22 August 2022

Stable Business Connections Can Master a Crisis Better

DATEV joined KISS project for research on AI-based rapid supply networks.

A platform for setting up value-added networks quickly using artificial intelligence (AI) - this is the goal of the KISS project. This project is supported by the Federal Ministry for Economic Affairs and Climate Action (BMWK) for a three-year term. It is a cooperation of DATEV, InfAI, biosaxony e.V., the Technical University Chemnitz, USU GmbH, Eccenca, NRU GmbH and the Fraunhofer IWU, doing research on how to set up such an AI-based rapid supply network. Especially medium-sized enterprises may benefit from this planned infrastructure and become more resilient for sudden major challenges.

Stable business connections are the key to survive a crisis. Especially in times when various events cause supply chains to falter it is extremely important to know one’s business partners and their default risk very well - thus being able to find alternatives. Many small and medium-sized enterprises have neither sufficient instruments for early detection and prevention of problem areas nor functioning mechanisms to counteract effectively.

KISS wants to minimize acquisition and maintenance effort of validated business information on business partners and supply chains, thus protecting the economy from crisis situations. Within the framework of this project all research partners elicit how AI-based systems may help detecting system-relevant risks and developments early and manage them so services and production can be maintained stably. The system is supposed to model existing supply and value chains and to present suggestions how to fill any gaps in the supply chain fast and effectively.

Optimized Data Basis and AI Provide Recommendations for Actions

DATEV focusses on AI methods for analyzing and monitoring supply chain networks and supply chains. Existing data, open data sources, and anonymized data submitted to DATEV are initially examined by experts regarding their specific validity. Also, experts check how the quality of the business partners’ data can be improved. Questions on standardization and aggregation of different data sources need to be answered, such as invoice and payment information, tax ID, value added tax identification number check or business register. The goal is to create a consistent basis for identification, presentation, and evaluation for business partners, supply chains, and networks.

The next step will be the development of automated functions for analysis, identification, and presentation of business partners as well as supply chains. Finally, DATEV researchers will determine how this data can filter fast all relevant information for each individual situation of businesses – for example considering parameters such as sector, size or region – and deduct recommendations for actions. Thus, a corresponding data pool could allow precisely fitting risk forecasts, development of suited early warning systems as well as simple set-up of business continuity plans.