Consumer Credit Stocks Screener Excel: Tracking Lender Health as Card Debt Tops $1.25 Trillion (July 2026)

Consumer credit stocks are heading into one of the most closely watched Q2 2026 earnings seasons in years, and this guide gives you an Excel screener to track the whole group in one place. With U.S. credit card balances now above $1.25 trillion, headline inflation still running near 4.2 percent, and the consumer visibly stretched, the question hanging over card networks, card issuers, and consumer lenders is simple: are credit losses about to turn, or has the group already priced in the pain? The finance sector kicks off Q2 reporting in mid-July, and the consumer-credit names follow across the back half of the month. This post walks through how to screen them in Excel, which metrics separate an asset-light network from a credit-sensitive lender, and how to model a charge-off shock yourself. It comes with a free screener template built on live MarketXLS formulas.

This is educational analysis, not investment advice. The tickers below are used to demonstrate how the formulas and the screen work, not as recommendations to buy or sell anything.

Consumer Credit Stocks Screener Excel: The Group at a Glance

The consumer-credit complex is not one trade, it is three. Payment networks earn a toll on every swipe and carry almost no credit risk. Card issuers lend directly to cardholders and live or die on the net charge-off rate. Consumer and fintech lenders sit at the credit-sensitive end of the spectrum, where funding costs and delinquencies swing earnings the most. A good screener has to show all three side by side so you can compare a premium compounder against a deep-value cyclical honestly.

Here is the quick-reference table the template is built around.

The point of the screen is not to declare a winner. It is to make the trade-offs visible: networks command premium multiples for durability, while issuers and lenders trade at low multiples precisely because their earnings are exposed to the credit cycle.

Why Consumer Credit Stocks Are in Focus Right Now

Three things have collided in mid-2026 to put this group front and center.

First, the balance sheet of the American consumer is stretched. Revolving credit card debt has pushed past $1.25 trillion, and with the Consumer Price Index still running around 4.2 percent year over year, real disposable income is under pressure. That combination is exactly the setup that eventually shows up in delinquency and net charge-off data at the card issuers.

Second, rates are staying high. Under new Federal Reserve Chair Kevin Warsh, the funds rate has been held in the 3.50 to 3.75 percent range, and forward guidance has been replaced with pure data dependence. Higher-for-longer rates cut both ways for lenders: funding costs stay elevated, but so do the yields on their loan books.

Third, the calendar. Q2 2026 finance-sector earnings begin in mid-July, and the consumer-credit names report across the back half of the month and into early August. Analysts expect finance-sector earnings to grow in the low double digits year over year, but the market has already re-rated the group, so the reaction will hinge on the credit commentary, not just the headline beat.

Put together, that is why a consumer credit stocks screener is worth building today rather than in hindsight. You want the framework in place before the prints land.

The Metrics That Matter for Consumer Credit Stocks

Screening lenders is different from screening industrials or software. You are analyzing a balance sheet with a lending business attached, so valuation leans on book value and returns, not just earnings growth. Here are the metrics the template is built around and the exact MarketXLS formulas behind them.

Notice what is not on the list as a live formula: the net charge-off rate. Charge-offs and delinquency figures are reported in company filings each quarter, not streamed as a spreadsheet field. The template handles that honestly by giving you a scenario model to frame the sensitivity and an earnings watchlist to track the actual prints, rather than pretending a live cell exists.

Building the Consumer Credit Stocks Screener in Excel

The MarketXLS approach is to put one ticker per row and let live formulas fill each column. Once the first row is built, you copy it down and the entire screen refreshes with current data. Here is what the core of the Main Dashboard looks like in formula form.

Start with identity and price:

=Name("V")                    Company name
=Sector("V")                  GICS sector
=QM_Last("V")                 Live last price
=QM_ChangePercent("V")        Intraday percent change
=MarketCapitalization("V")    Market capitalization

Then layer in the valuation and quality metrics:

=PERatio("COF")               Trailing P/E
=ForwardPE("COF")             Forward P/E
=PriceToBook("COF")           Price to book
=DividendYield("COF")         Dividend yield percent
=ReturnOnEquity("COF")        Return on equity percent
=ProfitMargin("COF")          Net profit margin percent
=Beta("COF")                  Beta versus the S&P 500

Because every value is a formula tied to the ticker in column A, you can drop in any consumer-credit name you want to track. Swap COF for DFS-style peers, regional card banks, or international issuers, and the row rebuilds itself.

A Simple Value and Quality Score

The template adds a rules-based score so you are not eyeballing eight columns at once. It rewards cheap valuation, healthy returns, a dividend, and lower volatility, all referencing your own input thresholds in the yellow cells:

=IF(PE>0, IF(PE<15, 2, IF(PE<25, 1, 0)), 0)
 + IF(DivYield >= MinYieldInput, 1, 0)
 + IF(ROE > 0.15, 2, IF(ROE > 0.08, 1, 0))
 + IF(Beta <= MaxBetaInput, 1, 0)
 + IF(PriceToBook < 3, 1, 0)

That produces a 0 to 7 score and a plain-English signal (Deep Value / High Quality, Balanced, or Growth / Premium). It is a teaching device to organize the group, not a buy list. A network like Visa scores low on value because its P/E and P/B are high, while a deep-value issuer scores high, and that contrast is exactly the insight the screen is meant to surface.

Modeling a Charge-Off Shock: The Scenario Sheet

The single most important variable for card issuers and consumer lenders is the net charge-off rate, the share of loans written off as uncollectible. The Scenario Analysis sheet lets you stress that variable and see the read-across to earnings.

The logic is straightforward. Start with an illustrative issuer that earns a base level of pre-tax income on a book of average receivables. A rise in the charge-off rate applies directly to that receivables base as an extra credit cost, and a rise in funding cost does the same. The adjusted pre-tax income falls accordingly.

The takeaway the model is designed to teach: a spread lender that loses a given share of pre-tax income sees a similar percentage hit to earnings per share, all else equal. That is why issuers trade on single-digit multiples and near book value, while the networks, which have essentially no balance-sheet credit exposure, command premium valuations. You can calibrate the model with real numbers using formulas like =Revenue("COF"), =EarningsPerShare("COF"), and =ReturnOnAssets("COF").

This is a framing tool, not a forecast. Nobody knows the path of the credit cycle, and the point is to size the downside, not predict it.

The Earnings Watchlist: Positioning Into the Prints

Because Q2 2026 is the near-term catalyst, the template includes an Earnings Watchlist sheet. It lists each name with an approximate report window and shows where the stock sits relative to its own trading range using live formulas:

=QM_Last("AXP")                       Current price
=FiftyDayMovingAverage("AXP")         50-day moving average
=TwoHundredDayMovingAverage("AXP")    200-day moving average
=FiftyTwoWeekHigh("AXP")              52-week high
=FiftyTwoWeekLow("AXP")               52-week low

From those, the sheet computes a Range Position (0 percent at the 52-week low, 100 percent at the high) and the percent off the high. That tells you at a glance whether a name is running hot into its print or lagging the group, which shapes how much a beat or miss might move it. Report windows in the template are approximate and based on prior-year timing, so always confirm the exact date on each company's investor-relations page.

Sizing Positions and Estimating Income

The Portfolio Allocation sheet turns the screen into a position plan. Enter a portfolio size and target weights in the yellow input cells, and the sheet sizes each position, estimates the share count from the live price, and projects annual dividend income:

Allocation $      = Portfolio Size * Target Weight
Est. Shares       = Allocation $ / Live Price
Annual Dividend   = Allocation $ * Dividend Yield

It also rolls up a portfolio-level estimated yield, which is useful when you are blending a low-yield network like Visa with a high-yield consumer lender like OneMain. The dividend figures use =DividendYield("OMF") and =DividendPerShare("OMF") so they refresh with the market.

Networks vs Issuers vs Lenders: The Comparison Matrix

The final sheet is a side-by-side comparison that makes the business-model differences explicit, because those differences drive the entire valuation gap in the group.

The single key insight the matrix is built to deliver: the consumer-credit trade is really two trades. Networks are quality compounders priced for durability. Issuers and lenders are cyclical, credit-sensitive names priced for risk. In a late-cycle, sticky-inflation backdrop, the swing factor for that second group is the net charge-off rate reported each quarter. Use the scenario sheet to frame the downside and the watchlist to track the prints.

What Is in the Template

The workbook has six sheets:

• How To Use explains each sheet and lists the MarketXLS formulas involved.
• Main Dashboard is the screener, one row per stock, with the value-and-quality score and adjustable input cells.
• Scenario Analysis models a charge-off and funding-cost shock across five scenarios.
• Earnings Watchlist shows Q2 2026 report windows plus moving averages and 52-week range position.
• Portfolio Allocation sizes positions and estimates dividend income from a portfolio input.
• Comparison Matrix contrasts networks, issuers, and lenders on model, risk, and valuation.

Every sheet includes a MarketXLS Functions Used box so you know exactly which formulas power each calculation.

Download the templates:

• - Pre-filled with illustrative data so you can see the layout immediately
• - Live-updating formulas that refresh with current market data

To use the live version, you will need MarketXLS installed in Excel. If you want a guided walkthrough of building screens like this, you can book a demo.

Frequently Asked Questions

What are consumer credit stocks?

Consumer credit stocks are companies whose earnings depend on how much Americans borrow and spend on credit. The group spans three tiers: payment networks like Visa and Mastercard that earn fees on transactions, card issuers like Capital One and Synchrony that lend to cardholders, and consumer or fintech lenders like Ally, OneMain, SoFi, and Affirm. Each tier has a different exposure to the credit cycle, which is why they trade at very different valuations.

Why do card issuers trade at lower multiples than card networks?

Card networks such as Visa and Mastercard carry almost no credit risk, because they earn a fee on payment volume without lending money. Card issuers actually extend credit and absorb the losses when borrowers default, so their earnings swing with the net charge-off rate. Markets pay a premium for the durable, asset-light network model and a discount for the cyclical, balance-sheet-heavy issuer model. The screener and comparison matrix in the template make that gap easy to see.

What is the net charge-off rate and why does it matter?

The net charge-off rate is the percentage of loans a lender writes off as uncollectible, net of recoveries. For card issuers and consumer lenders it is the single most important driver of earnings, because a rising charge-off rate flows straight through to the bottom line. It is reported in quarterly filings rather than streamed as a live data field, so the template models its sensitivity in the Scenario Analysis sheet and tracks the reported figures through the Earnings Watchlist.

Which MarketXLS formulas does the screener use?

The core formulas include =QM_Last() for live price, =PERatio() and =ForwardPE() for earnings multiples, =PriceToBook() for valuation, =ReturnOnEquity() and =ReturnOnAssets() for returns, =DividendYield() and =DividendPerShare() for income, =ProfitMargin() for margins, and =Beta() for volatility. The watchlist adds =FiftyDayMovingAverage(), =TwoHundredDayMovingAverage(), =FiftyTwoWeekHigh(), and =FiftyTwoWeekLow(). Every formula is a live MarketXLS function that refreshes inside Excel.

When do consumer credit companies report Q2 2026 earnings?

The finance sector opens Q2 2026 reporting in mid-July, with the largest banks first. The consumer-credit names generally follow across the back half of July and into early August. Report dates shift year to year, so the watchlist windows in the template are approximate. Always confirm the exact date on each company's investor-relations page before positioning around a print.

Can I add my own tickers to the screener?

Yes. Every metric is a formula tied to the ticker in column A, so you can replace any symbol or extend the list with regional card banks, international issuers, or other consumer lenders. The row rebuilds automatically with live data, and the score and signal columns recalculate on their own.

The Bottom Line

Consumer credit stocks head into Q2 2026 caught between a stretched consumer and a market that has already re-rated much of the group. The names split cleanly into asset-light networks priced for durability and credit-sensitive issuers and lenders priced for cyclical risk, and the swing factor for that second group is the net charge-off rate reported each quarter. A screener that puts all three tiers side by side, models the charge-off sensitivity, and tracks the earnings calendar gives you a repeatable framework instead of a headline reaction. Build it once in Excel with live MarketXLS formulas and it refreshes every quarter.

To build screens like this with live financial data inside Excel, explore MarketXLS or book a demo for a guided walkthrough.

Educational content only. Nothing here is investment advice or a recommendation to buy or sell any security. Always do your own research and consult a licensed financial professional.