Besides having to balance customer satisfaction with operational losses, one of the critical challenges for retailers and e-commerce platforms is combatting fraudulent activity. Merchandise returns, for example, significantly contributed to substantial overall losses for retailers.*
Against this scenario TP leverages AI and machine learning to prevent, reduce and monitor fraud in real-time, and behavioral analytics to identify suspicious patterns in customer and employee behavior. While safeguarding your customer data from tampering and data breaches.
Don’t compromise. Respond effectively to fraud red flags. Improve your fraud detection, prevention and monitoring capabilities with TP today.
Payment Fraud: combat increasing credit card fraud, chargeback disputes and unauthorized transactions.
Refund and Return Fraud: address scams related to refunds, exchanges, and fake returns.
Cybersecurity Risks: protect customer data and sensitive business information from breaches.
Gift Card, Promotion and Loyalty Fraud: recognize and stop scams involving retail gift cards.
Vendor and Supplier Fraud: prevent procurement fraud in supply chains.
Insider Threats: detect and address fraudulent activity by employees.
Inventory Shrinkage: understand and combat theft, loss, and mismanagement.
Besides having to balance customer satisfaction with operational losses, one of the critical challenges for retailers and e-commerce platforms is combatting fraudulent activity. Merchandise returns, for example, significantly contributed to substantial overall losses for retailers.*
Against this scenario TP leverages AI and machine learning to prevent, reduce and monitor fraud in real-time, and behavioral analytics to identify suspicious patterns in customer and employee behavior. While safeguarding your customer data from tampering and data breaches.
Don’t compromise. Respond effectively to fraud red flags. Improve your fraud detection, prevention and monitoring capabilities with TP today.
Payment Fraud: combat increasing credit card fraud, chargeback disputes and unauthorized transactions.
Refund and Return Fraud: address scams related to refunds, exchanges, and fake returns.
Cybersecurity Risks: protect customer data and sensitive business information from breaches.
Gift Card, Promotion and Loyalty Fraud: recognize and stop scams involving retail gift cards.
Vendor and Supplier Fraud: prevent procurement fraud in supply chains.
Insider Threats: detect and address fraudulent activity by employees.
Inventory Shrinkage: understand and combat theft, loss, and mismanagement.
|
Transactions
|
|
After-sales
|
|
Onboarding
|
|
Listing evaluation
|
|
Account management, back office
|
|
Social media
|
|
Loyalty program management
|
|
|
Transactions
After-sales
Onboarding
Transactions
After-sales
Onboarding
Listing evaluation
Account management, back office
Social media
Loyalty program management
Transactions
After-sales
Onboarding
Our client, a global fast fashion apparel company with a wide portfolio of brands, sells their products across numerous markets worldwide through e-commerce. They experienced a significant increase in refund trends during major sales events, with a high proportion of orders being refunded, and the reasons for refunds remaining unclear.
Our goal: to conduct root causes analysis for refunds and design an actionable plan
Descriptive and analytical modeling: applied AI, ML (Machine Learning) using gradient boosting regression to assess refund attributes.
Predictive modeling: to predict probable refund percentage and find the key drivers that impacted refund percentage.
Top attributes of predictive model by Order: delivery company, product category, and product brand.
Top attributes of the predictive model by product: color, brand, return recency.
Descriptive and analytical modeling: applied AI, ML (Machine Learning) using gradient boosting regression to assess refund attributes.
Predictive modeling: to predict probable refund percentage and find the key drivers that impacted refund percentage.
Top attributes of predictive model by Order: delivery company, product category, and product brand.
Top attributes of the predictive model by product: color, brand, return recency.
Digital adoption
Gain a competitive edge by leveraging data analytics, AI, virtual assistants, ML, and process automation.
Omnichannel integration
Purchases anytime through their preferred means. Provide a seamless shopping experience for your customers by integrating offline purchases and online history in real time.
Social media listening
Implement a comprehensive social media monitoring, moderation, and community engagement strategy to foster a healthy and positive environment for all.
Combat misinformation
Monitor and act against false or misleading services or product information online.
Reputational
Build your brand reputation with legit brand reviews and social media mentions.
Regulatory
Adhere to regulations for content, advertising, and transparent use of algorithms.
Allow us to assist you in enhancing your business flexibility and adaptability.
Learn how we partner with the largest e-commerce brands across the globe to guarantee digital trust, safety, and growth. Discover how we ensure business continuity while meeting all your objectives and KPIs, even in the event of unforeseen shifts in demand.
