Kevin Wald is a field compensation professional at American Fidelity, an insurance company headquartered in Oklahoma City. Before insurance, he ran comp in oil and gas and logistics. His current role sits between the comp plan and 500+ agents in the field — explaining how payouts work, handling disputes, and translating comp mechanics into something reps can act on. We asked him about what stays broken regardless of industry, what happened when a product incentive misfired, and where AI has changed his daily work.
“Regardless of the industry — people not understanding their plans. You can give them documents, send emails, give them all the literature in the world. A lot of times they’re still not going to fully understand how they’re paid.”
On the one problem that shows up in every comp environment:
Kevin has built and administered comp programs across three industries. The technical details varied. The human dynamic didn’t. Reps consistently don’t understand how they get paid, even when the documentation is thorough. His read: salespeople’s strength is selling — finance and plan mechanics aren’t where their attention goes. A significant part of his role is just translation: helping reps understand what counts toward their comp, why their check doesn’t match what they expected, and what to do about it.
“We had to change the rate, which had unintended consequences. You’re kind of blowing your credibility with the Salesforce.”
On what happens when a product incentive misfires:
American Fidelity uses a credit multiplier system — products they want to prioritize get a higher NDAB factor, others get a discount. When a product was assigned a premium multiplier based on actuarial projections that turned out to be wrong, the field responded exactly as the plan designed: they sold a lot of it. When the error was caught and the multiplier was lowered, reps stopped selling that product almost immediately. Not because anyone told them to. Because they noticed the rate had changed. They never complained directly — they just stopped.
“How much behavior are you really going to change when reps don’t know what they’re getting paid until a month and a half after what they wrote?”
On the gap between what reps track and what they actually get paid on:
Reps at American Fidelity are paid on issued applications, not written ones. A rep who writes $50,000 in business in a month might get paid on $30,000 — because the rest issues the following month or doesn’t clear underwriting. Most reps track what they wrote in their own spreadsheets and expect payment on that figure. Kevin’s team fields those gap questions constantly. The company is implementing a new system to surface daily visibility — what’s written, issued, pending, and paid. Until then, most reps find out what they earned when the deposit hits.
“I’ll throw the question and the comp document into AI and it’ll spit out an answer. Honestly, a lot of times it’s better than me. About 95% of the time, it’s really good.”
On where AI has actually changed the daily work:
Kevin uses AI in three specific ways: generating Excel formulas he doesn’t have memorized, answering rep questions by feeding the comp document and the question in together, and summarizing long email chains before he has to respond. The rep question use case is the one he reaches for most. He drops in the comp doc and the question, gets an answer, confirms it manually, then sends. The accuracy has been high enough that it’s become a standard part of how he handles inbound from the field.
“The worst thing you can do is not be transparent, not be open, because then that removes the trust.”
On how to communicate comp changes without losing the field:
When his team has made adjustments to the comp plan, they’ve run focus groups first — reps, managers, and supervisors from the field — before anything is finalized. The consistent message to the field: “We’re not taking money away. We might be moving it into different pockets to motivate different behaviors, but the total amount we’re paying out is the same.” Kevin’s one piece of advice for anyone building a comp function from scratch: lead with transparency. Once trust is gone, it’s harder to rebuild than any plan redesign.
TOP BYTES
“Regardless of the industry — people not understanding their plans. You can give them all the literature in the world. A lot of times they’re still not going to fully understand how they’re paid.”
“Once they figured out they weren’t getting paid the premium, they quit selling that product almost immediately. It was fascinating.”
“How much behavior are you really going to change when reps don’t know what they’re getting paid until a month and a half after what they wrote?”
“I’ll throw the question and the comp document into AI and it’ll spit out an answer. Honestly, a lot of times it’s better than me. About 95% of the time, it’s really good.”
“We’re not taking money away. We’re moving it into different pockets to motivate different behaviors. Being honest about that is what keeps the trust.”
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