Stop Fraud in Its Tracks – Protect Your Revenue with Predictive Analytics
Fraudulent transactions and chargebacks can bleed a business dry, not only in lost revenue but also in fees, inventory loss, and damage to your reputation. Traditional fraud prevention often feels like a game of whack-a-mole: you set up rules and checkpoints based on the last scam you saw, only to be hit by a new tactic the next week.
And reviewing transactions manually? That’s like finding needles in a haystack – slow, expensive, and error-prone.
Pecan’s Fraud & Chargeback Prevention solution offers a smarter, proactive defense. It uses AI to predict which transactions or customers are likely fraudulent or high risk, so you can stop fraud before it causes loss. Think of it as an intelligent shield that’s learning from your data – catching patterns far too complex for static rules, and doing it in real-time. It’s simple and fast for your existing team to implement (no need to hire a squad of fraud data scientists), and it continuously adapts to outsmart fraudsters’ evolving tricks. With Pecan, you move from being reactive to staying one step ahead of fraud, all while minimizing false alarms that inconvenience good customers. Your finance and risk teams will sleep easier, and your bottom line will thank you.
Every fraudulent order or chargeback hits your revenue directly. Whether it’s stolen goods, refunded charges, or penalty fees from payment processors, these losses add up quickly. For many businesses, fraud is not an occasional nuisance but a significant drain that can be a few percent of revenue if not managed.
Fraudsters are constantly finding new ways around filters – from using synthetic identities to exploiting loopholes in payment systems. Rule-based fraud systems struggle to keep up; by the time you add a new rule for the latest scheme, bad actors have moved to the next tactic. This cat-and-mouse dynamic means your defenses might always lag behind without a more adaptive solution.
Crude fraud rules (e.g., block all orders over $1000 from a new account, or flag transactions from X country) can cast too wide a net. They may catch fraud, but they also snare legitimate customers, causing frustration, order delays, or wrongful declines. False positives not only hurt customer experience but also mean lost sales that should have been approved.
Many companies resort to teams of analysts manually reviewing flagged transactions or accounts. This process is slow and doesn’t scale – during peak times (like holiday sales), queues back up, and either reviews get rushed (letting fraud slip through) or orders get delayed (angering good customers). Plus, manual review is costly in terms of labor and still prone to human error or inconsistency.
Even when businesses have data that could help spot fraud (past order history, IP addresses, device info), it’s often siloed and not fully utilized in real-time. Implementing a sophisticated fraud model in production can be technically challenging, leading companies to rely on simpler, but less effective, methods. This gap leaves money on the table – or rather, in the fraudster’s pocket.
Pecan’s Fraud & Chargeback Prevention solution brings a proactive, intelligent approach to safeguarding your transactions. At its core is a machine learning model trained on your historical transaction data – including order details, user behavior, payment information, and prior fraud/chargeback cases. It learns the subtle signals that differentiate fraudulent activity from legitimate transactions.
Once in place, Pecan will score each incoming transaction or account for fraud risk. If something looks suspicious (say, an order that matches patterns of past fraudulent ones), it flags it for review or automatic blocking before the transaction is completed. This means you’re always a step ahead, catching new schemes that simple rules-based systems would miss.
Importantly, Pecan’s AI is adept at minimizing false positives by considering a wide range of factors together – it might recognize that while an order is high-value (normally risky), the combination of a long customer history and matching shipping/billing addresses makes it likely legit, so it doesn’t flag it. This nuanced understanding keeps good orders flowing smoothly while stopping bad ones. And there’s no heavy lift for your team: Pecan’s platform is intuitive and easy to integrate via API or connectors, plugging into your e-commerce, payments, or ERP system to ingest data and output risk scores. Your analysts can configure workflows like “if risk score > 0.9, hold for review, if >0.98, auto-cancel” etc., within your existing order management.
Pecan also provides interpretable insights – for instance, highlighting which factors contributed to a high-risk score (e.g., “Card BIN country mismatch with IP location”), so your team understands the why and can refine processes if needed. Additionally, this solution addresses chargebacks specifically by predicting which customers or transactions are likely to result in a chargeback (maybe due to friendly fraud or service disputes) so you can proactively intervene, such as contacting the customer or requiring additional verification. It’s a comprehensive shield: fast, adaptive, and intelligent, deployed quickly using your current team and data. In short, Pecan gives you the peace of mind that you’re not leaving the door unlocked for fraud – it’s proactively guarding it.
Catch fraudulent transactions before approval. Pecan’s model evaluates each transaction fast, assigning a fraud likelihood score. High-risk orders can be automatically blocked or queued for review, preventing chargebacks and losses upfront rather than after the fact. This proactive stance can drastically reduce fraudulent completions in your system.
Increase the accuracy of fraud flags, so you stop bad actors without turning away good customers. By analyzing dozens of data points simultaneously, the model can better distinguish legitimate purchases from fraudulent ones, leading to far fewer “false alarms.” For example, instead of blocking all big orders from international cards (which could alienate valid customers), Pecan might identify a specific risky fingerprint that truly correlates with fraud. Your genuine customers enjoy seamless purchases, and your fraud team isn’t bogged down chasing ghosts.
You don’t need a specialized data science unit to deploy this. Pecan’s platform is built for business and data teams to use directly. In fact, most teams can get an initial fraud model up and running in a matter of days using their historical data – often seeing results (fraud catch rate improvement, false positive reduction) within the first few weeks of use. This speed to value is a game-changer, especially if you’re currently suffering losses; you can start plugging the leak almost immediately. And because it’s intuitive with easy integrations, it slots into your existing tech stack without months of IT projects.
By preventing fraud and chargebacks more effectively, Pecan saves you money directly – less lost product, fewer chargeback fees/fines, and potentially lower insurance or compliance costs related to fraud. It’s also far less expensive than hiring a team of fraud experts or investigators (and works 24/7 tirelessly). Pecan’s pricing is typically a fraction of what a single data scientist’s salary would be, yet it delivers enterprise-grade machine learning power. Additionally, as your business grows, the solution scales effortlessly. Whether you’re processing hundreds or millions of transactions, the AI can handle it without a linear increase in cost or effort, unlike manual review teams.
Book a demo of Pecan’s fraud prevention solution and see how you can outsmart fraudsters, protect your business, and save money – all with the team and data you have right now.
