2 August 2022

Stable business relationships can better withstand a crisis

DATEV has joined the KISS project to research AI-based rapid supply networks.

The KISS project aims to create a platform for rapidly establishing value-added networks using artificial intelligence (AI). The project has been funded by the Federal Ministry of Economics and Labour (BMWK) for three years. It is a cooperation between DATEV, InfAI, biosaxony e.V., Chemnitz University of Technology, USU GmbH, Eccenca, NRU GmbH and Fraunhofer IWU, which is researching how such an AI-based rapid supply network can be set up. Mediumsized companies, in particular, can benefit from this planned infrastructure and become more resilient in the face of sudden significant challenges.

Stable business relationships are vital to surviving a crisis. Especially in times when various events disrupt supply chains, it is crucial to know your business partners and their risk of default - and to be able to find alternatives. Many small and medium-sized enterprises need more tools for early detection and prevention of problem areas and effective mechanisms to deal with them.

KISS aims to minimise the cost of acquiring and maintaining validated business information on business partners and supply chains, thus protecting the economy from crisis situations. In this project, all research partners investigate how AI-based systems can help identify and manage systemic risks and developments to maintain stable services and production. The system will model existing supply and value chains and suggest how to quickly and effectively fill any gaps in the supply chain.

Optimised databases and AI provide recommendations for action

DATEV uses AI methods to analyse and monitor supply chain networks and supply chains. Experts first check the validity of existing data, open data sources and anonymised data submitted to DATEV. The experts also examine how the data quality of business partners can be improved. Questions relating to standardising and aggregating different data sources, such as invoice and payment information, tax ID, VAT number verification or business register, must be answered. The aim is to create a consistent basis for identifying, presenting and evaluating business partners, supply chains and networks.

The next step will be to develop automated functions for analysing,identifying and presenting business partners and supply chains. Finally, DATEV researchers will determine how this data can be used to find all the relevant information for any company situation quickly - for example, considering parameters such as sector, size or region - and derive recommendations for action. Such a data pool could enable precise risk forecasts, the development of suitable early warning systems and the easy creation of business continuity plans.