🚀 CONFIG 2026 is just around the corner! ^^ I'm traveling from Vietnam to San Francisco with a group of colleagues to attend CONFIG. As you can imagine, planning a multi-person trip across different cities, events, and schedules can get complicated very quickly. Some activities we'll attend together. Some we'll join individually. Some events are official CONFIG sessions, while others are community meetups, networking gatherings, or spontaneous adventures around the Bay Area. To keep everything organized, I built a Travel Plan Tracker: 👉 https://travel-timeline-tracker.figma.site/ What started as a simple itinerary quickly evolved into a shared travel management tool that helps us: ✈️ Track our flights and travel mindmap/timeline 📅 Manage both shared and individual schedules 📍 Save places we want to visit along the way 🤝 Keep track of events, meetups, and networking opportunities 💰 Manage trip expenses and split shared bills fairly among the group 📖 Download *.docx itinerary for visa/immigration procedure. If you're attending CONFIG this year, drop your itinerary, side events, meetups, workshops, dinners, or travel plans in the comments. Feel free to add them to the tracker as well. And here's a fun detail about my trip: 🇹🇼 I'll be transiting through Taipei and spending one night there on June 18 before flying to San Francisco.

If you're also passing through Taipei, living there, or happen to have a similar itinerary, let's meet up and explore the city together before CONFIG begins! I'd also love to connect with other CONFIG attendees.

See you in Taipei and San Francisco! 🇹🇼✈️🇺🇸✨

#Config2026 #Figma #Contra #Makeathon #UXDesign #UIDesign #ProductDesign #DesignCommunity #SanFrancisco #BayArea #Taipei #TravelPlanner #Network

the level of organization here is impressive ✨

Fraud doesn’t always look suspicious, until you analyse the patterns. I recently worked on a Vehicle Insurance Claim Fraud Analysis case study where the goal was simple: 👉 identify hidden risk signals and process gaps that allow fraudulent claims to slip through. 🔍 The problem Insurance teams deal with thousands of claims, but: • Fraud is often buried inside normal-looking transactions • Manual checks miss systemic weaknesses, not just bad actors • High-risk signals are rarely quantified clearly So I approached this as a real-world fraud analyst, not just a dashboard exercise. 🛠️ What I did (end-to-end) Using Excel analysis, I: • Cleaned and structured claim-level data • Defined fraud-focused KPIs, not vanity metrics • Built an interactive dashboard with slicers to simulate decision-making 📊 Core KPIs tracked • Fraud Rate (%) • Total Fraud Cases • Average Driver Risk Rating (Fraud) • Police Report Gap (%) - fraud claims filed without police reports 🚨 Key insights discovered • Fraud concentration varied strongly by vehicle price band, not just volume • Certain vehicle categories consistently showed higher fraud exposure • An alarming 97%+ of fraudulent claims lacked police reports, highlighting a major verification gap • Driver risk ratings provided early signals that could support preventive controls These insights aren’t theoretical, they point directly to where insurers are leaking money. 💡 Business impact (how this helps) This type of analysis helps organisations: • Flag high-risk claims earlier • Strengthen fraud prevention rules • Improve compliance and documentation checks • Reduce payout losses without increasing manual workload 🧠 Tools & skills applied Excel (Advanced Pivot Analysis) Fraud & Risk Analytics Dashboard Storytelling Business Intelligence Thinking I’m building and sharing real fraud analytics case studies as I continue to grow in this space, focusing on credit card, insurance, and transaction fraud. If you’re a: • Fraud / Risk Manager • Insurance or FinTech team • Founder needing data-driven fraud insights I’m open to conversations and collaboration. #FraudAnalytics #FraudDetection #RiskAnalytics #BusinessIntelligence #ExcelDashboard #DataAnalytics #BuildInPublic

wow this is very insightful