Our technology is based on Reinforcement Learning, a kind of Machine Learning. Our algorithm learns to repeat successful strategies and intensify actions which have a positive influence on the desired result.

Data Science.

The algorithm processes various individual characteristics of your defaulting customer which are extracted both before and during the interactions in the reminder process. Various behavioural patterns are identified based on these characteristics and the typology is specified.

Customer data from agents
Your customer data gives an insight into consumer behaviour and indications of systematic behaviour patterns, which can be used to determine communications channels.
Data from third parties
Data from credit agencies, credit institutions and market data help obtain a better idea about the solvency of your defaulting customer. This allows specific individual potential solutions to be offered.
Digital data
Digital data obtained from social media or as part of the e-mail authentication process provides additional information about the socioeconomic status of your customer and is also used to tailor communications during the reminder process.
Behavioural data
Behavioural data such as availability, type of reaction or reaction speed provides information about the willingness of your customer to pay and show whether the measures in the reminder process are appropriate.
+ 80 different multidimensional characteristics


Optimum contact to the customer is determined based on findings from behavioural research. During the interaction, the algorithm adjusts the communication individually based on the customer’s reaction until a final agreement is reached with your customer.

  1. Channel
  2. Timing
  3. Possible solutions
  4. Frequency
  5. Tonality
  6. Stylistic tools

Our partners.

“For me, PAIR Finance is a digital champion in the collection industry, with its approach and its technology. It is based on recognising and correctly assessing the current, individual situation of the defaulting customer. By focussing on a digital, behaviour-driven approach, PAIR Finance makes contact quicker, which is a significant success factor in receivables management. By using digital data and its own AI technology, PAIR Finance can also offer the defaulting customer tailored solutions, thus saving both defaulting customers and their creditors from long, dragged-out collection processes. This aspect is proven to increase the recovery rate and avoids unnecessary and expensive customer losses.

Michael Weinreich

CEO Transcom & former CEO Arvato Financial Services

“With its solution, PAIR Finance has found a practical, technical application for artificial intelligence. Moving away from standardised, traditional reminders towards individual, digital communication with automated processing, which has been proven to promise more success in recovering outstanding debts. The rapid digitalisation of the financial world makes the innovative approach of PAIR Finance to receivables management indispensable.

Herbert Henzler

Former European Chairman of McKinsey & Company

“In my opinion, PAIR Finance has the potential for a really innovative product. Interventions to increase skill and transparency put debtors in a position to handle their finances on a more sustainable basis. This is supported by a debtor management model based on the latest psychological and statistical findings. I believe that this makes PAIR Finance the innovation leader in debtor management, promoting the economic development of its business partners in the medium to long term based on positive, respectful handling of their customers.”

Prof. Gerd Gigerenzer

Director of the “Adaptive Behaviour & Cognition” department of the Max. Planck Institute