Tham khảo tài liệu 'project management risk and customer relationship_7', khoa học xã hội, kinh tế chính trị phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Page 253 Table RelationshipofOddstoScaleeRiskScoree PROBABILITY GOOD LOG DERIVED OF TO OF RISK BAD BAD ODDS ODDS SCORE 1 1 480 2 1 520 1 540 4 1 560 1 580 8 1 600 1 620 16 1 640 1 660 32 1 680 1 700 64 1 720 1 740 128 1 760 1 780 256 1 800 rts 20 row float box Risk Score V run Z y Figure depicts gnnd newt fnr Eastern Telan. Mntt nf First Reserve s customers have a relatively low risk level. If Eastern selects all names with a score of 650 nr above it will have almost 125 000 low-risk First Reserve customers tn solicit. A Different Kind of Risk Fraud The main focus of this chapter has been on predicting risk for default on a payment. And the methodology translates very well to predicting the risk of claims for insurance. There is another type of risk that also erodes profits the risk of fraud. Losses due to fraud cost companies and ultimately consumers millions of dollars a year. And the threat is increasing as more and more consumers use credit cards telecommunications and the Internet for personal and business transactions. Team-Fly Page 254 I-----------------------------------------------------1------------------------------------1------------------------------------1 1 Risk Seo re Ị I 1 Customers 1 Predieted 1 Probability j 450 500 1 42. on 1 500 550 1 25 B6 1 1550 - 6Ũ0 1 2 638 - 1 1 I 1 1 aoo - 050 20 6531 I 550-700 56 860I 3 20 I 1700 - 750 I 07 5521 I Total L 1 1 1 1 1 Figure Tabulation of risk scores. Jaya Kolhatkar Director of Fraud Management for discusses the mechanics of developing fraud models and the importance of proper implementation Fraud in the e-tailing world has increased rapidly over the past two years. Being a virtual marketplace most of the fraud checks in the physical retail
