As the digital world continues to evolve, merchants are battling various types of fraud to protect both their customers and their bottom line. As fraudsters become more sophisticated and target businesses even earlier in the transaction process, merchants need to take a multi-layered approach to weed out bad actors and bad transactions alike.
Ekata’s latest update to the Transaction Risk API is built to help businesses do exactly this: identify fraud early in the transaction flow for all types of purchases.
Why Stop Fraud Early
Identifying fraud early in the transaction process can help eliminate some of the less obvious fraud costs for many merchants. This includes:
- Potential revenue loss due to poor customer experiences. Customers expect a fast and secure shopping experience. Ensuring a seamless, friction-free user experience will help increase an existing customer base, improve retention, and boost customer lifetime value and sales.
- False declines. Many legitimate transactions are falsely identified as fraudulent as a result of inaccurate risk management. Even one good customer turned away is too many. Reducing false declines can help increase approval rates while minimizing customer friction.
- Time-consuming and unoptimized manual review processes. When a transaction requires manual review and verification, businesses lose time and money. Removing bad transactions early allows your agents to be more efficient and review transactions that actually require another level of oversight.
Transaction Data that Exposes Fraudulent Activity
Transaction Risk API provides critical insights to help you confidently assess the risk of any transaction using the following data:
- Risk flags and scores – Model-derived signals that predict the risk of each customer
- Network signals – Usage patterns of elements that suggest fraudulent or legitimate customer activity
- Match statuses to name – Confirmation that those details provided in each transaction are associated with the customer-provided name
- Validity checks for payment details – Authentication of both billing and shipping details provided by the customer
- IP Distance from address calculations – Distance calculation of your customer’s IP and their provided address
- Enriched phone metadata – Insight into line type of a phone number (often a strong indicator for fraud)
All these data points can be used in your risk models or rules systems to help you isolate fraudulent transactions before or after authorization occurs.
From account opening and sign up to the post-authorization of a transaction, merchants must optimize their fraud systems. By setting up checkpoints at various points in the customer workflow, merchants can stay ahead of fraudsters and catch bad behavior before it occurs. For all transactions, you can rely on Ekata’s Transaction Risk API to help you isolate fraud early in the transaction flow and ultimately reduce downstream costs, increase approval rates, and optimize your customer’s digital experience.