toronto area sas society december 8, 2006 how one can use sas to easily manage an otherwise...
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Toronto Area SAS Society
December 8, 2006
How One Can Use SAS to Easily Manage an Otherwise Unmanageable Task
Dr. Arthur S. TabachneckDr. Arthur S. TabachneckInsurance Bureau of CanadaInsurance Bureau of Canada
Statistical Research and Development DepartmentStatistical Research and Development Department
Toronto Area SAS Society
December 8, 2006
IBC’s Department of Statistical Research and Development
• Manage databases which include all government and non-government auto insurers’ premium and claims information
• Build and maintain a database of Vehicle Information Numbers (VINs) and the vehicle characteristics they represent
• Assist other IBC divisions with all needed analytical services
• Conduct research to identify emerging trends
• Develop and apply statistical models to estimate anticipated claims and related costs
• Provide advisory make/model/model year-specific Collision, Comprehensive, Property Damage and Accident Benefit ratings for all Canadian insurers
Toronto Area SAS Society
December 8, 2006
Insurance 101
IBC
ICBC
SGI
Data
Including:
Vehicle Information Number (VIN)premium/vehicle/coverage
# of claims/vehicle/coveragecost of claims/vehicle/coverage
MPI
GAA
SAAQ
Toronto Area SAS Society
December 8, 2006
0.25 mil vehicles
0.076 mil vehicles
0.53 mil vehicles
0.45 mil vehicles
4.2 mil vehicles
6.8 mil vehicles
0.62 mil vehicles
0.66 mil vehicles
2.2 mil vehicles
2.2 mil vehicles
0.024 mil vehicles
How much data is involved?
0.003 mil vehicles0.021 mil vehicles
Toronto Area SAS Society
December 8, 2006
How much data is involved?
# of Records = 18,123,885 × 10 = 181,238,850# of Records = 181,238,850 × 12 = 2,174,866,200# of Records = 40 × 2,174,866,200 = 86,994,648,000
Toronto Area SAS Society
December 8, 2006
Loss Cost =
Total Claim Costs× -------------------------- # of Claims
Total Claim Costs ------------------------ = # of Vehicles
Likelihood of a claim
Average claim cost # of Claims ------------------- # of Vehicles
Insurance 101
Toronto Area SAS Society
December 8, 2006
One’s Driving Record
One’s Age
Where One Lives
Cost of Insurance
The Vehicle
How Much One Drives
Total PremiumCLEAR Rating
Insurance 101
Toronto Area SAS Society
December 8, 2006
Collision coverage: the costs involved when one is “at fault” in an accident
Can’t just look at how much a vehicle costs Toyota Corolla MSRP $16,404
Relative Loss Cost = 115
The Problem
Mitsubishi LancerMSRP $15,555
Relative Loss Cost = 650
Toronto Area SAS Society
December 8, 2006
Chevrolet Avalanche 1500MSRP $35,938
Mercedes-Benz C230 MSRP $36,386
Relative Theft Frequency = 74
The Problem
Theft Frequency (the likelihood of a vehicle being stolen)Can’t just look at how much a vehicle costs
Relative Theft Frequency = 238
Toronto Area SAS Society
December 8, 2006
The added cost of features which reduce insurance claim costs should not result in higher premiums
Traction ControlABS
Seat Belt PretensionersTheft Deterrent Systems
Restraint Systems
Stability Control
The Problem
Toronto Area SAS Society
December 8, 2006
Insurance rates must be available before insurance experience is known
The Problem
Toronto Area SAS Society
December 8, 2006
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
•Body style
•Drivetrain
•Wheelbase
•Weight
•Engine displacement
•Engine horsepower
•MSRP
•Indexed MSRP
•Type of brakes
•Theft deterrent system
•Track width
•Height
•Types of airbags
•Manufacturer
•Seating capacity
•Brake assistance
•Ground clearance
•Traction control
•Stability control
•Types of headrestraints
•Seatbelt pretensioners
•Lane departure warning
•Tracking system
•Parts marking
•Engine type
•Engine placement
•Age
•General model and model
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
Assu re reasonab ility o f insu rance da ta(fo r a ll cove rages)
Stat Plans Error CheckingAccuracy Checks Reasonability Checks
# Exposures Prem ium s # Cla im s Loss
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
CLEAR - How it works
Toronto Area SAS Society
December 8, 2006
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Co n v e rt Ad jRLCs to Rate G ro u p s
Rate Gro u p =1*(Ad jRLC<34.5)+(Ad jRLC/10-1.95)*(34.5<=Ad jRLC<=304)+(Ad jRLC/20+13.275)*(Ad jRLC>304)
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Co n v e rt Ad jRLCs to Rate G ro u p s
Rate Gro u p =1*(Ad jRLC<34.5)+(Ad jRLC/10-1.95)*(34.5<=Ad jRLC<=304)+(Ad jRLC/20+13.275)*(Ad jRLC>304)
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Acco mplishRe v e rsal Co n tro l
Assu re re v e rsalsare ju stifie d
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Balan ce Tab le
Ad ju st RLCsto ach ie v erate le v e ln e u trality
Acco mplishRe v e rsal Co n tro l
Assu re re v e rsalsare ju stifie d
Co n v e rt Ad jRLCs to Rate G ro u p s
Rate Gro u p =1*(Ad jRLC<34.5)+(Ad jRLC/10-1.95)*(34.5<=Ad jRLC<=304)+(Ad jRLC/20+13.275)*(Ad jRLC>304)
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Balan ce Tab le
Ad ju st RLCsto ach ie v erate le v e ln e u trality
Acco mplishRe v e rsal Co n tro l
Assu re re v e rsalsare ju stifie d
Co n v e rt Ad jRLCs to Rate G ro u p s
Rate Gro u p =1*(Ad jRLC<34.5)+(Ad jRLC/10-1.95)*(34.5<=Ad jRLC<=304)+(Ad jRLC/20+13.275)*(Ad jRLC>304)
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Balan ce Tab le
Ad ju st RLCsto ach ie v erate le v e ln e u trality
Acco mplishRe v e rsal Co n tro l
Assu re re v e rsalsare ju stifie d
Co n v e rt Ad jRLCs to Rate G ro u p s
Rate Gro u p =1*(Ad jRLC<34.5)+(Ad jRLC/10-1.95)*(34.5<=Ad jRLC<=304)+(Ad jRLC/20+13.275)*(Ad jRLC>304)
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Ap prov alPro ce ss
Ens ure RateLe ve l Ne utralityand Acce ptable
Dis location
Canadian Loss Experience Automobile Rating (CLEAR)
Toronto Area SAS Society
December 8, 2006
Canadian Loss Experience Automobile Rating (CLEAR)
How?
Toronto Area SAS Society
December 8, 2006
How?: Design appropriate directories and filename structures
ARQC3001.sas7bdat
Type of Run Measure
ProvinceCoverage
Version
Toronto Area SAS Society
December 8, 2006
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Balan ce Tab le
Ad ju st RLCsto ach ie v erate le v e ln e u trality
Acco mplishRe v e rsal Co n tro l
Assu re re v e rsalsare ju stifie d
Co n v e rt Ad jRLCs to Rate G ro u p s
Rate Gro u p =1*(Ad jRLC<34.5)+(Ad jRLC/10-1.95)*(34.5<=Ad jRLC<=304)+(Ad jRLC/20+13.275)*(Ad jRLC>304)
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
How?: Build SAS macros to accomplish each task
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
Toronto Area SAS Society
December 8, 2006
How?: Use SAS AF to let users indicate requirements
Toronto Area SAS Society
December 8, 2006
How?: Use SAS AF to let users indicate requirements
Toronto Area SAS Society
December 8, 2006
Est Cla im s=Actua l # Cla im s le ss e ffe ctsdue to ta riffs &/or discounts
Est Loss=Actua l Loss le ss e ffe cts dueto due to ta riffs &/or discounts
Build /Incorpo rateData Normalization M od e ls
De v e lo p /Re v ie w /Ap p lyStatistical M o d e ls
De v e lo p an d ap p ly fo rmu laeto e stimate n o rmalize d claim
fre q u e n cy an d se v e rityfro m v e h icle ch aracte r istics
Pro je ct Pu b lica tio n Ye a r F le e t
Use link m ode l ba se d on thre em ost re ce nt a ccide nt ye a rs'
e x posure s (a s a t De ce m be r 31stof e a ch ye a r), curre nt ye a r
e x posure s (a s a t June 30th), a ndsa le s e stim a te s
Ad ju st RLCs fo r Risk Lo ad ing an dco ntro l chan ge w ith p r io r RLC
Ad jRLC=(ip r ice >=65k)*[EstRLC((ip r ice -45k)/i5k)*10]
Balan ce Tab le
Ad ju st RLCsto ach ie v erate le v e ln e u trality
Acco mplishRe v e rsal Co n tro l
Assu re re v e rsalsare ju stifie d
Co n v e rt Ad jRLCs to Rate G ro u p s
Rate Gro u p =1*(Ad jRLC<34.5)+(Ad jRLC/10-1.95)*(34.5<=Ad jRLC<=304)+(Ad jRLC/20+13.275)*(Ad jRLC>304)
De ve lop a nd m a inta inve hicle cha ra cte ristics
W he e lba se : 2718 TDS: NoW e ight: 1889 S tyle : S UVDrive tra in: 4 ABS: Ye sPrice : $43,356 Doors: 4VCODE: 6706 Ye a r: 2007Airba g: Ye s Pow e r: 190
Assu re re aso n ab ility o f in su ran ced ata (fo r a ll co v e rag e s)
Sta t P la ns V IN De codingError Che cking Re a sona bility Che ck
# Ex posure s P re m ium s # Cla im s Loss
Calcu lateLC & Re l LC
(Ad jEstF *Ad jEstS)/
W t Av g LC
Adjust e stimate s tore fle ct actual e xpe rie nce
Ad jESTF=ESTF(1+M AFF)Ad jESTS=ESTS(1+M AFS)
How?: Incorporate SCL to run each macro
Toronto Area SAS Society
December 8, 2006
How?
• Understand the problem
• Planning
• Design
• SAS Macros
• SAS AF
• SAS Component Language
Toronto Area SAS Society
December 8, 2006
Questions?