How is Artificial Intelligence (AI) used in debt collection? In this interview, Dmitry Sharkov, CTO at PAIR Finance, and Maxime Kaniewicz, Team Lead Data Science at PAIR Finance answer questions about the key technology.
How is AI changing the debt collection industry?
Dmitry Sharkov: At PAIR Finance, we have been working with AI in debt collection since 2016 and have done pioneering work in this area. The keyword here is “personalisation”—making the debt collection process customer-focused and efficient, while sustainably improving the customer journey.
We are trying to understand every consumer’s personal situation within an analysis of static data and dynamic characteristics. What social environment does the person live in, what is their purchasing behaviour and financial scoring, when do they visit our payment page, have they actively contacted us, and if so, in what way?
By doing this, we find the best way for our consumers to close their debts as soon as possible. We do this based on our experience with people in similar situations. Without AI, it would not be possible to decide as precisely and effectively how and when to contact a person for the best possible outcome for both parties.
How do you strike a balance between AI and human expertise in debt collection? What skills are critical for a digital debt collection company in the age of AI?
Maxime Kaniewicz: AI is particularly relevant and powerful to solve repetitive problems that are clearly defined with a certain input (the data which the algorithm receives) and output (the solution which is being delivered by the algorithm).
In digital debt collection, this means for instance that whenever a message needs to be sent, an AI model can determine exactly which channel or which message template would be the most effective to encourage the consumer to repay their debt. This situation typically occurs thousands of times per day and is a well-defined task.
Still, human expertise is absolutely essential to control the context of the message: Have we included all the information we legally need? Is the message clear to our consumers? Do the company’s goals align with those of AI optimisation?
Mastering the business context is key to using AI in debt collection optimally. This requires AI experts and business owners to develop a strong understanding of each other’s work.
How can a debt collection company ensure its AI models are transparent and fair?
Dmitry Sharkov: Training data always needs to be reliable and unbiased. We use different kinds of cases for different kinds of training methods because, for instance, a model trained on a data set from online retail would give bad predictions for debt cases with electricity bills and vice versa.
The PAIR Finance team always investigates first, performing analysis and checking statistics and applying the outcome of this, before we even start training AI models. This amount of manual human input is very important and ensures that our models and the data which we use are unbiased and trustworthy.
Data can sometimes reveal very sensitive details about a person. We strictly adhere to all legal requirements, ensuring that decisions are always fair and non-discriminatory. Therefore, we only use and request data that is truly necessary.
How do you use AI in debt collection for the benefit of all stakeholders? And what role do data protection, compliance and anti-discrimination play in this?
Maxime Kaniewicz: We use AI to personalise and optimise the debt collection experience for each consumer. It is imperative that these tools are not discriminatory, for instance based on the identity of the consumer. The best way to prevent this is to eliminate the possibility of such discrimination at the data source.
For example, we do not store information about the consumers that should not be used in the collection process. We train machine learning models on data sets that are anonymised and stripped of any data that could be misused, even inadvertently.
Data protection is of the utmost importance to us. We ensure full compliance with all legal requirements, such as the General Data Protection Regulation (GDPR) and the German Federal Data Protection Act (BDSG). Additionally, we adhere to the European AI Act, which has been in effect since 1 August 2024. Our goal is to deploy innovative technologies responsibly, maintaining maximum transparency and security for consumers.
What will digital debt collection of the future look like as AI continues to advance?
Dmitry Sharkov: I think the future of the industry could be to provide all consumers with a “real-time virtual communication assistant” that works not only on the website but also via SMS, email, video call or WhatsApp and understands human emotions.
Such an assistant could use sentiment analysis to provide targeted, active reminders in real time and respond more individually to requests than a conventional chatbot, because it determines consumers’ concerns, opinions or moods from text, voice or video data.
The development in this field is rapid and there are first tests that show that AI can perceive the environment and then realistically perform an action. In the future, consumers could ask the virtual assistant questions around the clock via their preferred communication channel and even receive tips about their finances.
However, it remains crucial to consider ethical concerns and not overlook the human element. Advanced technologies must always be complemented by the expertise and empathy of our support team to ensure that consumers receive personal and human support whenever they need it.
AI is part of your daily work at PAIR Finance, but do you also use it in your private lives?
Maxime Kaniewicz: Of course! Most of us are using AI products all the time without even noticing it because AI is seamlessly integrated into so many products or services that we use regularly. Music recommendation is probably the AI application that has had the strongest impact on my private life, as it allowed me to considerably expand my musical interests in the last years.
I would estimate that about 30% of the music that I listened to in the last weeks was recommended to me automatically, which every now and then leads to fantastic discoveries which I may not have made on my own. For example, I recently discovered the band “Traveling Wilburys” thanks to such recommendations, which I definitely recommend in return as well!
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Last updated: 29 January 2025, by Jana Caterina Erhardt
