Increasing the probability of payment claims in the debt collection industry for coeo Incasso
An all too common scenario for individuals or corporations: products or services are being purchased or rented, but invoices go unpaid for many reasons. The majority of these cases are settled after a simple payment reminder, but a large portion remains unpaid. An uncomfortable situation for all parties. Especially aggravating to the debtor, for whom uncertainty over future payments starts to build. Leading them to the last-ditch effort for many corporations: hiring a debt collection agency.
In coeo Incasso, we find one of the most modern and technologically innovative debt collection agencies right in front of us. At the center of all their actions is one central aim: finding an amicable solution for everyone.
Seeing significant growth in recent years, coeo Incasso is facing a high increase in incoming claims. Posing an immense challenge for the whole organization to validate and process every single one, they saw potential for artificial intelligence and machine learning early on.
‘Debt collection optimization’ and the challenges for coeo
Historically, the debt collection process has been a rather “manual” and time-consuming process. Validating and following up on every claim, even those with a low probability of success, is not possible anymore. To free time and focus on claims to handle all claims properly, coeo looked into a first use case: prioritizing claims and automating actions. Based on the ‘likelihood-to-pay’ in relation to days of outstanding payments, a machine learning model was developed.
However, as many companies experience, simply deciding on and building a model does not guarantee actual usage. A key business process would be (partly) replaced by automated decisions and machine learning still presents an unknown element to the daily work, transparency, and trust among employees were essential. In addition, to ensure legal accountability, every prediciton needed to be reproducible at any time. A case perfectly fitter to Deeploy’s mission to ensure explainability, accountability, and manageability for machine learning.
Use case ‘Debt collection optimization’
- Ambition: ensuring that the largest possible share of outstanding payments is settled
- Situation: evaluation of claims, estimation of likelihood of payments per customer and resource prioritization (e.g. people, time) conducted manually
- Models: likelihood-to-pay in relation to days of outstanding payments resulting in automatically triggered measures
- Solutions needed to integrate machine learning into business processes to level fast growth while simultaneously reducing high manual effort
- Limited link and transparency between business units and machine learning applications
- Desire to reproduce predictions at any time to evaluate the taken measures
The solution: enabling human-machine interaction and accountability through Deeploy
As a start, Deeploy provided Coeo with the platform to easily deploy and update their models without facing any costly downtimes. But even more importantly was another Deeploy feature: the human-feedback loop. Based on customized explainers, Deeploy is able to give Coeo’s business and legal experts detailed insights on each prediction made by the model. Building on those insights, Deeploy creates full transparency and explainability while providing the opportunity to evaluate and provide feedback on the model logic. By involving all relevant stakeholders and providing a chance for feedback, Deeploy creates a perfect feedback loop. Placing high emphasis on accountability and reproducibility, Deeploy allows Coeo to constantly log and trace every change and prediction made by a model. Creating clear audit trails. In that way, Coeo is able to achieve full documentation and accountability for the decisions made by their models. By establishing trust and transparency towards ML models, Coeo was able to significantly free the time of their employees. Time that can now be used to focus on claims that need the involvement to generate payouts. Supporting their fast expansion and growth through AI and ML.
Realized benefits through Deeploy
Coeo trusts Deeploy as a tool to establish transparency and explainability for models throughout their organization, while simultaneously ensuring accountability and manageability. Building the base for Coeo’s future growth!
- Version control of historic models & predictions
- Automated audit trails
- Customized explainers for every prediction
- Human-feedback loop for business experts
“Deeploy has enabled us to respond to the customer’s situation at the debtor level and to take targeted personal actions so that we can put empathy in the way we communicate with them. This is an important aspect for our clients in the context of customer retention.” – coeo Incasso
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