Reducing payment defaults in B2B leasing: 7 levers that really work in 2026

Payment defaults are part and parcel of the leasing business. Nevertheless, leasing companies today face new challenges that are becoming increasingly difficult to manage with traditional methods alone. Higher financing costs, volatile markets, a continued high level of economic uncertainty and delayed corporate insolvencies mean that historical creditworthiness data is often no longer sufficient to reliably assess risk.

At the same time, pressure on the revenue side is increasing. Sales and the market expect fast decisions and high approval rates, while risk management must keep defaults as low as possible. However, these two objectives are not necessarily in conflict.

Anyone seeking to reduce payment defaults in B2B leasing must identify risks earlier today and base decisions on a broader data foundation. Modern data sources such as account-based creditworthiness information supplement traditional credit reports with up-to-date insights into a company's actual economic performance. This makes it possible both to reduce unnecessary rejections and to identify risks earlier.

This article outlines seven levers that leasing companies can use to systematically develop their risk management in 2026.

The true cost structure of a default in leasing

A payment default does not end with an outstanding receivable. For leasing companies, it regularly triggers a series of further economic consequences that, viewed in their entirety, are often considerably higher than the original amount owed.

In addition to the actual bad debt, costs arise from repossession and disposal of the leased asset, potential residual value losses, refinancing costs and internal processing effort. On top of this comes tied-up equity capital and opportunity costs, since financing capacity cannot be used elsewhere.

Particularly in the case of high-value movable assets or capital goods, several cost items can take effect simultaneously. This means that the quality of the credit check is not the only factor determining a portfolio's profitability; the ability to identify risks as early as possible is equally important.

Lever 1: Early-warning indicators from account data instead of quarterly financial statements

What

Traditional credit checks are predominantly based on historical company information. Annual financial statements, register data or published financial figures remain important components of any professional risk assessment, but by their nature they reflect past developments.

Account-based credit checks supplement this information with current payment flows. This makes economic changes visible considerably earlier. For example, it becomes possible to identify:

• declining revenues,
• increasing liquidity fluctuations,
• recurring account overdrafts,
• conspicuous direct-debit returns, or
• changes in regularly recurring payments.

This information does not replace a traditional credit report, but it does provide additional early-warning indicators.

Effect

The earlier economic changes can be identified, the greater a leasing company's scope for action. Instead of only reacting to published company figures or payment defaults, risks can be identified as they emerge. This improves both the quality of risk management and the predictability of the portfolio.

Implementation

A sensible starting point is to use account-based information initially only for defined risk cases or larger exposures. This makes it possible to gain experience without fundamentally changing existing decision-making processes.

Lever 2: A second look for rejected but economically sound applicants

What

Not every rejection is based on an actually elevated default risk. Young companies in particular, or businesses with a limited credit history, often fail to achieve a sufficient rating from traditional credit reports even though their current economic situation is stable.

A second look supplements the existing information with current account data and enables a more differentiated assessment of such borderline cases. Further information on the methodology can be found in our article on the Second Chance.

Effect

Leasing companies can thereby identify additional economically viable customers without fundamentally lowering their risk criteria. The second look broadens the decision-making basis – not the appetite for risk.

Implementation

A two-stage process has proven effective:

1. traditional credit check,
2. account-based second review exclusively for defined borderline cases.

This keeps the standard process fast and efficient.

Lever 3: Dynamic limits instead of static frameworks

What

Many credit and leasing decisions are based on credit or exposure limits set once. These often remain unchanged throughout the term of the contract, even though the lessee's economic situation changes. Current company data, by contrast, enables more dynamic management.

Effect

Positive developments can be taken into account more quickly. At the same time, risks can be identified earlier, before payment disruptions occur. This improves both portfolio management and capital allocation.

Implementation

Dynamic limits should not automatically take every account movement into account. It is more sensible to define clear threshold values that trigger a renewed risk assessment when exceeded.

Lever 4: Behaviour-based monitoring during the term of the contract

What

The credit check does not end when the contract is signed. Throughout the term, a company's revenue development, liquidity and payment behaviour change. Continuous monitoring makes it possible to identify these changes at an early stage. In addition to traditional credit bureau information, current account data can provide additional indications here.

Effect

Behaviour-based analyses help risk management identify risks before leasing instalments are actually missed. The earlier changes become visible, the greater the scope for action. Possible measures range from more intensive customer support to individual restructuring solutions.

Implementation

Monitoring should be risk-oriented. Not every exposure requires the same level of oversight. Larger financing volumes or defined risk segments in particular benefit from continuous data monitoring.

Further information on account-based credit checks can be found in our foundational article. We explain the regulatory basis of account information services (AIS) separately.

Lever 5: Taking industry-specific default patterns into account

What

Not every industry reacts to economic changes in the same way. While some sectors show relatively stable payment flows, others are subject to considerably stronger cyclical or seasonal fluctuations. A uniform risk model often fails to do justice to these differences. In B2B leasing in particular, it is therefore worth taking an industry-specific approach.

Examples:

• Construction: project delays, rising material costs and seasonal fluctuations have a direct impact on liquidity.
• Logistics: declining transport volumes or rising fuel costs can lead to short-term strain.
• Hospitality and hotels: seasonality and fluctuating visitor numbers regularly produce very different cash flows.

Effect

Anyone familiar with industry-specific patterns can better classify economic developments and reduce incorrect decisions. A short-term decline in revenue often carries a different significance in a seasonal industry than in a continuously operating manufacturing business.

Implementation

Industry-specific rules should not replace traditional creditworthiness information, but supplement it. The combination of credit bureau data, industry knowledge and current account data enables a considerably more differentiated risk assessment.

Lever 6: Automated dunning and restructuring processes

What

The earlier conspicuous developments are identified, the greater the chance of developing viable solutions together with the lessee. A modern dunning and restructuring playbook therefore defines clear processes for different risk situations. Examples:

• personal contact,
• individual payment arrangements,
• temporary contract adjustments,
• closer support.

Effect

Not every payment delay inevitably leads to a final bad debt. Early communication increases the probability that economically sound companies can overcome temporary liquidity shortfalls. Both sides benefit as a result.

Implementation

Automated workflows ensure that defined events immediately trigger the appropriate measures. This makes risk management faster, more consistent and more scalable.

Lever 7: A data partnership between credit bureau and account analysis

What

The most powerful risk models are not created by replacing existing data sources, but by intelligently combining them. Creditreform has been providing high-quality information on companies for many years and remains an important component of professional credit checks.

Current account data supplements this information with an additional perspective: how is the company developing today? This combination links historical stability with current economic reality.

Effect

This gives leasing companies a considerably more sound basis for decision-making. Particularly in borderline cases, economically sound companies can be identified more effectively without diluting existing risk criteria. Additional opportunities for early risk monitoring also arise within existing portfolios.

Implementation

A sensible process typically looks as follows:

1. traditional credit check (e.g. Creditreform),
2. automated decision for clear-cut cases,
3. account-based second look for defined borderline cases,
4. integration of the results into existing underwriting.

This preserves established processes while extending them in a targeted way.

Traditional risk management versus data-based risk management in 2026

The table makes clear that modern risk decisions do not arise from replacing established procedures, but from developing them further.

Implementation roadmap: towards data-based risk management in 90 days

A complete overhaul of underwriting is usually not necessary. In practice, a step-by-step approach has proven effective:

1. Conduct a current-state analysis: analyse reasons for rejection, identify borderline cases, structure the portfolio by risk class.
2. Define a pilot area: for example, corporate customer leasing, particular asset groups or defined volume limits.
3. Integrate the second look: establish triggers, define the consent process, add account-based review.
4. Develop decision logic: traffic-light model, threshold values, documentation.
5. Measure results: approval rate, default trends, processing time, contribution margin.

A pilot project of limited scope often delivers robust findings within just a few months.

Conclusion: reducing payment defaults in B2B leasing means making better decisions

Anyone seeking to reduce payment defaults in B2B leasing today needs more than a traditional credit check. Historical company information remains indispensable and continues to form the basis of professional risk decisions. At the same time, however, the importance of current economic data is growing.

Account-based credit checks supplement existing processes where traditional information alone does not permit a clear decision. Particularly in borderline cases, this results in a more complete picture of a company's economic performance.

For leasing companies, this means:

• more well-founded decisions,
• earlier risk detection,
• more efficient processes,
• better cooperation between sales and risk management,
• higher approval quality without a blanket increase in risk.

The future of credit checking does not lie in replacing established procedures, but in combining them intelligently.

Further in-depth information can be found in our specialist articles:

• Account-based credit check
• Second Chance
• Credit checks in leasing
• Account information services (AIS)