The era of the fax machine is over – digitalization has long since found its way into German companies. Andreas Liebich, Head of Claims Management at Stadtwerke Düsseldorf AG, was an early adopter of automation and explains in this interview how his tasks have changed in recent years. He talks about current challenges, the use of AI and the opportunities that innovative technologies will open up for claims management in the future. Particularly exciting: How can predictive analytics and machine learning help to identify payment defaults at an early stage?

Have your tasks in claims management at Stadtwerke Düsseldorf changed in recent years and what role do developments in the field of artificial intelligence play in this?

Andreas Liebich: We have been consistently pursuing digitalization and automation for more than ten years. We now use more communication channels, we have more payment methods, but the core processes are highly automated and largely silent. Examples include the use of barzahlen.de, MaKo for the blocking process and the implementation of the avoidance agreement. However, I think that customers are increasingly aware of claims management due to the developments of the last four years (corona, inflation, war, price brakes, etc.). We have also expected a lot from the customer (price adjustments, budget billing adjustments, processing arrears, etc.) and have not always done everything well… The customer has become more demanding overall. Sensitivity to the smooth functioning of payment, direct debit and dunning processes has increased significantly, right up to the board level. AI has not been involved so far.

What advantages do you see in the use of AI for the optimization of payment processes and claims management?

Andreas Liebich: In view of the demographics of our company and the challenge of recruiting new staff, I believe it will be absolutely essential to take advantage of the opportunities that AI will offer. Artificial intelligence will – hopefully – help us to increase the allocation rates for payments and, ideally, also for clearing payments on the customer account. The automated generation of account statements would be a dream…

For claims management itself, I hope to see benefits in the area of predictive analytics. In the early detection of payment disruptions and payment defaults, ideally combined with suggestions for the next step in customer communication, e.g: When is it advisable to switch the business customer to prepayment in order to minimize the risk of insolvency?

Artificial intelligence (AI) is a major topic in many industries. How do you use AI in receivables management at Stadtwerke Düsseldorf AG? Are there specific examples or projects in which AI has already been used successfully in your company?

Andreas Liebich: We can see that plug and play solutions are not yet available on the market. But they will develop. We are not yet using AI in claims management. At SWD AG, we are currently involved in a transformation project in which we are replacing our entire system landscape with the new S/4 world of SAP. As part of the project, we are currently examining the use of Collections Management in FI-CA (Contract Accounts Receivable and Payable), which gives us access to AI functionalities, especially in accounting.

At the beginning of the year, we switched our agent desktop to the SAP Service Cloud as a first step in the project and are currently using AI to categorize messages on the writing channel. An interesting side note: training the AI is quite time-consuming. I also miss this aspect in many success stories. Who trains? Who tests? How long does it take? How many resources are tied up?

The new, open architecture of S/4 enables us as customers to gain access to new AI services from third-party providers via the SAP BTP (Business Transformation Platform) or to develop our own AI services with SAP Joules (SAP AI Assistant). And all this with a high level of integration into the existing system landscape. I’m excited to see what else there is to discover!

A common concern when introducing AI is data protection. How do you handle sensitive customer data at Stadtwerke Düsseldorf AG, especially in connection with AI applications?

Andreas Liebich: Data protection and data confidentiality are a valuable asset for energy suppliers. Also for SWD AG. Particular care is required here, especially with regard to future, intact customer relationships. We must create trust and reduce fears. This can only be achieved with transparency about the type and purpose of data processing. Guidance from the GDPR, which primarily focuses on protecting private customers, helps here.

With regard to AI, this excludes the use of public cloud scenarios in particular, as there is no control over data access and use. As a company, we take the requirements of the GDPR very seriously and involve our data protection officer in all decisions regarding the storage location of data and the systems used.

How do you see the future of claims management in relation to AI and other innovative technologies? What trends and developments do you expect?

Andreas Liebich: You can see it on the stock markets – the first big hype surrounding AI has died down. The topic of artificial intelligence is here to stay, but I suspect that it will be different from the blockchain topic, which was expected to be more successful. Key areas will crystallize where AI works particularly well. In addition, all topics that increase the degree of automation, e.g. RPA, will continue to be in the spotlight. I assume that our software suppliers will make a significant contribution to further development with AI modules.

The focus for the future will continue to be on keeping employees primarily occupied with topics that optimize our value creation. Digitalization will continue to advance and I am excited to see what we will be talking about in two years’ time.

© Coverimage: Andreas Liebich