Soft declines: how to diagnose and prevent them

Key takeaways

• Soft declines account for 80-90% of all payment failures and are temporary issues that can be recovered with intelligent retry strategies.
• Paddle data shows that adding three extra retries within the standard dunning window lifted failed payment recoveries by 20.2%.
• Retrying cards 24 hours after the initial failure, rather than the standard 2 hours, improved failed payment recovery by 6.5%, according to Paddle data.
• Mobile wallets like Apple Pay and PayPal reduce soft declines caused by incorrect card details at checkout.
• Paddle's churn prevention features drive up to 17% improvement in failed payment recovery rates through automated retry logic and recovery processes.

Failed payments are often seen as lost revenue, but that's not always the case. Most payment declines are temporary issues that can be resolved with the right approach. The problem is that many subscription businesses lack the systems to recover these failed payments effectively, leaving money on the table every month. Understanding what causes soft declines and how to handle them can mean the difference between losing a customer and keeping recurring revenue flowing.

What are soft declines?

A soft decline occurs when a payment is rejected for reasons that aren't permanent. The customer's card is valid and their account is active, but something temporary is preventing the transaction from going through at that specific moment. This could be insufficient funds, an authentication requirement, a technical glitch, or the card issuer flagging an unusual purchase pattern.

Soft declines vs. hard declines

Soft and hard declines are different, and understanding their differences is vital to optimizing your payment process. A hard decline is permanent and happens when a card is declined because it's expired or reported stolen, or the account has been closed. There's no point in retrying those transactions without the customer providing new payment information. But soft declines can often be recovered simply by trying again at a better time or through a different approach.

This distinction matters because it represents recoverable revenue. While hard declines require customer action, soft declines can be resolved in the background without bothering your customers. For instance, a SaaS company that loses customers due to failed payments might be able to recover those subscriptions by adjusting retry timing. An app developer with subscription lapses could bring users back by implementing smarter retry logic.

Common causes of soft declines

Insufficient funds

This is the most common reason for soft declines. The customer simply doesn't have enough money in their account when you attempt to charge them. This happens frequently with debit cards and is especially common early in the billing cycle. Companies charging monthly subscriptions might see this as a failed renewal on the first of the month. 

Authentication failures

Authentication-related declines trigger when transactions don't meet Strong Customer Authentication requirements. This is particularly relevant in regions covered by PSD2 regulations, such as the EEA and the UK. If a customer doesn't complete a 3D Secure challenge or the authentication process times out, the payment fails. Many app users abandon the checkout process when faced with unexpected authentication steps, and SaaS businesses can see subscription renewals decline when authentication requirements aren't smoothly integrated.

"Do Not Honor" decline codes

This is a frustratingly vague decline code that banks use when they're rejecting a transaction without providing a specific reason. This could be triggered by anomalies in spending patterns, daily transaction limits, or internal risk assessments. For instance, a customer upgrading to an enterprise plan might trigger this decline because the charge amount is significantly higher than usual. 

Technical issues

These occur when there are temporary problems with payment networks, processor downtime, or communication errors between systems. They're usually resolved within hours, but can cause a spike in failed payments if they happen during peak billing times.

The revenue impact of soft declines

Failed payments cost businesses billions annually. What makes this worse is that many customers who experience a card decline never return to that merchant, with a majority of the lost revenue going straight to competitors.

For subscription businesses, the impact compounds over time. A failed payment doesn't just cost you one month's subscription fee. It potentially costs you the lifetime value of that customer if you can't recover the payment and they churn. A SaaS company with a $50 monthly subscription and an average customer lifetime of 24 months isn't just losing $50 when a payment fails—they're risking $1,200 in lifetime revenue. 

The silver lining is that 80-90% of declines are soft, meaning most of this revenue is actually recoverable. The businesses that recover these payments effectively have a competitive advantage over those that simply accept the failed transaction and move on.

Strategies to reduce soft declines at checkout

Reducing soft declines at the point of checkout means fewer failed payments to deal with later. Here are some strategies to try: 

Encourage mobile wallets and saved payment methods

Mobile wallets significantly reduce declines caused by incorrect card details because they store verified payment information. With Apple Pay, Google Pay, or PayPal, customers aren't manually entering card numbers where typos can happen. For apps especially, mobile wallets provide a smoother checkout experience and reduce friction on smaller screens where typing card details is more error-prone.

Saved payment methods work similarly for returning customers. When a SaaS business allows customers to securely save their payment information, subsequent transactions are faster and less prone to errors. This is particularly valuable for businesses with usage-based pricing or metered billing, where charges might vary month to month.

Validate payment methods

Real-time card validation at checkout catches issues before they result in failed charges. This checks whether the card number is valid, whether it's expired, and whether basic formatting is correct. It prevents customers from submitting payment information that will inevitably fail, giving them the chance to correct it immediately rather than discovering the problem when their subscription doesn't renew.

Use smart payment routing

Using a provider like Paddle means your payments get routed across multiple payment gateways instead of relying on a single processor. When your primary gateway returns a soft decline—such as a "Do Not Honor" code or a technical timeout—the system automatically cascades the transaction to a secondary gateway in real-time.

Different gateways have different risk appetites and technical infrastructures. One gateway might flag a transaction as suspicious and decline it, while another views the same transaction as legitimate and approves it. For instance, a customer in Germany whose payment was declined by one processor might have their transaction succeed through an alternative gateway without any intervention. Cascading across gateways recovers payments that would otherwise be lost to false positives in fraud detection systems.

Local acquiring takes payment routing a step further for cross-border payments. Smart routing systems detect the country where a card was issued and send the payment to a local bank (acquirer) in that same region. This matters because banks are much more likely to trigger soft declines on foreign transactions since they resemble potential fraud patterns. 

Routing payments through local acquiring banks in each market significantly increases approval rates. Paddle's payment routing  handles this complexity automatically, testing different routing strategies and continuously optimizing based on real transaction data. The system adapts routing rules based on factors like card type, transaction amount, and customer location without requiring manual configuration. 

Recovering failed payments: retry timing and logic

When a soft decline happens, timing your retry attempts is an art and science. If you retry too quickly, you're likely to hit the same temporary issue that caused the initial failure. If you wait too long, you give customers time to forget about the charge or move on to a competitor. The challenge is finding the optimal window when the temporary issue has resolved, but the customer is still engaged with your service.

Why timing matters

Data from payment recovery systems shows that timing matters significantly. Paddle found that retrying cards 24 hours after the initial failure, rather than the standard 2-hour retry window, improved failed payment recovery by 6.5%. This longer window gives sufficient time to resolve common issues like insufficient funds—customers receive their paychecks, bill payments clear, or spending limits are reset for a new day.

The optimal number of retries

The number of retry attempts also influences recovery rates. More isn't always better because card networks monitor retry attempts, and excessive retries can lead to penalties. But too few attempts leave recoverable revenue on the table. Paddle data shows that adding three extra retries within the standard dunning window lifted failed payment recoveries by 20.2%. This suggests that most payment processors' default retry logic is too conservative and businesses could be recovering more revenue by extending their retry strategy.

What intelligent retry logic considers

The best retry systems factor in more than just timing. They consider:

• The specific decline code (insufficient funds requires different handling than "Do Not Honor")
• Card type (debit cards might need more time between retries than credit cards)
• Customer billing location (different regions have different billing cycle patterns)
• Historical payment patterns for similar transactions
• Day of the week and time of day when retries are most likely to succeed

Dunning processes

Dunning flows complement retry logic by bringing customers into the recovery process when automated retries don't succeed. Emails that clearly explain the payment failure and provide a simple way to update payment information can recover subscriptions that would otherwise be lost. For businesses with high-touch customer relationships, these communications can be personalized based on the customer's usage level or account status. For app developers with large user bases, automated dunning flows need to be simple and mobile-friendly since users are likely to interact with them on their phones.

Setting up automated transaction recovery without the overhead

The challenge with implementing effective retry logic and dunning flows is that they require ongoing maintenance and optimization. Payment failure patterns change, card network rules evolve, and what worked six months ago might not work today.

This is where automated recovery systems provide value. Paddle's churn prevention features drive up to 17% improvement in failed payment recovery rates by running intelligent retry logic and automated recovery processes in the background. The system considers factors like day of the week, specific decline codes, card type, and payment location to determine optimal retry timing. These optimizations happen automatically without requiring engineering resources or a payment operations team.

For a SaaS company focused on building product features, this means payment recovery runs without pulling engineers away from their roadmap. For an app developer scaling across multiple markets, this means recovery logic adapts to regional billing patterns without requiring market-specific configuration. 

Codeway, a mobile app company with over 300 million users, achieved a 36% recovery rate on previously failed payments using Paddle's automated recovery features. This translated to approximately $500,000 in recovered revenue—money that would have been lost without intelligent retry logic and automated dunning flows. These recoveries contributed directly to profitability and allowed the company to reinvest in product development rather than being forced to allocate resources to manual payment recovery. Read the full case study.