  Predicting invoice payment is valuable in multiple industries and supports
decision-making processes in most financial workflows. However, the challenge
in this realm involves dealing with complex data and the lack of data related
to decisions-making processes not registered in the accounts receivable system.
This work presents a prototype developed as a solution devised during a
partnership with a multinational bank to support collectors in predicting
invoices payment. The proposed prototype reached up to 77\% of accuracy, which
improved the prioritization of customers and supported the daily work of
collectors. With the presented results, one expects to support researchers
dealing with the problem of invoice payment prediction to get insights and
examples of how to tackle issues present in real data.
