Bookkeeping has the difficult task of estimating bank accounts liquidity several weeks in advance. Influenced by incoming customer payments, rent, wages, tax obligations, and other bills, the question is whether machine learning can simplify this process.
We worked with the customer to find influencing variables and engineered features that provide a correlation with the individual parts of a liquidity analysis. This allowed us to apply time series prediction methods to predict for example, when posted invoices will get payed or how high the tax liability is in the next months.
Results and Impact
The uncertainty of when posted invoices get payed was reduced to an average of seven days. The customer is now confident that machine learning can simplify the liquidity analysis in many parts and wants to develop a solution that can be integrated with the current bookkeeping technology.
We provide our customers with innovative solutions build on cutting-edge technologies from artificial intelligence and machine learning.
13355 Berlin, Germany
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Since 1996 the P3 group represents innovative Engineering services in the areas automotive, telecommunications, aviation, energy and public sector. The foundation are 3,900 highly qualified and motivated employees at over 40 locations in 17 countries.