WSO2Con EU 2015: Catch Them in the Act: Fraud Detection With WSO2 Analytics Platform
•
1 j'aime•572 vues
WSO2Con EU 2015: Catch Them in the Act: Fraud Detection With WSO2 Analytics Platform Presenter: Seshika Fernando Technical Lead, WSO2
Recommandé
Recommandé
Contenu connexe
En vedette
En vedette (20)
Similaire à WSO2Con EU 2015: Catch Them in the Act: Fraud Detection With WSO2 Analytics Platform
Similaire à WSO2Con EU 2015: Catch Them in the Act: Fraud Detection With WSO2 Analytics Platform (20)
Plus de WSO2
Plus de WSO2 (20)
Dernier
Dernier (20)
WSO2Con EU 2015: Catch Them in the Act: Fraud Detection With WSO2 Analytics Platform
- 1. Catch them in the Act Fraud Detec+on with WSO2 Analy+cs Pla:orm Seshika Fernando Technical Lead WSO2
- 2. Bad News $4 Trillion in Global Fraud Losses That’s 5% of Global GDP
- 3. Good News WSO2 Analy9cs Pla;orm + Domain Exper9se ≈ Digital Sherlock
- 4. Domain Exper+se Generic Rules
- 5. Typical Fraudster • Use stolen cards • Buy Expensive stuff • In Large Quan++es • Very quickly • At odd hours • Ship to many places • Get rejected oSen Siddhi Queries
- 6. from e1 = Transac+onStream -‐> e2 = Transac+onStream[e1.cardNo == e2.cardNo] <2:> within 5 min select e1.cardNo, e1.txnID, e2[0].txnID, e2[1].txnID insert into FraudStream Transac9on Velocity
- 7. The False Posi9ve Trap Rich guy GiS giver Impulse Shopper Night owl Many girlfriends? ๏ So what if I buy Expensive stuff ๏ And why can’t I buy a lot ๏ Very Quickly ๏ At odd hours ๏ Ship to many places Blocking genuine customers could be counter produc9ve and costly
- 8. How to avoid False Posi9ves • Use combina+ons of rules • Give weights to each rule • Single number that reflects many fraud indicators • Use a threshold to reject transac+ons • You just bought a Diamond Ring? • You bought 20 Diamond Rings, in 15 minutes at 3am from an IP address in Nigeria?
- 9. How to score Score = 0.001 * itemPrice + 0.1 * itemQuan+ty + 2.5 * isFreeEmail + 5 * riskyCountry + 8 * suspicousIPRange + 5 * suspicousUsername + 3 * highTransac+onVelocity
- 10. Are we safe ?
- 11. Markov Models • Model randomly changing systems • Detect rare ac+vity sequences using • Classifica+on • Probability Calcula+on • Metric Calcula+on
- 12. Fraud Detec9on in Real-‐9me • Encode Domain Knowledge into Generic Rules • Use Fraud Scoring to reduce False Posi+ves • Use Markov Modelling to detect rare pakerns
- 17. Dig using Big • Provide access to historical data to dig deeper • Make querying and filtering easy and intui+ve • Provide useful visualiza+ons to isolate incidents and unearth connec+ons
- 18. Dashboard Fraud Detec9on Toolkit Events Events Events Events
- 19. Payment Fraud Dashboard Transac+ons Transac+ons Transac+ons Transac+ons Payment System
- 20. An9 Money Laundering Dashboard Bank Txns Bank Txns Bank Txns Bank Txns Core Banking System
- 21. Iden9ty Fraud Dashboard Events Events Events Events WSO2 Iden+ty Server
- 23. Thank You