Commercial dunning procedure: Use of artificial intelligence

Modern credit management is essential in order to secure liquidity and thus the existence of a company. Receivables management, in particular the commercial dunning procedure, plays a central role here. In a rapidly evolving digital landscape, innovative solutions that rely on artificial intelligence (AI) are becoming increasingly important to increase process efficiency and minimize payment defaults.

Important points on the commercial dunning procedure:

• Reminder as the first stage of the procedure
• Dunning levels with increasing urgency
• Reminder fees as an incentive to pay quickly
• Possibility of debt collection in the event of an unsuccessful reminder
• Legal action and enforcement as the final step in the proceedings

Basics of the commercial dunning procedure

The commercial dunning procedure involves systematically contacting customers who have not fulfilled their payment obligations despite the due date. This is an essential sequence of communication measures aimed at persuading defaulting payers to settle their outstanding items. This requires a balanced mix of tenacity and tact in order to avoid straining customer relationships while at the same time safeguarding the company’s liquidity.

Effective design and implementation of this process is crucial to reducing operational costs and improving cash flow. Great importance is therefore attached to optimizing dunning processes in order to shorten payment delays and reduce the risk of bad debts.

Definition and legal framework

The commercial dunning procedure comprises established receivables management processes designed to ensure customers’ payment behavior. Essentially, it is used to collect overdue liabilities and maintain the liquidity of companies.

The dunning process is not specifically regulated by law; however, it is based on general principles of the law of obligations. Professional implementation protects against legal sanctions and promotes the preservation of business relationships.

An efficient dunning procedure can accelerate incoming payments by up to 30%.

Precise documentation and tracking of the dunning process is essential for compliance with the legal framework. This creates transparency and serves as a safeguard in the event of possible legal disputes over outstanding receivables.

Sequence of a typical procedure

In the first step of the commercial dunning procedure, the invoice is issued after the service or delivery has been provided, usually by an automated system. The payment deadline is defined and communicated.

After the deadline has expired, the dunning process begins if payment is not made. This is often system-driven and rule-based.

The first reminder is then sent out as a payment reminder, often including grace periods. Communication remains friendly and professional.

If the payment deadline continues to pass, further reminders will follow with increasing pressure and consequences such as interest on arrears or commercial register notifications.

At the same time, the debtor’s creditworthiness is monitored and the risk of default is assessed by means of an outstanding receivables check. This is increasingly being done using AI-supported analyses.

Finally, if there is no response, the debt is handed over to a debt collection company(debt collection) or legal action is initiated. Specialized AI systems support the decision-making process for this escalation.

Differences to the judicial dunning procedure

In contrast to the judicial dunning procedure, the commercial dunning procedure is a pre-trial process. The primary aim is to reach an out-of-court settlement in order to save time and money.

Judicial dunning procedures result in an enforcement order, commercial ones do not.

Another difference lies in the flexibility of the process design, which is greater in the commercial approach.

In addition, personalized communication channels are often chosen in commercial dunning procedures, while judicial dunning procedures tend to follow standardized patterns.

In addition, commercial reminders allow for a stronger relationship with the customer through an individual approach to the respective situation.

Last but not least, prevention plays a central role in the commercial dunning procedure in order to minimize future payment defaults.

AI in the dunning process: Opportunities and limits

The integration of artificial intelligence (AI) in commercial dunning holds considerable potential for increasing efficiency and reducing costs. AI systems can analyze large volumes of data, identify payment patterns and thus predict the probability of incoming payments. This data intelligence makes it possible to adapt dunning strategies precisely to the payment behaviour of customers and thus optimize liquidity protection.

However, the use of AI in the dunning process also has its limits. Data protection regulations, such as the GDPR, set strict framework conditions for automation. In addition, the correct interpretation of payment behavior and customer relationships is a challenge that requires a delicate balance between algorithmic decision-making and human evaluation. The human factor therefore remains an indispensable component in commercial dunning in order not to jeopardize customer loyalty and to enable individual solutions.

Increased efficiency through automation

Automation processes act as catalysts for the commercial dunning procedure. They eliminate repetitive, time-consuming tasks and thus increase operational effectiveness.

Intelligently structured automation of dunning runs enables companies to make targeted use of their resources. Dunning processes are optimized and payment defaults minimized by using AI-supported algorithms to control the appropriate dunning level and strategy individually depending on the customer profile and payment history. This not only leads to a reduction in operating expenses, but also to improved customer communication and relationships.

Automation also enables continuous analysis and adaptation of processes. Deviations and patterns are identified at an early stage, minimizing risks and proactively shaping receivables management. This implicitly increases the efficiency of the entire dunning process.

By integrating artificial intelligence into automation, repetitive tasks can not only be performed faster, but also more intelligently. Machine learning makes it possible to learn from every dunning action and continuously optimize the strategy. In this way, AI helps to avoid payment delays and supports companies in securing their own liquidity and reducing the risk of non-payment.

Artificial intelligence in data analysis

Artificial intelligence (AI) plays a key role in the advanced commercial dunning process. It enables granular analysis of customer data and proactive risk assessment.

In the context of receivables management, AI provides essential services for identifying payment patterns and process deviations. Algorithm-supported learning interprets data histories in order to derive tailored dunning strategies and increase the engagement rate while minimizing errors and costs.

The added value of AI lies particularly in its adaptability: it can react dynamically to changes in payment behaviour and optimize dunning strategies in real time. This leads to an increase in the efficiency of incoming payment forecasts and a reduction in credit risk.

By integrating AI into the dunning process, even complex data structures can finally be used efficiently. Capabilities such as semantic understanding and pattern recognition make a decisive contribution to improvingcash flow and thus form the basis for future-proof accounts receivable management. AI-supported systems therefore provide an essential basis for sound business decisions.

Limits of AI in the legal context

The implementation of AI in commercial dunning procedures is coming up against legal limits, particularly in the interpretation of legal situations and contracts. Judicial complexities and individual cases cannot be comprehensively covered by a predefined AI logic.

AI systems have no legal judgment.

Processes such as the commercial dunning procedure require a deep understanding of the legal framework, which requires human judgment and consideration of case-specific nuances. A purely algorithmic evaluation of these aspects can lead to misleading conclusions and inadmissible recommendations for action.

The use of AI in the legal context is therefore guided by the understanding that it has a supporting function, but can never replace the expertise and decision-making power of a qualified lawyer. Especially in critical situations that require an in-depth legal assessment, people remain irreplaceable. In addition, compliance with current legal regulations must always be ensured in legal matters, which requires continuous updating of the AI systems. The decisive factor is therefore a harmonious interplay between human expertise and the performance of the AI.

Practical example: AI-supported dunning procedure

AI-supported commercial dunning procedures are also gaining in importance as part of the digitalization of financial processes. This innovative approach makes it possible to manage outstanding receivables more effectively and accelerate the receipt of payments. By using machine learning, patterns in customer payment behavior can be identified and individually adapted dunning strategies can be developed. This makes the dunning process not only more efficient, but also more customer-oriented.

A decisive advantage of using AI in the dunning process lies in the dynamic risk assessment. Based on continuously collected data, the system predicts potential payment defaults and enables companies to take preventative measures. This makes a significant contribution to increasing sales security and minimizing financial risks. Added to this is the automated adaptability of communication and escalation levels in the dunning process, which makes it possible to react promptly and appropriately to changes in customer behavior.

Implementation in the company

The establishment of a commercial dunning procedure represents substantial added value for companies. However, the integration of such a process requires thorough preparation and strategic alignment with company-specific requirements.

Given the complexity of modern business environments, it is essential that both the organizational and technological foundations for the automation of dunning processes are precisely defined. The selection and implementation of adequate AI solutions plays a key role here, which is a top priority, not least because of the necessary data security and data protection. Artificial intelligence not only makes it possible to record payment patterns, but also to proactively adapt dunning strategies to individual debtor profiles.

A tailor-made concept and implementation of the dunning procedure is crucial for its success. This also includes training and change management programs for employees to ensure acceptance and effective use of the new technologies. The aim must be to establish a system based on artificial intelligence that increases efficiency without neglecting the interpersonal component.

Ongoing evaluation and optimization of the dunning process are crucial to ensure consistent and satisfactory results in the long term. AI systems equipped with analytics functions provide the necessary transparency and enable continuous improvement of the process. This not only achieves operational excellence and minimizes bad debt losses, but also strengthens customer relationships in the long term.

Results and field reports

In practice, it has been shown that a commercial dunning process supported by artificial intelligence (AI ) contributes significantly to reducing payment defaults.

Several studies have already shown that the use of AI in dunning processes leads to a reduction in throughput times, enables a more precise risk assessment and increases customer satisfaction through individualized communication. In addition, experience shows that AI-supported analytics can improve the forecast quality for payment probabilities and thus manage financial risks more effectively. This leads to an optimization of capital allocation and resource-saving design of the dunning process.

Companies report that automated processes and intelligent decision-making algorithms have increased internal efficiency and reduced administrative burdens. The result was faster receipt of payments and increased liquidity. These aspects contribute to economic stability and the further development of business models by freeing up financial resources for investment.

The role of AI in identifying payment patterns and debtor behavior is particularly noteworthy. Machine learning and the processing of large volumes of data are used to continuously refine the dunning process. Companies that rely on such advanced systems benefit from agile, data-driven decision-making and improved strategic positioning in the market.

The future of dunning with artificial intelligence

Artificial intelligence (AI) is revolutionizing the commercial dunning process by automating repetitive processes and supporting data-based decisions. Predictive analytics enables payment defaults to be identified at an early stage and prioritized dunning strategies to be developed accordingly. Nevertheless, the individual customer approach remains a central component that AI systems can optimize through personalized reminders based on customer profiles.

The use of AI in dunning enables error-resistant and scalable processing, which leads to a significant reduction in debtor risks. Companies that use AI technology can therefore focus on strategic tasks while operational processes are largely automated and efficiently controlled.

Further development of AI technologies

In the context of dunning, the further development of AI technologies is of eminent importance. Advanced algorithms can significantly increase the efficiency of the process.

AI systems are constantly evolving through machine learning and neural networks, leading to more precise forecasting models. This enables earlier and more accurate identification of payment defaults. In addition, advanced analysis methods ensure deeper customer segmentation, which in turn helps to refine dunning strategies. Risk management is therefore becoming increasingly proactive rather than reactive.

At the same time, adaptive AI systems make it possible to react to changing market dynamics and the individual payment behavior of debtors. This agile approach increases the accuracy of dunning measures and promotes cost efficiency and customer retention. Personalized communication through AI makes a significant contribution to improving the customer experience.

However, the integration of AI into the commercial dunning process also requires stringent data quality and security. As systems become increasingly networked, data protection and integrity must be maintained, for which AI provides assisting technologies for anomaly detection and prevention. This creates the basis for a reliable and trustworthy application of AI in dunning, which is not only effective but also legally compliant.

Outlook for future areas of application

The future implementation of AI in the commercial dunning process opens up advanced optimization potential.

1. Forecast accuracy: Improved prediction of payment defaults through more precise risk analyses.
2. Automated customer interaction: development of self-learning chatbots to increase interaction efficiency.
3. Integration of blockchain technology: securing transaction history and increasing transparency.
4. Advanced data analysis: use of big data for profiling and personalized communication.
5. Preventive risk management: early identification and minimization of risks through proactive measures; increased efficiency through automated processes creates capacity for strategic tasks.

The aim is to sustainably improve payment practices and minimize defaults.

Glossary of commercial dunning procedures (the 7 most important terms)

The commercial dunning procedure is an important part of receivables management in companies. To help you understand the process better, the seven most important terms are explained here:

1. Reminder: A reminder is a written request to the debtor to settle an outstanding invoice. It serves as the first stage of the dunning procedure and informs the debtor of the payment arrears.
2. Payment deadline: The payment deadline is the period that the debtor has to settle the outstanding invoice after receiving the reminder. It is usually specified in the reminder and should be observed by the debtor.
3. Dunning level: The commercial dunning procedure consists of several dunning levels. Each stage is introduced by a further reminder that increases in tone and urgency. The number of dunning levels can vary depending on the company.
4. Reminder fees: Dunning fees are costs that are charged to the debtor for the dunning procedure. They serve as an incentive to settle the outstanding invoice quickly and are intended to cover the costs of receivables management.
5. Debt collection: If the commercial dunning procedure does not lead to the desired success, debt collection can be called in. The claim is handed over to a debt collection agency, which takes care of collecting the outstanding amount.
6. Enforcement: If the debtor does not settle the outstanding invoice even after collection, a court title can be obtained. This serves as the basis for further enforcement measures.
7. Compulsory enforcement: Compulsory enforcement is the final step in the commercial dunning procedure. Measures are taken to enforce collection of the outstanding debt, for example by seizing the debtor’s assets.
8. Creditor: The creditor is the person or company to whom a claim is due. In the commercial dunning procedure, the creditor is the party who has an outstanding invoice against the debtor and initiates the dunning procedure to demand payment.

Extrajudicial dunning procedure. What is that?

The extrajudicial dunning procedure is a procedure for the extrajudicial collection of outstanding debts. It is a preliminary stage to the judicial dunning procedure and aims to reach an agreement between creditor and debtor without the need for a court judgment or title.

In extrajudicial dunning proceedings, written reminders and requests for payment are sent to the debtor. The creditor or a commissioned debt collection agency carries out the procedure. The aim is to persuade the debtor to settle the outstanding invoice and reach an out-of-court settlement.

The extrajudicial dunning procedure offers several advantages. It is more cost-effective and time-saving compared to the judicial dunning procedure. It also enables faster processing of outstanding receivables and a higher probability that the debtor will be willing to pay.

It is important to note that the extrajudicial dunning procedure does not involve the direct involvement of the court or a judge. It is an out-of-court solution that aims to reach an agreement between the parties without the need for court proceedings.