according to the customer. For example, we address a person from Generation Z differently than a Baby Boomer. Even though artificial intelligence is highly involved in the service, we will never want to replace the human factor in the collection. Therefore, as digital frontrunners, we have an in-house call center where we communicate with debtors in seven languages. We try to make it as easy as possible for the debtor to contact to communicate with us. Debtors can also pay their bills, reminders and claims conveniently, as we offer more than 35 international payment methods via PayLink, PayQR codes and a PayPage. Another unique selling point of eCollect is that, in addition to the common payment methods, we also offer WeChatPay, AliPay and new types of crypto currencies via smart contracts.

We are currently defining segments for a large part of the portfolio and the aim is for the debtors to be controlled individually and automatically through the process. If the system recognises that the collection strategy was correct, it should also apply it to a new debtor with similar data points. Each debtor has around 40 data points, such as: date of birth, origin of the claim, address, etc. An individual collection strategy for the respective debtor should then be created from these data points.

Another collection strategy we apply using AI is the so-called payment forecast. When we get a portfolio from a client, we can quickly and accurately analyze how many of the debtors will pay and during which stage of the collection. Statistics show that an average of 74 percent of debtors at eCollect pay during pre-legal collection and 18 percent require legal action. With the help of AI, we can tell which debtor group we should tackle first and where we will have the best chances to collect the outstanding claim.

Which challenges are currently being worked on at eCollect in the field of AI?

We are working on risk analytics, context-based routing and autonomous communication.

We will soon also be purchasing debt portfolios. Currently, we are mainly focused on collection until we master our risk and data analysis capabilities. I have already brought up the topic of context-based routing: this process individually guides debtors through the process and decides on wether a machine is able to answer an email independently or the case has to be forwarded to an agent.

That brings us to the third topic: automated communication.

We combine AI-based and human-led communication. Our USP is that we can smoothly map the transition and thus gradually increase the efficiency and quality of manual communication. This allows us as a company to grow rapidly and strongly and to keep our core team efficient.

How is eCollect’s solution different from the competition?

Our solution works as a one-stop-shop solution for different service areas—all on one platform and cross-boarder. In this way, we manage the holistic receivables management process for our clients in a fully digitalised way, in order to successfully design the customer journey for all parties involved. We are committed to create a successful customer journey so that the debtor can remain a consumer of our client. Here we use AI-supported solutions and this is one of our greatest USPs.

What advice do you have for medium-sized companies about the use of AI?

As our CTO often says: “The risk of getting burned by AI is high for medium-sized companies.” AI is a complex technology that requires experience and expert knowledge. If you want to use AI, you should deal extensively with it and build teams of experts. This is too time-consuming and costly for many medium-sized companies, and in my view AI experts are difficult to hire, since they mostly either want to work in a start-up and FinTech environment or in large corporations. Based on my experience, medium-sized companies eventually drop out of the race. For example, mid-sized debt collection companies do not really address the capabilities of AI. We are facing a consolidation on the German debt collection market, which we have already seen in the UK and Scandinavia. In the end, the big, financially strong players and the technology-driven companies will divide the market among themselves.

What does eCollect want to achieve with AI?

eCollect will grow significantly in the area of ​​receivable management in the next few years. To realize this growth, it is necessary to scale employees accordingly. AI plays an essential role here and it is our goal to use it to improve automation. Routine tasks will be completely eliminated and the employees will primarily deal with special cases.

What is your fascination with AI?

In many cases we have found that machines can make better decisions and fewer mistakes than humans. If you have certain data points and have repeated the same process 20,000 times, it is highly likely that the machine will be more accurate at the end of the day.

In addition, AI systems have better control over their emotionsand are very successful at formulations and tonality, which makes debtors much more willing to pay. Furthermore, unlike humans, AI ​​does not get bored while executing repetitive tasks and every debtor receives the same degree of attention. I think that’s why it’s so interesting for our industry and that’s why we’re also investing in AI.

Originally posted on fintechtube.

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