The setting
's runs in the cloud. It covers travel policies, approvals, and bookings of hotels, flights, cars and rail.
Blocking linked account-takeover bookings protects payment loss but can strand urgent travelers.
Fraud containment depends on acting across linked signals, while enterprise travel depends on legitimate urgent bookings clearing.
Who you’d be doing this for
“My traveler was headed to a client meeting when the ticket disappeared, and finance asked whether the card was compromised.”
Marie Visser · Corporate Travel Manager · a character in this brief
Oversees urgent travel and payment controls for an enterprise program affected by false blocks and disputed charges.
What is at stake
Linked account-takeover bookings could create $1.2 million in monthly payment exposure. You must choose a production intervention that contains the ring without cutting off legitimate urgent travel.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- fraud loss containment vs urgent travel continuity
- linked-signal coverage vs case-level proof
- real-time intervention vs booking reliability
- risk appetite vs enterprise escalation load
Why Navan
Corporate-card travel payments connect booking, identity, and expense activity, so a linked fraud pattern can move across the platform quickly.
Written with these in mind
Not your kind of problem? 61 more at Navan, or browse every organization.
Where the organization context comes fromThe postings this brief was written from, and the reporting read before it.
The organization context comes from public information. The situation and characters are written for the brief.
Job postings it was written from
Public descriptions of the work at Navan. They are listed as sources, not as openings. The lines under a posting are its own words, where it meets this brief.
- Senior Data Scientist, Fraud Operations (opens in a new tab)
- Lead the design and development of advanced ML and statistical models to detect, predict, and prevent fraudulent behavior across onboarding, payments, and expense workflows.
- Navan is expanding its Fraud Risk Management team to build world-class fraud detection, prevention, and analytics capabilities supporting our rapidly growing travel and expense businesses.
- Sr. Data Scientist (opens in a new tab)
- You will lead projects from discovery through delivery, combining statistical methods, software development, and AI tools to support business decisions and reshape the traveler experience across planning, booking, and support.
- Director, AI Enablement (opens in a new tab)
- Drive an AI-First Culture: Stay ahead of emerging AI tools and trends, rapidly evaluating new capabilities and demonstrating practical ways to embed AI into everyday operations.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.
Where similar work appears
Other live briefs connected to this one, and what connects them.
Similar problems at other organizations
Like this one, each of these is about money moving incorrectly, late, or twice.
Losses have risen 2.6-fold from synthetic identities that pass today's onboarding rules, and a blunt fix would reject real founders.
You set the thresholds and the review evidence before a cutover date that is already fixed.
Disputed completed trips reached $41,000 in 18 hours across 286 linked accounts.
You have to weigh immediate loss containment against permanently restricting legitimate riders on incomplete links.
One hundred eighty linked retailer accounts could push credit exposure above $4 million as pending seasonal orders clear.
You must weigh fast containment against keeping verified shops able to buy inventory.
The same setting, from another role
Each is set around Navan’s Corporate Travel Management Platform, written for a different role. They’re separate briefs, not the same scenario.
Hotel complaints are scattered across conversations, evaluation results, and bug bashes, obscuring recurring booking failures.
You have to decide where clustering of hotel evidence hands over to the PMs who frame the problem and choose what enters metric review.
Travelers abandon connected trips when they must restate their needs for each booking leg.
You must weigh a simpler planning experience against clear policy and booking boundaries.
Confirmed hotel stays are being reclassified after travelers receive booking confirmation.
You must weigh a durable audit record against a recovery path that keeps travelers housed.
Other problems with a similar purpose
In each of these, as in this one, the aim is to make complex payment systems feel dependable in the exact real-world moment someone needs to complete one.
Some New York refunds miss the lender statement window, leaving shopper balances open after a merchant approves the return.
You have to weigh a simpler merchant handoff against controls that prove every refund record arrived on time.
Approved agent purchases with changed prices are failing during authentication.
You have to weigh faster completion against a control path that bad actors could exploit.
Mobile job completion is creating duplicate charges after some technicians reconnect.
You must protect payment integrity without making field completion brittle.
