Election outcomes won’t ease financial pressure on businesses

“CFOs should anticipate consistently higher borrowing costs moving into 2027,” stated Josh Putnam, global and Americas corporate finance leader at EY-Parthenon. He emphasized that financing volatility is likely to continue regardless of congressional control.

Putnam attributes pressure on long-term rates to factors including growing deficits, strong capital demand, inflation volatility, and policy uncertainty. He advises finance chiefs to rigorously evaluate investments, manage debt strategically, and make prudent capital allocation decisions.

Gregory Daco, EY-Parthenon’s chief economist, agrees that political gridlock alone won’t automatically increase long-term borrowing costs. However, repeated budget disagreements and debt ceiling concerns could exacerbate upward pressure. He recommends stress-testing investments and maintaining hurdle rates that account for higher and more unpredictable capital costs.

Mark Williams, a master lecturer in finance at Boston University’s Questrom School of Business and former Federal Reserve Bank examiner, highlights that uncertainty, whether from Washington, D.C., or Wall Street, leads to increased costs. Banks may tighten lending terms and reduce credit availability in response to perceived risk, potentially causing spikes in short-term borrowing costs for companies reliant on commercial paper. He suggests securing credit lines with multiple banks and exploring longer-term funding options.

Furthermore, Williams advises developing internal economic models to compensate for potential delays in government data releases due to shutdowns. Government contractors should also assess the impact of payment delays on cash flow.

The rapid growth of AI is also drawing increased financial and political scrutiny. Voters signaled concerns about the costs associated with data centers, with candidates focused on rising electricity bills securing key victories, and several Ohio towns implementing restrictions on data center development. This could lead to higher interest rates for AI and data center projects, and potentially lower prices for existing AI bonds.

Williams recommends reverting to fundamental corporate finance practices, such as conservative net present value assessments and scenario analysis. Daco cautions that a backlash is likely if AI investments drive up power costs without broadly shared benefits. He urges CFOs to prioritize projects with demonstrable productivity gains, fully account for infrastructure costs, and invest in workforce development alongside technology.

Ultimately, disciplined financial management will be crucial. As Putnam concludes, “Companies that demonstrate their ability to effectively deploy capital will be best positioned for growth.”