Nearly 40% of customers who face a declined legitimate transaction never return to the brand, a ripple effect that translates into lost lifetime value. The challenge lies in preventing fraud without alienating loyal shoppers. Fortunately, advancements in AI and machine learning (ML) offer a way forward.

The cost of false declines and the need for balance

False declines often emerge from the difficulty of distinguishing between risky but legitimate transactions and actual fraud. Merchants may overcorrect by taking overly cautious authentication measures, only to drive away customers with excessive verification steps. Requiring every shopper to undergo intense scrutiny slows down checkout and increases cart abandonment. At the same time, overlooking security puts businesses at significant risk of fraud.

The solution lies in striking a dynamic balance. Tools with adaptive checkout flows and AI-powered fraud detection can assess orders on a case-by-case basis. By tailoring responses to an order’s risk profile, merchants can ensure smooth experiences for trustworthy customers while challenging high-risk transactions that aren't safe enough to approve as is.

Smarter security while maintaining seamless checkout

AI-driven fraud prevention tools like Adaptive Checkout by Riskified revolutionize the shopping experience by balancing security with convenience. Trained on vast amounts of global merchant data, Adaptive Checkout can detect suspicious behaviors – from established fraud patterns as well as emerging threats – with precision.

By analyzing each transaction’s risk, low-risk orders move through checkout with ease, while high-risk ones prompt additional verification like 3DS or one-time passwords. For instance, a returning shopper with a stored credit card won’t be asked to re-enter their CVV unless genuinely required. By minimizing unnecessary friction, legitimate shoppers are encouraged to complete purchases.

Tailoring fraud solutions to unique business needs

Every business has its own risk profile and operational nuances, and fraud prevention should reflect that. Effective AI-powered solutions are deeply customizable, addressing specific concerns like policy abuse, serial returns, and chargeback fraud.

For instance, merchants can choose to focus on pre-authorization or post-authorization fraud reviews, or even use a combination of both, based on their specific needs and risk levels. They can also implement region-specific or vertical-specific fraud models to meet their unique needs. A high-end marketplace may favor strict verification steps for rare items, while a fast-fashion retailer might focus on speed and efficiency.

Customization extends even further. Merchants can adjust settings like authentication time frames, verification methods, and thresholds for intervention. This flexibility ensures a business’s approach aligns with its operational priorities, whether it’s reducing fraud, streamlining processes, or enhancing customer satisfaction.

Fraud prevention as a growth engine

Merchants can turn fraud prevention from a hurdle into a catalyst for revenue growth. The key lies in treating fraud prevention as a collaborative, data-informed strategy designed to future-proof operations and deliver unparalleled customer experiences.

Proper fraud prevention tools intercept fraudulent attempts at an early stage, safeguarding transactions before they reach authorization. At the same time, enriched data insights empower issuing banks to make better-informed decisions, improving the accuracy of approvals.

With fewer false declines and a secure transaction process, businesses build trust with both customers and financial partners. This strategic alignment results in higher approval rates, and optimized checkout processes that drive more sales.