How does the reduction in debt improve the company’s credit rating or cost of capital?

Short answer:

By cutting roughly $25 million of non‑affiliated debt, Hyperscale Data Inc. (GPUS) has lowered its leverage, improved key credit‑rating metrics (e.g., debt‑to‑EBITDA, interest‑coverage) and increased liquidity. Those changes make the company look less risky to rating agencies and lenders, which can lead to an upgraded credit rating—or at least a more favorable outlook—and to a lower cost of capital for future financing (both debt and equity).

Below is a step‑by‑step explanation of why and how this debt reduction can translate into rating and financing benefits, using only the information disclosed in the press release.

1. What the press release tells us

From these points we can infer that the debt cut is a deliberate balance‑sheet optimization aimed at supporting a large upcoming capital project (the Michigan AI data center). The release does not specify the original debt level, interest rate, or any rating agency commentary, but the language (“strengthening capital structure,” “financial flexibility”) is precisely how companies describe actions that improve credit quality.

2. How lower debt improves credit‑rating metrics

2.1 Leverage ratios fall

• Debt‑to‑EBITDA (or Debt‑to‑Operating‑Cash‑Flow) drops because the numerator (total debt) is smaller while earnings or cash flow from operations stay roughly the same (or are expected to rise with the new data‑center).
  
• Debt‑to‑Equity declines because equity remains unchanged (or may even increase later through retained earnings), while debt shrinks.

2.2 Coverage ratios rise

• Interest‑Coverage Ratio (EBIT/Interest Expense) improves because interest expense falls in line with the $25 M debt reduction (assuming the same average interest rate).
  
• Fixed‑Charge Coverage (including lease payments) also moves in the same direction.

2.3 Liquidity improves

• Net‑Debt‑to‑Cash‑and‑Cash‑Equivalents improves, meaning the company now has a larger buffer of liquid assets relative to what it still owes.
  
• The company can meet short‑term obligations more comfortably, a factor rating agencies weigh heavily.

2.4 Debt maturity profile becomes less risky

• If the $25 M represented a chunk of near‑term maturities, paying it down reduces the amount that must be refinanced in the next 12‑24 months, cutting refinancing risk.

Result for credit ratings:

Rating agencies (S&P, Moody’s, Fitch) use the above metrics in their quantitative models. A measurable reduction in leverage and improvement in coverage typically leads to:
- Rating upgrades (e.g., from “BBB‑” to “BBB” or “A‑”), or

- Positive rating outlook changes (e.g., “stable” to “positive”), which in turn influences market perception even before an official upgrade occurs.

Because the press release explicitly states the debt reduction “strengthens the capital structure,” it signals to rating agencies that the company is actively managing risk, which can be reflected in rating committee discussions.

3. How a better credit rating (or stronger balance sheet) reduces the cost of capital

3.1 Lower borrowing costs (Debt side)

3.2 Lower equity cost (Equity side)

3.3 Overall Weighted‑Average Cost of Capital (WACC)

• WACC = (E/V)×Re + (D/V)×Rd×(1‑Tc)
  Where Re = cost of equity, Rd = cost of debt, Tc = corporate tax rate, E/V and D/V = equity and debt weights.
  
• By cutting debt, the D/V proportion falls, but Rd also falls more because the spread narrows.
  
• Simultaneously, a stronger balance sheet lowers Re (lower equity risk premium).
  
• The net effect is a lower WACC, meaning each dollar of new capital (whether borrowed or raised from shareholders) is cheaper for the company.

4. Why this matters for the Michigan AI Data Center expansion

1. Financing the project – The data‑center will require substantial CAPEX (likely hundreds of millions). With a lower WACC, the net present value (NPV) of the project improves, making the venture more economically attractive.
2. Flexibility for phased roll‑out – Reduced debt frees up borrowing capacity, allowing the company to phase financing (e.g., take on new debt as the center becomes operational, rather than front‑loading the entire amount).
3. Risk mitigation – Should market conditions tighten (e.g., higher interest rates in 2026‑27), having a cleaner balance sheet cushions the company against spikes in financing costs.
4. Investor confidence – A credit‑rating upgrade or positive outlook signals to both debt and equity investors that the expansion is financially sustainable, supporting demand for any new securities issued to fund the project.

5. Bottom‑line summary

• Debt reduction of $25 M → lower leverage, higher coverage, better liquidity.
  
• These improvements feed directly into credit‑rating models, likely resulting in a rating upgrade or at least a positive outlook.
  
• Higher credit quality reduces the spread investors demand on new debt, and strengthens the company’s equity profile, both of which lower the overall cost of capital (WACC).
  
• For Hyperscale Data, this means cheaper financing for the upcoming Michigan AI data‑center, greater financial resilience, and a stronger competitive position in the rapidly growing AI‑infrastructure market.

All of the above conclusions are drawn from the information given in the press release (debt reduction, capital‑structure strengthening, and the upcoming data‑center expansion) and from standard credit‑rating and corporate‑finance principles.