When processing travel bookings for customers, you retain key travel information, such as hotel, flight, and rentals, about your customer at the time of purchase. While your fraud teams are best equipped to detect potentially fraudulent activity, we can also use those details to help prevent fraud.
To improve our efforts to mitigate fraud, we’ve updated our APIs to collect all relevant travel metadata to help us better determine potential risks associated with a transaction. This additional information also helps fine-tune our credit decision-making systems to increase customer approvals.
## Customer signals
There are many types of fraud signals, some of which are easy to identify with the customer information. Some of the most common [customer fraud signals](🔗) are:
Inconsistencies in customer details across multiple purchases (e.g., using different email addresses for purchases)
A new or guest user
No purchase history
Their identity was not verified
Many payments (including those that have been declined) made with:
The same card but different shipping addresses.
Many cards that use the same shipping address.
Failed payment attempts or bounced.
## Itinerary signals
There are also fraud signals around any [itinerary types](🔗): rentals, hotels, flights, etc. Customers that misuse services are more likely to be focusing and spamming the same purchase item. Having more specifics on those will help Affirm's make a better decision.
We support different details per item types. For each, we require additional information.