At Lithic, we’ve worked with companies building every kind of card program, and we’ve seen firsthand how the choice between charge and credit can define the economics and risk exposure of a business. As Lithic’s Risk Lead, I regularly advise both prospective and current clients on the risk factors associated with each model, as well as the operational requirements necessary to manage those risks effectively.
In this piece, I’ll outline the key differences between charge and revolving credit cards (i.e., credit cards), address some common misconceptions, and offer a practical framework to help you select the right model for your business goals and risk appetite.
Charge Cards vs. Credit Cards: A Quick Overview
When founders approach us at Lithic with plans to launch a card product, one of the first decisions we help them navigate is: should we issue a charge card or a credit card?
Typically, we see two types of founders or businesses looking to launch a card product. The first founder type is building a card to serve a specific consumer niche or affinity group—think: the ultimate card for pet owners. These founders often lean toward issuing a revolving credit card (i.e., credit card), which allows users to carry a balance and pay over time—the model most people associate with traditional credit cards.
The second type of founder is someone who already has a business or product in the market. These entrepreneurs have often relied on personal credit lines or off-the-shelf business cards to manage expenses or enable employee spend. For them, charge cards—also known as "closed-ended" cards, which require the balance to be paid in full each billing cycle—are often the more appealing choice.
Additionally, it's crucial to factor in rewards costs in your financial modeling, generous rewards programs (such as 3% cashback in specific categories and 2% elsewhere) impacting the potential revenue a program may earn from interchange.
Common Misconceptions
Many founders come to Lithic with a few preconceived notions about charge cards vs. credit cards. So, let’s clear up a few common misconceptions.
Misconception #1:
Charge cards are “less advanced” than credit cards and are not as flexible.
Reality:
Charge cards are not credit cards with training wheels — they are purpose-built for specific use cases. If you’re a business that requires higher spending limits, frequent expense cycles, or many authorized users, a charge card may be the more sophisticated solution compared to a traditional credit card.
Misconception #2:
Charge cards are always less risky to launch than credit cards.
Reality:
Charge cards indeed eliminate revolving debt risk — but that doesn’t mean they’re risk-free. Operational risk, repayment enforcement, and real-time fraud controls are still essential. You’re fronting funds for every transaction, so you still carry short-term credit exposure until repayment occurs. Additionally, offering flexible spending limits without rigorous controls can expose your business to unexpected loss events.
Misconception #3:
Spending limits are lower and more rigid with charge cards.
Reality:
Dynamic limits on charge cards can enable significant spend capacity without extending credit in the traditional sense. In fact, some of the highest-limit cards on the market are technically charge cards (Ahem - American Express Business Platinum Card). Sophisticated risk management systems that leverage transaction data and cash flow patterns can support these dynamic limits while still managing risk effectively.
Misconception #4:
Only banks can issue credit cards.
Reality:
It’s true that credit cards come with heavier regulatory requirements and typically involve a lending partner, but with the right structure and partners in place, fintechs can absolutely launch them.
Monitoring Risk
TLDR:
For charge cards, pay attention to cardholder cash flow and payment patterns. For credit cards, focus on utilization rates and paydown behavior. Having a pulse on these variables can help you address risk early on.
As we noted earlier, charge cards carry a different risk profile compared to revolving credit cards. That means the metrics and signals to help you manage your program will vary depending on which product you choose.
For charge cards, we tend to prioritize signals related to repayment discipline, average balances, and the predictability of cash flow. Cash flow tends to play an important part during the underwriting process for charge card holders, as well as ongoing indicators like payment velocity and repayment rate. Exception management also plays an important role—specifically, how often customers request adjustments to terms such as payment due dates or spending limits. A spike in exception volume or magnitude can be a leading indicator of stress in your cardholder portfolio.
Revolving credit cards require a slightly different lens. We tend to place greater emphasis on credit utilization rates, the pace at which customers are drawing down or paying down their available lines, and material changes to either of those variables. A rapid increase in utilization or a sharp pullback in spending can signal a shift in credit risk. And of course, credit bureau scores play a more central role in underwriting and ongoing monitoring of risk for traditional credit card holders.
Where the Risk Model Breaks Down
Credit Cards
The credit card risk model assumes some defaults but prices for this risk through interest and fees. The model works when portfolio-level loss rates remain within forecasted ranges, interest and fee income sufficiently covers losses, and delinquency transitions follow predictable patterns. The risk model is designed to mitigate risk through a combination of high APRs, late fees, and penalty interest. This is why credit card issuers focus so heavily on maximizing customer lifetime value (LTV). The model breaks down when economic shocks cause large ability-to-pay issues, regulatory changes limit fee income, or competitive pressures compress margins below risk-appropriate levels.
Charge Cards
Charge cards often assume users won’t default, but it’s a bigger problem when they do. Since balances must be paid in full, default rates should be low. However, if defaults spike unexpectedly, charge card issuers lack the cushion of interest income to absorb losses.
The biggest risk for charge cards is not default, but liquidity shocks. If a business or individual suddenly faces cash flow issues, they may be unable to pay in full, forcing the issuer to either cut off credit entirely or make exceptions.
Insider Insight:
Operational issues delaying collections effectiveness could also put charge card programs at risk. For charge cards, the collections window is compressed; you typically have 30-45 days to resolve a payment issue before considering a charge-off, compared to 120+ days for traditional credit cards. This requires more responsive monitoring systems and aggressive early-stage collections.
Getting Your Program Approved
Launching a card program requires approvals from multiple stakeholders: your board, your issuing bank, capital providers, and legal/compliance teams. Understanding what they look for can streamline the process.
When evaluating whether to greenlight a new card program, both Lithic and our sponsor bank partners take a close look at a specific set of metrics; those metrics vary depending on whether the product is a charge card or a revolving credit card.
Charge Cards
With charge cards, the focus is less on credit scores and more on the underlying business. We examine:
- Company History and Stability: Operating track record and management expertise
- Transaction Flow Analysis: Historical volumes and patterns
- Repayment Velocity: How quickly users typically pay balances
- Cash Flow Patterns: Predictability and seasonality of business cash flows
- Operational Controls: Processes to manage exceptions and delinquencies
- Capital Adequacy: Sufficient working capital to support short-term exposures
We also assess whether the business’s revenue is steady or highly seasonal and how seasonal (or any other) volatility might be mitigated. Other key indicators include dispute rates and the charge off rate, which is the percentage credit issued the company ultimately has to convert to a loss.
Credit Cards
For traditional credit card programs, we tend to pay close attention to anticipated or existing:
- Credit Risk Infrastructure: Underwriting models and validation processes
- Portfolio Projections: Expected utilization, payment, and loss rates
- Regulatory Compliance Framework: Capabilities for managing lending regulations
- Capital and Liquidity Planning: Long-term funding to support revolving balances
- Loss Forecasting: Statistical models to predict default patterns
- Collections Strategy: Process for managing delinquent accounts
These metrics help us understand how fintechs are managing their debt over time and what the likelihood of repayment looks like.
From the sponsor bank’s perspective, there’s an additional layer of scrutiny, especially when a fintech company is launching a net-new product. Banks want a detailed view of:
- The company’s financial health, including its current cash position and overall runway
- How the fintech plans to fund the program
- If the business is self-funding, how much capital has been allocated to support credit activity?
- If it’s relying on an external line of credit, what are the terms of that agreement?
In either case, banks want confidence that the program is being launched on stable financial footing. It’s not uncommon for banks to require 12, 24, or even 36 months of runway, or a minimum amount of cash on hand.
Regulatory Considerations
Credit cards face more comprehensive regulatory requirements than charge cards, including Truth in Lending Act (TILA) and Regulation Z disclosures, Credit CARD Act provisions for consumer protections, Fair lending compliance monitoring, and State-specific lending regulations.
Charge cards typically face fewer lending regulations but may still require clear disclosure of payment terms and fees, compliance with payment processing regulations, and fair treatment and collections practices.
Insider Insight:
Unlike many other fintech products, it is challenging to "beta test" a new card product. Contracts with banks and lenders typically span 2-5 years, and the wind-down process for card programs is particularly onerous. This makes your initial program design and risk management approach especially critical.
Which Path is Easier?
Credit cards require investment in loss forecasting, repayment modeling, and regulatory compliance tied to lending and interest disclosures. Between interest rates, late fees, and minimum payments, the product requires a more sophisticated risk infrastructure and compliance testing program. For those entering card issuing for the first time, charge cards can be more approachable.
Unlike credit cards, charge cards don't involve interest rate mechanics or a revolving balance structure. You're offering a single-point line of credit that resets each billing cycle, which streamlines both the user experience and the backend operational complexity.
That said, the added complexity of credit cards comes with a meaningful upside. Interest and fee revenue can significantly enhance the profitability of a program. For founders with access to strong credit risk capabilities and capital, a credit card model can offer more diverse revenue streams than a charge card.
Insider Insight:
While charge cards may offer simpler implementation and operational advantages, their revenue model can present monetization challenges as a standalone product, particularly in low interest rate environments. Most successful charge card programs function best as complementary offerings to an established business rather than primary revenue drivers.
Remember, whether offering a charge or revolving credit card, it's crucial to factor in rewards costs in your financial modeling. Generous rewards programs, such as 3% cashback in specific categories and 2% elsewhere, may impact the potential revenue a program may earn from interchange.
The Future of AI and Risk Management
We're optimistic about the advancements AI can bring to risk management for both card types, particularly in:
- Enhanced Cash Flow Analysis: AI can identify subtle patterns in transaction data to better predict payment capacity for charge cards and revolving behavior for credit cards.
- Dynamic Limit Management: Machine learning models can adjust limits in real-time based on evolving risk signals, particularly valuable for charge cards.
- Fraud Prevention: AI can detect anomalous patterns before traditional systems, critical for high-limit charge cards.
- Early Warning Systems: Predictive models can identify accounts showing early signs of stress, allowing for proactive intervention.
Implementation roadmap considerations include starting with specific use cases rather than comprehensive replacement, investing in transparent model governance, building feedback loops to continuously improve performance, and maintaining human oversight for exceptions and edge cases.
It’s important for card issuers to recognize that bad actors are likely to leverage these same tools; sometimes at a pace that outstrips the industry’s ability to respond. At Lithic, we're committed to staying ahead of the curve. We're actively exploring how AI can be used not just to improve internal risk controls, but to better protect both our customers and their cardholders from fraud.
Conclusion: Making the Right Choice
The decision between charge and credit products should be driven by:
- Business Model Alignment: Which product better complements your core offering?
- Customer Needs: What type of payment flexibility do your users require?
- Operational Capabilities: Can you support the regulatory and technical requirements?
- Risk Appetite: Are you prepared for the specific risk profile of your chosen product?
- Capital Resources: Do you have the funding structure to support your program?
By thoroughly evaluating these factors and understanding the distinct risk profiles and operational requirements of each product type, you'll be better positioned to launch a successful card program that enhances your business while effectively managing risk.