Do-it-yourself strategies may seem like a good way to save money, but they can’t solve the complex issues behind payment failures
Failed payments are a hidden but serious threat to subscription businesses. Every unsuccessful transaction represents more than just a lost payment—it can lead to involuntary churn, damaged customer trust, and missed revenue opportunities. In fact, more than 50% of involuntary churn is driven by failed payments. Customers leave, but not because they want to cancel.
Many businesses attempt to tackle this problem by building simple, in-house payment recovery systems. These usually involve retrying the transaction a few times or sending basic reminder emails. While a do-it-yourself approach may seem like a good first step, creating a truly effective internal solution is far more challenging—and costly—than most businesses realize.
Common Challenges with In-House Payment Recovery
One of the first mistakes businesses make is assuming that a straightforward retry strategy is enough. Simply resubmitting a failed transaction at regular intervals doesn’t address the real reasons behind payment declines. Worse, aggressive retry tactics can hurt your standing with card issuers, increasing your future decline rates and damaging your merchant reputation.
Another major gap in internal solutions is the misinterpretation of decline reason codes. Codes like “Do Not Honor” or “Insufficient Funds” only tell part of the story. To recover failed payments effectively, businesses need real-time, data-driven insights—something most internal teams can’t produce without advanced analytics and data science capabilities.
The complexity doesn’t stop there. Understanding payment failures requires skilled interpretation of massive volumes of transaction data, including customer demographics, card issuer behaviors, and the ever-changing landscape of bank and network rules. Without this expertise, even the best internal recovery teams are flying blind.
External Factors Make Recovery Even Harder
Building recovery processes in-house is one thing—keeping them up to date is another challenge entirely. Regulatory requirements are constantly evolving. Initiatives like 3DS 2.0 and Strong Customer Authentication (SCA) have already reshaped payment authorization standards in many parts of the world.
More recently, Visa’s introduction of the Acquirer Monitoring Program (VAMP) has created a new layer of complexity. VAMP consolidates fraud and chargeback monitoring into a single program while adding oversight for enumeration attacks—a sophisticated form of card testing fraud.
Merchants who fail to meet VAMP compliance standards risk higher fees, account penalties, or even placement on Visa’s MATCH list—a near-death sentence for payment processing capabilities. Keeping up with these shifting compliance landscapes requires more than basic internal
resources—it demands dedicated, specialized expertise.
The True Cost of Building an In-House Payment Recovery Team
Building a world-class payment recovery function in-house isn’t just difficult—it’s incredibly expensive. A fully capable team would require specialized roles, including:
- Multiple data scientists with expertise in payment data modeling
- Data Analysts to interpret trends and identify risk patterns
- Machine learning engineers to build and maintain dynamic, evolving recovery models
Salaries and overhead for this team easily cost more than $1 million per year. And that’s without accounting for ongoing software development, compliance management, and data infrastructure costs.
And creating your own recovery tool is no quick fix. Even with significant investment, it typically takes 6 to 18 months to gather enough transaction data, build recovery models, fine-tune algorithms, and see meaningful results. Meanwhile, the business continues to lose revenue and suffer from elevated churn rates.
A Smarter Alternative: Partnering with a Specialized Provider
Rather than investing millions of dollars and waiting months—or years—for results, businesses can achieve better outcomes faster by partnering with a specialized provider like FlexPay.
FlexPay offers immediate access to advanced AI-powered recovery technology trained on massive transaction datasets, including real-world issuer behavior and bank-specific decline patterns. Our machine learning models create personalized retry strategies based on factors like transaction type, customer behavior, issuing bank rules, and decline reason codes—something in-house systems typically can’t match.
FlexPay’s failed payment recovery solution seamlessly integrates into existing billing platforms like Stripe, Recurly, Aria, and more, operating quietly in the background to optimize payment recovery without disrupting your existing billing system, resulting in a up to 73% improvement in recovery. By partnering instead of building, businesses benefit from faster deployment, dramatically higher recovery rates, all without the burden of long-term salary or development costs.
The Role of AI in Payment Recovery
Businesses must optimize payment recovery to reduce churn and the financial strain that goes along with it. A case in point: research from Checkout.com shows that 45% of consumers won’t retry a payment after a single false decline while our own research shows that more than a quarter of subscribers have experienced a failed payment in the past 12 months. Using AI tools reduces the risk of churn and improves customer retention.
AI tools that include Machine Learning (ML) are best suited for failed payment optimization because ML models continuously learn from the data it uses, and performance improves over time. This machine learning technology can increase approval rates by improving transaction requests and strategically managing retries. By adjusting payment data—such as modifying formatting, including or omitting specific details, and aligning with issuer preferences—AI increases the likelihood of approval. AI also adapts to changing network conditions, including issuer requirements, regulatory updates, and industry rules, which helps businesses eliminate formatting inconsistencies or data entry mistakes that could cause payment declines.
Focus Your Resources Where They Matter Most
Building an internal payment recovery solution might seem attractive at first glance, but the reality is very different. It’s costly, time-consuming, and complex—and doesn’t get the results a specialized solution can deliver.
Instead of draining resources trying to reinvent the wheel, businesses should focus their efforts where they can make the biggest impact: product innovation, customer experience, and strategic growth.
Don’t let failed payments quietly drain your revenue. Talk to our team today to learn how FlexPay’s specialized, AI-powered recovery platform can boost your recovered revenue and help you retain more customers without the cost, risk, and delay of building in-house.
