.. debt collection may not sound like the sexiest industry for founders to build startups.
However, if receivables management is not done properly, dire consequences would usually follow – for both creditors and consumers. Did you know that in 2020, according to an Atradius report, 50% of B2B sales in Eastern Europe have been made on credit?
With that said, late payments account for 1 of 4 bankruptcies in the EU – without liquidity and predictable cash flows, one cannot really operate a company and those with limited access to finance (e.g. SMEs and startups) are most affected. As per numbers from the European Commission, only 40% of businesses in the EU are paid on time. Globally, €1.2T (trillion) of excess working capital is tied up on balance sheets, PwC states.
Covid-19 has accelerated these issues across several dimensions. On the one hand, sales on credit have increased further as firms have been trying to close deals, stay competitive, and in general provide support and flexibility for their customers. At the same time, in Eastern Europe, the number of invoices paid on time has decreased by 17%, compared to pre-pandemic times. In what may ultimately cause a domino effect, the usual counter strategy for companies in the region has been to delay payments to their own suppliers.
As with every crisis, all these problems also offer an opportunity for disruptive fintech startups. Especially, given that EOS survey shows that less than 20% of companies in Europe have fully digitalized their dunning systems (in a nutshell, dunning is the process you have in order to deal with customers’ failed payments).
This is just the tip of the iceberg. Many creditors are still using outdated communication methods such as letters via the post or phone calls. To a large extent, data is still processed in an error-prone and time-consuming manual manner. Traditional collection service providers are usually constrained to a single location and offer support only during office hours. Last but not least, ethical and legal practices are not always followed, sometimes on purpose, others because of the lack of knowledge.
So, how can technology help optimize accounts receivables (AR)? What opportunities can automation unlock for all stakeholders in the complex debt collection equation? Who are the players providing the key innovations in the space? Hint: one of them, eCollect is being developed in Sofia, Bulgaria. The answers to these and more questions – in our latest deep-dive dedicated to fintech innovation in Southeast Europe.
When it comes to innovation, the debt collection industry is certainly behind other segments in the financial sector – with process efficiency and consideration for the customer experience still missing for the most part. If we consider the number of potential users across multiple industries as well as the frequency and intensity of the problem with delayed payments, there is already a huge market for debt collection digitalization. According to Allied Market Research, in 2019, debt collection software generated $3.1B in revenue globally and close to $1B in Europe. Both numbers are projected to at least double by 2026.
In fintech in general, there has been a trend towards the integration of separate vertical solutions into horizontal ones (Nobody wants to use 15 apps, if you can do it all with one). A great local example is Bulgarian startup Payhawk, which puts together enterprise payment, expense, and accounting systems in one single stack. The company, part of Eleven Ventures portfolio, recently raised a $20M Series A round.
The same holds true for account receivables. If invoicing, dunning, legal and payment processing can be integrated into one scalable automated platform, this means improvements in debt recovery times and process costs – by a double-digit factor. Such improvement in productivity directly supports business income.
Recent advances in Machine Learning have enabled further optimization of the process, making the use of data from various sources much easier. For example, customer experience is one of the biggest areas for improvement in debt collection. In today’s highly competitive business landscape – customer happiness makes the difference between success and failure. Research shows that about 50% of consumers with late payments had only a short-term financial obstacle or just forgot to pay. Of course, an AI chatbot can not replace human negotiators but it can help them understand customers and send appropriate personalized communication – faster and cheaper – at the right time and channel.
AI-driven segmentation can already classify debtors in different buckets, so businesses can devise different strategies to collect their money. If you can easily see that these 2000 people have a trustworthy history and are likely to pay if given an alternative, why not provide them with a more flexible payment plan?
Predictive analytics can help businesses optimize their debt collection decisions and track performance. With actionable insights on borrowers’ profiles, process costs, the number of recovered debts per approach, and the types of payments that are still pending, one is better equipped to remove bottlenecks in the process.
On the legal side, there are usually well-defined requirements in place (which do change from time to time). If they’re incorporated in an automated accounts receivables system, this would translate to a lower necessity for human interpretation (and error) and lower legal costs overall. With the boom of international transactions, AI also presents an option for cross-border compliance.
The EU standard on e-invoicing has paved the way for machine-readable documents, enabling automated exchanges between all stakeholders in the process.
Taking into account the payment and revenue challenges that the Covid-19 pandemic brought to business all over the world, it comes at no surprise that 45% of the total value of B2B invoices in SEE left unpaid at the time they were due, which marks a striking 88% increase from the previous year.
With each industry experiencing a different challenge as a result of the economic crisis, the deployment of all-in-one AR management solutions is recognized as an efficient and effective way to optimize cash flows by CFOs and CEOs from various sectors. AI-powered accounts receivables platforms are especially useful in industries which are known for struggling to get paid in time. According to analysis by the financial information company Sageworks, companies in enterprise management, automotive equipment rental and leasing sectors, and health care centers are known for being in the top ten for slow accounts receivable collections with respectively 125, 104, and 99 accounts receivable days.
There are both industry-specific ways in which businesses can minimize their late debt collections and some universal solutions which are connected to customization, omni-channel communication, enhanced relationships and brand loyalty, and improved workflows. Here is how automated debt collection softwares alleviate cash flow and liquidity pain points across the different industries:
Easy access to accurate data, enhanced end-to-end visibility of information, and improved working capital are only some of the “side effects” resulting from the use of smart and next-generation AR platforms. With the digitization and automation of the accounts receivable processes, companies can significantly decrease the manual and repetitive work associated with payment processing, deduction handling, credit risk assessment, and collection management. Let’s now look at how automated AR platforms positively impact some of the main elements in the debts collection process – invoicing, cash application, dunning, and collections management.
Starting with invoicing, intelligent AR platforms allow the process of initiating and distributing the invoices to be done completely autonomously. Moreover, the distribution of invoices can be automatically performed across borders, which eliminates the need of international debtors to implement separate solutions for the different countries they serve. When it comes to the process of cash application, during which financial specialists match the incoming payments with existing customer data, automated debt collection solutions can spare employees hours of data keying and allow them to use their time for monitoring and analyzing the data. This is good news for the companies’ financial decision-makers as they are provided with data-based insights that help them prioritize invoices based on their payment probability and value realization. AI account receivables solutions can not only help SMEs with aggregating and correcting data and matching the accounts receivable processes, but also with extracting data from emails and web payment portals.
Another major advantage that automated AR platforms bring is connected to the so called “dunning” processes, which deal with the initiation and distribution of payment reminders. Automation and data analytics allow businesses to personalize the relationship with their clients and send them reminders at the right time and via the right communication channels. This is made possible by the capacity of machine learning algorithms to retrieve and analyze historical customer data, extract insights on user’s behavior and on the cash flow of the company. Next, in the AR process pipeline, the historical data can be used to make predictions about the expected payment days on invoices and working capital, and even suggest companies what types of personalized incentives they can offer to customers to speed up the payment of the receivables. Put in other words, unlike traditional accounts receivables collections, which are reactive and done after the invoice is due, the AI-powered AR strategies are proactive as they are backed not only by market trends but also by the historic data of customers.
According to PwC research, around 17% of the credit sales are locked in accounts receivables and enabling businesses to collect their debts quicker, AR automations ensure that the days sales outstanding (DSO) are significantly reduced and the business dispose of more working capital to power it’s day-to-day operation and have more opportunities to invest. DSOs are a measure of how long it takes a business to collect its cash from customers and the implications of reducing DSOs is particularly important for both B2B and B2C companies in the SEE since it is reported that Mediterranean countries are the ones with the worst habits of paying late.
And last, but certainly not least, automated AR processes can become a main source of competitive advantage for businesses in the debt collections industry as it makes the UX times better. A McKinsey survey points at the misalignment between the communication strategies and channels used by companies and the preferred communication methods by their delinquent customers, and naturally this has a significant impact on the outcome of the debt collection process.
As the infographic above shows, the majority of businesses still use traditional last-contact channels such as phone calls, letters, and voicemails despite the fact that a large proportion of customers who have overdue accounts prefer a “digital-first” approach. Moreover, it appears that with the use of AR smart platform, businesses are better able to avoid the mismatch between the customers preferences and their communication strategies and increase the likelihood of their delinquents paying off debts. The same survey by McKinsey highlights that by using phone calls companies deteriorate their chance of receiving a full repayment by 47%, while by using mobile reminders and push notifications, they increase the chance of getting both a partial and full repayment by 44%.
Before diving deep into the regional trends in accounts receivables, let’s first see who are the first -movers around the world and what developments they are introducing. Peeking from across the ocean, the San Francisco-based TrueAccord helps US companies to improve their debt collections by using ML that adapts to consumer behavior and comes with automated and personalized communication to recover billions of dollars of locked revenue. Again in the USA, Attunely uses ML to analyze the accounts of debtors, matches them with various events and monitors for anomalies to develop compliance checks which are data-based. A solution similar to that of TrueAccord is developed by the Australian startup inDebted, which uses real-time data and behavior analytics to come up with the best channel to reach its lenders.
In the European fintech scene, AR tech startups such as the German receivables management platform with AI-based payment services collectAI, which is an affiliate company of the Otto Group – one of the country’s e-commerce giants, show the value-added from corporate innovation in the sphere. Another German digital debt collecting startup troy combines fintech with CRM to recover debts and ensure customer retention and satisfaction. Pair Finance, also founded in Germany, uses a sort of ML algorithm called Reinforcement Learning, which learns how to repeat and reuse successful strategies and tactics in debt collection. The algorithm extracts and analyzes customers characteristics both before and during the reminder process, which makes it possible for the communication to be adjusted according to the reactions of the customers until it finally reaches optimal levels. One more Western European innovator is the London-based platform for domestic and international accounts receivable management Collection Hub, which allows companies to compare quotes from debt collection agencies to help them save costs and time and eliminate bureaucratic processes. In the interactive map below, you can explore more about the startups transforming the AR fintech spaces both in the SEE and in Western Europe.
To explore what innovations in the accounts receivables space regional startups are introducing, The Recursive team talked with Marc Schillinger, co-founder and CEO of the AI end-to-end debt collection platform eCollect. The startup is part of the second season of the Visa Innovation Program for SEE fintech innovators that is managed by the Bulgarian early-stage venture capital firm Eleven Ventures.
The Recursive: What is actually the biggest problem eCollect is solving for its customers? How did you find it, what’s the story behind it, and how did you come up with the idea?
Marc Schillinger: eCollect is turning chaotic receivables management into a sleek customer experience. We have developed an all-in-one solution covering the entire receivables management process: from invoice creation and distribution, over dunning (payment reminders) to pre-legal debt collection and legal procedures including international payment options.
What motivated me to shape eCollect as the end-to-end platform and industry disrupter it is now, was the lack of willingness of the debt collection corporates to adapt to the needs and demands of the clients. Being in the financial sector for over 20 years now, before I stepped in as a CEO and co-founder of eCollect, I have spent five years at the Executive Board of the Lowell Group where I was responsible for sales and business development in 11 countries. Back then my corporate clients used to ask me for a one-stop-shop holistic solution for their receivables management process but such a solution didn’t exist. This motivated me to become an entrepreneur and search for a more innovative approach to how receivables are handled for businesses. At that point, I saw great potential for boosting receivables management with the power of AI and ML technology.
Currently, eCollect is headquartered in Switzerland, with operating hubs in Sofia, Bulgaria and Essen, Germany, and has 45 employees and a multi- language operational team for our pan-European operations. One of the strongest unique selling propositions of eCollect right now is that it is able to assist large corporations of all verticals and make use of AI and MI algorithms for better and automated dispute management with the debtors. Furthermore, the platform is unique in combining debtor management with classic collection and it does so across borders, in the local currencies, and with the customers’ preferred payment method, including digital currencies, which is our latest addition to the payment methods portfolio. We already process invoices, reminders, and collection in over 30 countries for our clients with the option for white-label service processing, which makes it a frontrunner in the pan-European market, and we are planning to expand to further contents in the near future.
Where is eCollect in May 2021 as a stage in its development? What are your top 3 biggest business achievements so far and what are the next goals and priorities for the company?
Today eCollect is the leading European platform for receivables management and we are delighted to have over 3000 corporate clients and more than 450 000 customers. There aren’t other providers who map the entire process chain on a cross-border platform and we are proud to be able to revolutionize and simplify receivables management for our clients and customers. One of your biggest achievements so far is definitely the transition of eCollect from a traditional digital debt collection company to an ultra-modern AI-powered end-to-end receivables management platform, offering a fully automated solution and multiple payment-related services. Moreover, in 2020, we have won one of the biggest European tenders in the mobility sector and have successfully expanded internationally.
Second, being a fully bootstrapped company, we managed to achieve healthy growth and could successfully onboard great talents at the company. Last but not least, the past year brought us multiple awards and distinctions, which by itself is great recognition from experts, industry. To name a few, we were selected among the top 10 FinTech startups in Switzerland and appointed part of the Swiss National Startup Team by Venturelab and Swissnex China. Furthermore, we won first place at the Tech Rocketship Awards in the category Digital Economy & Security organized by the English Department for International Trade (DIT), and second place in Europe by the world’s largest startup contest Unicorn Pitches.
As for future developments, we are working on improving our context-based routing – this individually guides debtors through the process and decides on whether a machine is able to answer an email independently or the case has to be forwarded to an agent. In that way, routine tasks will be completely eliminated with the power of AI. We are also working on new blockchain technologies, smart contracts, and the service of purchasing debt portfolios in the future.
From your perspective, in what direction is the debt collection industry going? What are the main emerging trends and your long-term vision for the role of eCollect in the sector?
As in every industry, only those who follow the recent trends and developments thrive and survive. I see the future of receivables management digitized and automated with a single client API onboarding serving multi-national territories. I am fully convinced that at eCollect, we will continue to show good practices for future innovators in the receivables and debt collection industry. Receivable management applications need to become more user-friendly and include features such as chatbots, UX dashboards for individual reporting and controlling functions.
Furthermore, receivables management companies will have to make their practices more sustainable and cut on unnecessary paper consumption for letters and administrative paperwork. On average, a tree produces 8,333 sheets of paper. Imagine how many trees are destroyed for an average of 300.000 customers who receive around 2-5 letters before paying debt off. We avoid that by running the whole process fully digital and only send out letters in exceptions.
What’s the role of AI in your product? What does it help you achieve, what are the advantages of the AI-based approach?
The use of AI is crucial for the innovation of the receivables management process and it is the biggest differentiator between traditional debt collection companies and more sophisticated receivables management solutions. AI helps us automate the receivables process by selecting the individual journey for each debtor with event-based processing. In our industry, most of the collection process is still executed by dreadful calls and letters. We are standing against those stressful, time-consuming, and inefficient approaches and choose to focus on digital communication and alternative channels such as SMS, Viber, and WhatsApp.
With the help of AI, the system creates a tailor-made customer journey and takes into account factors such as age, sex, demographics, and occupation. For example, we address a person from Generation Z differently than a Baby Boomer and this individual approach drastically reduces DSO and improves collection rate by building trust with the customer. Another advantage of the AI approach is our ability to create a payment forecast for our clients. As soon as we receive a portfolio from a creditor, we can quickly and accurately analyze how many of the debtors will pay and during which stage of the collection process.
Our internal statistics show that an average of 78 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 with the suitable dispute strategy. Our goal is to completely automate repetitive tasks and use AI for more balanced and bias-free communication. I believe, we can agree on the fact that if the same process is repeated 20,000 times, it is highly likely that the machine will make fewer mistakes and will be more accurate at the end of the day. At eCollect, we value people the most and therefore we employ AI to do all repetitive tasks so that we can give our clients an exquisite customer experience and our team can focus on strategic and creative solutions.
Can you share some examples of how the Visa Innovation Program helped you develop/grow eCollect?
The greatest benefits from the program were the exceptional business advisor we got the privilege to interact with as well as the innovation ecosystem we became part of. Visa is one of the most respected international financial services and eCollect is highly dependent on it in the most positive sense.
With the Covid-19 pandemic resulting in an all-time high debt and late repayments, businesses and lenders are starting to rethink their capabilities to handle debt. In order to address the prolonged credit cycles, businesses are turning to digital solutions to boost their resilience.
Therefore, it is not a surprise that the global market for debt collection software is expected to reach some $6,8B by 2027. Nevertheless, McKinsey research shows that as of now more businesses pursue traditional debt collection strategies such as outbound phone calls and letters, rather than digital multichannel strategies including email, text message, and online chats. On the other hand, the same research uncovers that the customers who have “digital-first” preferences largely outnumber the ones who choose the traditional debt collection communication channels. This not only means that there is a huge opportunity for businesses to boost their competitiveness by becoming a digital AR first-mover, but also that they would be able to meet the needs of a large customer base.
So, what are the musts in AR that would enable businesses to thrive in the digital age? Having a strong data foundation and applying data analytics, as well as deploying predictive analysis for improved inventory management and customer collection processes is only the beginning. According to an Experian report in 2021, the global trends in debt collection will be characterized by the sustained focus on automation with AI-powered customer communication gaining increasing traction and importance. At the same time, it is expected we will see a surge in the use of alternative communication methods and self-serving options, which would eliminate the need for debt collection departments to deal with high-volume tasks such as making repayments. The Covid-19 pandemic has accelerated the adoption of self-serving channels and a report by Boston Consulting Group reveals that the lockdown has caused an average of a 20% increase in self-service channels globally. Therefore, to take advantage of this trend, businesses should carefully assess the value-added form using self-serving portals. Reconsidering the way collection departments traditionally perform high-volume, time-consuming tasks of low complexity and embracing alternative methods in which customers resolve issues themselves can be the answer that saves companies days and weeks of repetitive work as long as there is regular customer feedback.
When it comes to changes and trends in consumer behavior, according to McKinsey the impact of Covid-19 on European customers has been that the average digital adoption levels rocketed to 94% during the lockdown, and the digital gap between countries has significantly shrunken. Moreover, the same research uncovers that 70% of the European consumers will continue using digital services with the same frequency. The implication of all these statistics for debt collection is that companies need to provide their clients with methods for digital managing, repayment, and outstanding debt tracking in order not to make it more difficult for customers to pay off their debts and, thus, more likely for them to dispose of less working capital.
Keeping in mind that more and more customers and businesses will fall into debt, it is important that companies focus on consumer verification by ensuring that their data is accurate and up-to-date. By verifying each customer, businesses would reduce the associated risks, and minimize the chances of fraud and liability charges. Furthermore, verifying consumers brings additional benefits associated with the ability of companies to trace the action of their customers and ensure legal compliance. Therefore, it is reasonable to expect that the upcoming trends in accounts receivables will have a lot to do with intent identification and compliance checking, which would include tracking calls with ML speech-to-text technologies and identifying agents’ misbehavior with customers.
As the inability of businesses to uncover which accounts are likely to default is pointed to as one of the main reasons for overdue accounts and bad debts, data analytics and algorithms that check for early warning signals will be increasingly gaining traction. So far traditional early detection systems have relied on income recognition and credit quality, but next-generation warning systems will deploy AI and use publicly accessible data on social activity, news on borrowers, and traditional financial information to minimize the likelihood for delinquent accounts. This will be made possible with ML technologies such as Natural Language Processing (NLP), clustering, and predictive analytics as well as by models such as ML-based recovery chance predictors, which prioritize and deprioritize accounts according to the probability of loan recovery.