By Sagar Shankaran, Founder of CallSphere
A cloned voice can get a prepaid training package refunded and a 24-hour fob turned back on. The callback rule that closes both, and what one incident costs.
Key takeaways
Fair. Nobody is running voice fraud to steal a rowing machine. That is not the thing in your building worth taking, and it never was.
What is worth taking is the prepaid personal training package. A member buys a twenty-four session block at $100 a session, uses six, and $1,800 sits on your books as a refundable-ish balance that a person on the phone can move. That, plus the credential that opens an unstaffed 24-hour club at two in the morning, are the two phone-authorised actions in a gym that a convincing voice can abuse. Both of them are handled routinely, by a nineteen-year-old at a front desk, at the exact hours nobody senior is in the building.
Voice cloning stopped being a research demo and became a cheap tool. Thirty seconds of clean audio is enough — and clubs generate clean audio constantly: the class recording you posted to Instagram, the member testimonial video on your website, the voicemail your own system captured. If your verification step is "she sounded like herself and she knew her address," you do not have a verification step.
Call one: money. "This is Dana Whitfield, member 40881. I'm moving to Charlotte in three weeks, I've got eighteen sessions left, my card was replaced after fraud, can you refund the balance to the new one and cancel the draft?" Every element of that call is normal. Members move. Cards get replaced. Training balances get refunded. In most clubs the desk takes the new card over the phone, the GM signs off in the morning, and the money leaves.
Call two: access. "My fob stopped working, I'm out front, can you turn it back on?" At a staffed hour that is a thirty-second fix. At 9:40 p.m. in a club that goes unstaffed at ten, it is a physical key to an empty building overnight, complete with a lobby full of members' bags, a merchandise cabinet, and a supply room. Access is the request people forget to protect, because it does not feel like money.
There is a third that deserves an honest mention: changing the bank account on a family or corporate account with multiple names on it. Less dramatic, quieter to abuse, and worth putting on the same list.
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The old rule was that you could tell. A cloned voice was flat, oddly paced, obviously wrong on an interruption. That is no longer true, and the tell people relied on — a hesitation when you throw an unexpected question — has largely gone. At the same time, everything a caller needs to sound legitimate is public or cheaply bought: name, address, phone number, the fact that they belong to your club, sometimes the last four of a card from an unrelated breach.
So the verification question changed shape. It is no longer "does this sound like the member" or even "does this person know the member's details." It is "can this caller demonstrate control of something the member controls" — the phone number in the record, the email in the record, the app login. That is the only test that a voice cannot pass by imitation.
flowchart TD
A["Caller at 8:52pm: my fob stopped working"] --> B["Pull the member record, read nothing back aloud"]
B --> C{"Does the request move money or open a door?"}
C -->|No| D["Answer it: hours, class times, hold status"]
C -->|Yes| E["Send one-time code to the phone already on file"]
E --> F{"Code read back within five minutes?"}
F -->|No| G["Stop. Log the attempt. No action taken."]
F -->|Yes| H["Action queued, GM releases refunds in the morning"]
Print it and tape it inside the desk cabinet. Four lines.
If you run an AI voice agent on the main line, the same rules apply and are easier to enforce, because software does not get talked out of a policy at 8:52 p.m. by someone who sounds upset. The agent handles hours, class schedules, hold status and bookings freely; the moment the request touches money or the door, it sends the code to the number on file and hands the rest to a person. What it must never do is take a new card number by voice or activate access on the strength of the conversation alone.
Assumptions, illustrative: one successful incident a year at a mid-size club, on a training balance of $2,400.
| Line item | Illustrative cost |
|---|---|
| Training balance refunded to the wrong card | $2,400 |
| Chargeback and processor fees when the real member disputes | $45 |
| Owner and GM time: investigation, calls, incident write-up (7 hrs) | $315 |
| Reissuing credentials after an overnight access event | $600 |
| The member you lose, and the one she tells (2 memberships, avg 9 months) | $936 |
| One incident, all in | $4,296 |
Now the cost of the fix. Suppose sixty requests a month genuinely move money or access. The one-time code adds about forty seconds to each — forty minutes of desk time a month, roughly $13 at a loaded front-desk rate. You are spending $156 a year to close a $4,300 hole, and the code step also kills the ordinary non-malicious version of the same problem: the ex-spouse cancelling a membership that is not theirs, which most clubs deal with more often than fraud.
Rules like this go wrong at the edges, and the edges in a gym are emotional. A member's husband died and his sister is calling to stop the draft. A member is in the hospital and her daughter wants the medical freeze started. A member with a disability cannot receive or read a text code. If the rule is only "no code, no action," your staff will either break it for the sympathetic cases — which reopens the whole hole — or apply it rigidly and generate the kind of story that lands on a local news segment.
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So write the exception path before you need it. Anything with a death, a medical event or an accessibility need routes to the GM by name, gets handled with documentation rather than a code — an emailed request from the address on file, a copy of the paperwork, a callback to the number of record — and gets a note in the member file explaining what was accepted and why. The point of the rule is never to be rude to a grieving family. It is that nobody at the desk should have to make that judgment alone at nine at night.
One more human piece: a stopped attempt is information. When a caller hangs up rather than take the code, that goes in a log with the date, the member account they were targeting, and what they asked for. Two of those against the same account inside a month means you call the real member before something worse happens.
Any business that moves money, releases goods, or changes an account by phone is a target, and a health club does all three: refunds on prepaid packages, physical access to an unstaffed building, and payment methods changed by voice. Add unstaffed overnight hours and a young front-desk team, and you are an easier call than a bank.
Less than you think, because it only fires on money and door requests, not on "what time is the 6 a.m. class." Explain it once in the member newsletter as protection for their training balance and it reads as competence. The members who object loudest to any verification are, in practice, the ones worth verifying.
Then it becomes an in-person visit with a photo ID, or a documented email exchange from the address on file plus a callback. That is a small inconvenience for a real person and a wall for someone with a cloned voice, which is exactly the trade you want.
Recording is useful evidence and useless prevention — the money is gone by the time you listen. Also check your state's consent rules before you record at all. Verify first, record second.
CallSphere builds AI voice and chat agents that answer club phone lines and web chat, book intro sessions and tours, and capture leads around the clock. The relevant part here is where the agent stops: it can answer hours, class times and hold status all night, but a request that moves money or opens a door triggers the one-time code to the number already on file and goes to a human, with the whole conversation written into the member record for the GM to read in the morning.
Written by
Sagar Shankaran· Founder, CallSphere
LinkedInSagar Shankaran is the founder of CallSphere, where he builds production AI voice and chat agents deployed across healthcare, hospitality, real estate, and home services. He writes about agentic AI, LLM engineering, and shipping voice agents that handle real calls in production.
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