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 promise.

We realise your outstanding claims efficiently and without strain on your customer relation!