Accounting

CIEAN SWEE TD. CUSTOMER DATA patatier, 200 ? Student Work Area (position copied data here): Part 2 (c) AFDA based on "Predictive Analytics" c b i [67 mark] Hrouse (student instructions) If Compiete an eitimatre of AFDA for noch input that will go into the Credis Scam Model. 2. Cell referente the rstimated AraA from esch workthert into ite table belo 1. Calculate the "erobability of defaut" ta be applied to the amaunts tram vour phet table. GENSWEEP LFD. CUSTOMER DATA Octobec, 2023 ? \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{9}{|c|}{ October, 2023? } & & \\ \hline & Cuntioner information & \multicolumn{6}{|c|}{ Schedule of Afed Accounts lecrivabie } & \multicolumn{3}{|c|}{ Other informanen } \\ \hline firysion & Customer Name & Total AR & 150dm & \begin{tabular}{l} Cretit \\ Matins \end{tabular} & \begin{tabular}{l} Custooner \\ Amponve \\ kate (W) \end{tabular} \mid & \begin{tabular}{c} Whita-dif \\ s \end{tabular} \\ \hline wing & Harnst Maple Broducts the. & 5,700 & 900 & 4.800 & 0 & 0 & of & MA & 100c & is \\ \hline whir & Theh Valley Therapy Lte. & 10,200 & 6,600 & 2,300 & 1,200 & 0 & of & MA & & (4) \\ \hline HAAMAIS & Hifisdate invialetion cor. & 8,600 & 4,000 & 0 & 700 & 2,000 & 1,900 & ccc & sin & ion \\ \hline & Pliericane foreiry ins: & 15,200 & 0.700 & 2,200 & 0 & 2,000 & 1,400 & asa & 00% & is \\ \hline mokinar & Ivery Hotein inc: & 2,400 & 1,1000 & 600 & 0 & a & 0 & haA & ton & 2 \\ \hline & fausly Talor and Aterctions ine: & 0,100 & & 2,200 & 9 & 0 & 0 & MA & & is \\ \hline tast & Johnean'z Fumniture flefiniskine that. & 2,500 & 1.400 & 10 & 1,100 & a & 0 & aA. & uos & 28 \\ \hline \end{tabular} The consultant has proposed you use a "Credit Score Model" to estimate AFDA based chthe following inputs which should be equally weighted: (a) Aged Receivables with Customer credit rating (AAA, BBB or CCC) (b) Customer Response Rate (CRR), and (c) Customer write-off history A. Student Work Area (position copled data here): Excel ninu io: H PCommunt otdining 1 CLEN SWEER UD. CUSTOMER DATA Gatober, 2023 \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{2}{|r|}{ Cuntomer information } & \multicolumn{6}{|c|}{ Schedule of Aged Acrounts Fecelvable } & \multicolumn{3}{|c|}{ Other informathin } \\ \hline Fiedon & Cuitomer Name & Total AR. & 1 so dare. & \begin{tabular}{l} Credit \\ Mutine \end{tabular} & \begin{tabular}{l} Caistnoner \\ flesponse \\ Aate (X) \end{tabular} & \begin{tabular}{c} Write off \\ \end{tabular} \\ \hline Wis: & Clockuork Camultine tnd. & 8,400 & 7,400 & 1,000 & 0 & 0 & o & NA. & 100 & ov \\ \hline Est & Continental Shippiry Ine. & 5,500 & 2,500 & 3,000 & a & 0 & 0 & AMA & 100 . & 14 \\ \hline wist & Cointside Haquet Chib Wit: & 7,500 & 5,200 & 2300 & 0 & 0 & o & AMA & son & \\ \hline West & Crekside Aehatolitatien Centre Ltd. & 5,400 & 3,800 & 1,600 & 0 & 0 & 0 & AM & log6 & on \\ \hline ctmotikat & Decis and Docks ine. & 16,900 & 11,300 & 3,000 & 400 & a & o & AM & eas. & os \\ \hline ruinif & Delia Plimbing tra. & 8.600 & 5,100 & 0 & 700 & 2,200 & 700 & alin & 70 & s \\ \hline & Divine Desian Servaces ine. & 2.900 & 1,100 & 1,000 & 200 & 100 & 100 & a & cos & es \\ \hline \end{tabular} 2/ Estimate AFDA using the following methods: a) Default Risk applied to overall Accounts Receivable b) Default Risk applied to Aged Accounts Receivable c) Credit Score Model (using "predictive analytics") 3/ What conclusions can you make about your analysis? Does one method provide a better estimate over another? Explain. CIEAN SWEE UR. CUSTOMER DATA Oetober, 2009 Part 2 (b) AFDA based on default risk applied to Aged Accounts Receivable [10 marks] Neneconwory. Probability of Mobability of 40 divi he bo day. 91120 days ruli Finment. pericin i1 10marks]1 1 \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \\ \hline \multicolumn{2}{|c|}{\begin{tabular}{l} CUSTOMER DATA \\ October, 2029 \end{tabular}} & \multicolumn{2}{|l|}{$} & & & & & & & \\ \hline \multicolumn{2}{|r|}{ Customet information } & \multicolumn{6}{|c|}{ Schedule of Aged Accounts Recrivabie } & \multicolumn{3}{|c|}{ Other information } \\ \hline Asplon. & 2 Customer Name & Total Ag & 150dan & \begin{tabular}{l} Credat \\ Rabne \end{tabular} & \begin{tabular}{l} Curtomer \\ liespense \\ Hatn (N) \end{tabular} & White of \\ \hline & fereus Masonry Corp. & 4,800 & 2,500 & 0 & 1,100 & 700 & 300 & nats & & 4x \\ \hline cenctiul & Atfor Mll Cross Trainityn ine. & 9,100 & 6.200 & 100 & 800 & 0 & 0 & AMA & 100% & as \\ \hline contreat & Five Mankevi indoor Playeround Ltd. & 5,600 & 4.600 & 1,000 & 0 & o & 0 & ma & 904 & is \\ \hline contral & Galaxy Aeronautical Inepineering Corp. & 9.400 & 6.100 & 3,300 & 0 & 0 & 0 & MA & 100s & ok \\ \hline w: & Georse and Son Contracton ins. & 9,000 & 6,100 & 2,900 & 0 & 0 & c & haA & & is \\ \hline west & Ginger imports inc. & 4,400 & 1,100 & 2,600 & 0 & D & a & AM & gos & os \\ \hline cinmal & Golden Era Cratismen Ltd. & 3.800 & 1300 & 500 & 0 & 0 & & MM & 90s & 25 \\ \hline \end{tabular} write of ainetint by the fotal A/R. What repoin seema to be having a vendicant collectability problem? filde the total wit wraten off for alt racions. mput your resalt inse the Part 2 / warkheet 2. Uhe the information from your Fivot Tabin to complete the mussine "arntunt" information located iscolume 0 2. Calcalne the "probubility of defacol" to be opplied to the amounts from vout pirot table. input your tetuit inte the Part.2c) worksheet. What conclusions can you make about your analysis? Does one method provide a better estimate over another? Explain. CUSTOMER DATA \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{2}{|c|}{ October, 2023} & \multicolumn{2}{|l|}{} & & & & & & & \\ \hline \multicolumn{2}{|r|}{ Centomer informuation } & \multicolumn{6}{|c|}{ Schedule of Aged Accounts Alecrivable } & \multicolumn{3}{|c|}{ Other informution. } \\ \hline Eezion & Cuitomer Name & 14,200TotalAR & 150cmx & \begin{tabular}{l} Credin \\ Roting \end{tabular} & \begin{tabular}{l} Custumet \\ Response \\ Rate py \end{tabular} & \begin{tabular}{c} Write-ent \\ x \end{tabular} \\ \hline Centiat & Dinfer Fabricatons inc & 6,900 & 6,900 & 0 & o & o & o) & uA & 100% & is \\ \hline 105T: & Bnar Logistics ita. & 0,100 & 6,400 & 800 & 1,900 & 0 & o) & m & 906 & is \\ \hline CONTAAL & Della Granite inc. & 4,700 & 2,400 & 0 & 2,300 & 0 & o) & MA & sons & on \\ \hline EAST & Bif Screen fntertainment ttd. & 6,000 & 4,800 & 1200 & & 0 & of & M. & sin & m \\ \hline CENTRA: & find Duct Cleaning ine. & 7,700 & 5,700 & 200 & 1,800 & 0 & of & Mn & 100% & 2s \\ \hline bas & Glun Plate Canering Services tid. & 15,300 & 9,800: & 4500 & 400 & 0 & 600 & ma & lon & JN \\ \hline ASte & & & rann & 1sm & n & n & & AAA & & is \\ \hline \end{tabular} PIVOI TABLE: (Students please parte your pivot table anywhere in the space below.) 17 In order to assist with this task, you have gathered information for each customer which you 18. befieve can help you predict expected credit losses. The information has been summarized in an 19 Excel Spreadsheet: (see the RawData tab): 20 - Schedule of Aged Accounts Receivable - Credit rating: - AAA firms having an above average credit rating - BBB hayirg a below average credit rating CCC firms having a poor credit rating. - Customer Response Rate (CRR) 23. which shows the percentage of time customers have responded to email \& telephone reminders (either by providing payment or by explaining why payment has not been made). 24 . Write-off rate of accounts rece ivabie over the past 3 years. > Cover Sheet QuEsion RawData Part 1 Part 2(a) Part 2(b) Part 2(c) CSM (Input 1) CSM Calculation Mode: Automatic Workbook Statistics 15C Sunny Search - Companies with a BBB rating have a 50% higher default risk compared to AAA companies. - Example: The default risk for a BBB company in the 91-120 day aging category would be (100%95%)1.5=5%1.5=7.5% - Companies with a CCC rating have a twice as high default risk compared to AAA companies. - Example the default risk for a CcC company in the 91-12.0 day aging category would bes (100%95%)2=5%2.0=10% - The consultant has determined that Canadian companies in general are less likely to pay their full Accounts Receivable balance if they nave a poor Customer Response Rate (CRR). In general, the consultant predicts... - companies with a CRR of 100 will pay 99% of their A/R - companies with a CRR of 90 will pay 98% of their A/R - companies with a CR of 80 will pay 97% of their A/R f. 125 manki studnt work Area: \begin{tabular}{|c|c|c|c|c|c|} \hline \\ \hline Ondit hation & Aeine & Amount & \begin{tabular}{l} Probablityc \\ Fullforment \end{tabular} & \begin{tabular}{l} Probebaing of \\ Dotede \end{tabular} & Etimated Non \\ \hline AM & Under 6 den & & 0.85 & & \\ \hline MM & 6050dm & & 975 & & \\ \hline AMA & & & & 3 & \\ \hlineM & 131.16dm & & & = & \\ \hlineM & Dow tso days: & 53 & bon & & \\ \hline sen & Undercodin & & Whats & & \\ \hline Bile & 6090 dews & & & 2= & \\ \hline 138 & 91-120 dion & ? & hwets & & \\ \hline & 121:150 don. & & whis & & \\ \hline 608 & Oever 150 den & & M415 & & \\ \hline \end{tabular} (ahne) Pivetiabe Finda fr You recently hired an independent consultant who specializes in credit risk to help you refine your estimate. The consultant has provided you with the following information: - The consultant determined companies with a AAA rating are of low credit risk. Probability of receiving full payment on AAA customer accounts receivable are as follows: - Companies with a BPE rating have a 50% higher default risk compared to AAA companies. - Example: The - lault risk for a BBB company in the 91.120 day aging category would be 17 CIEAN SWEEP UD. CUSTOMER DATA Cotrober, 202 st 1 Stardunt Clearing ted. Clean Sweep Ltd. is a retalier of several different brands of vacuum cleaners, from hand-hif models to built-in central vacuums. It sells it products to customers across Canada on a 30-di credit basis, Currently, Clean Sweep has 100 credit customers spread across the following reg. Shape, Text Bo - ESTr represents companies in the Maritime provinces - CENTRAL includes Ontario and Quebec; PRAIRIE includes Manitoba, Saskatchewan \& Alberta - WEST includes BC, the Yukon, NWT and Nunavit You are the credit manager at Cloin sweep ltd. In preparation for the quarter-end report, and your boss has asked you to estin the Allowance for Doubtful Accounts (AFDA) using a variety of techniques, including "predictive analytics". CLEN SWEEP LTO. CUSTOMER DATA October, 2023 : \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{2}{|r|}{ Cuntomer information } & \multicolumn{6}{|c|}{ Schedule of Aged Accounts Receivable } & \multicolumn{3}{|c|}{ Other irtormation } \\ \hline Realon & Customer Name & Total AR & 150 das & \begin{tabular}{l} Credit \\ Rominf \end{tabular} & \begin{tabular}{l} Cuntooner \\ Response \\ Rate (XY) \end{tabular} & \begin{tabular}{c} Weity-eft \\ s \end{tabular} \\ \hline EALT & Aceccarpentry inc. & 14,800 & 8,700 & 2.500 & 2,500 & 1,100 & & MAA & & 2x \\ \hline West & Addison imvestment Services inc. & 6,400 & 6,300 & 100 & 0 & 0 & g) & ANA & 30s & ox \\ \hline WEST & All Season Outerwear Company inc: & 12,900 & 9,200 & 3,700 & 0 & 9 & 0 & MAA & 90K & os \\ \hline PQAIRIE & Aurora's Antiques Ltd. & 11,400 & 7,200 & 4,200 & 0 & 0 & 9 & MAA & 100% & Qs: \\ \hline EAT & Autumn Tours ltd & 9,400 & 2,000 & 3500 & 2,300 & 800 & 860 & AB & & As \\ \hline GAST & B \& It the Rentaks the. & 14,200 & 10,600 & 3,100 & 0 & 0 & 500 & MA & & 2k \\ \hline CERTHAL & Baxter Fataricators inc. & 6,900 & 6,900 & 0 & 6. & 0 & of & ARA & 100N & ok \\ \hline \end{tabular} CIEAN SWEE TD. CUSTOMER DATA patatier, 200 ? Student Work Area (position copied data here): Part 2 (c) AFDA based on "Predictive Analytics" c b i [67 mark] Hrouse (student instructions) If Compiete an eitimatre of AFDA for noch input that will go into the Credis Scam Model. 2. Cell referente the rstimated AraA from esch workthert into ite table belo 1. Calculate the "erobability of defaut" ta be applied to the amaunts tram vour phet table. GENSWEEP LFD. CUSTOMER DATA Octobec, 2023 ? \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{9}{|c|}{ October, 2023? } & & \\ \hline & Cuntioner information & \multicolumn{6}{|c|}{ Schedule of Afed Accounts lecrivabie } & \multicolumn{3}{|c|}{ Other informanen } \\ \hline firysion & Customer Name & Total AR & 150dm & \begin{tabular}{l} Cretit \\ Matins \end{tabular} & \begin{tabular}{l} Custooner \\ Amponve \\ kate (W) \end{tabular} \mid & \begin{tabular}{c} Whita-dif \\ s \end{tabular} \\ \hline wing & Harnst Maple Broducts the. & 5,700 & 900 & 4.800 & 0 & 0 & of & MA & 100c & is \\ \hline whir & Theh Valley Therapy Lte. & 10,200 & 6,600 & 2,300 & 1,200 & 0 & of & MA & & (4) \\ \hline HAAMAIS & Hifisdate invialetion cor. & 8,600 & 4,000 & 0 & 700 & 2,000 & 1,900 & ccc & sin & ion \\ \hline & Pliericane foreiry ins: & 15,200 & 0.700 & 2,200 & 0 & 2,000 & 1,400 & asa & 00% & is \\ \hline mokinar & Ivery Hotein inc: & 2,400 & 1,1000 & 600 & 0 & a & 0 & haA & ton & 2 \\ \hline & fausly Talor and Aterctions ine: & 0,100 & & 2,200 & 9 & 0 & 0 & MA & & is \\ \hline tast & Johnean'z Fumniture flefiniskine that. & 2,500 & 1.400 & 10 & 1,100 & a & 0 & aA. & uos & 28 \\ \hline \end{tabular} The consultant has proposed you use a "Credit Score Model" to estimate AFDA based chthe following inputs which should be equally weighted: (a) Aged Receivables with Customer credit rating (AAA, BBB or CCC) (b) Customer Response Rate (CRR), and (c) Customer write-off history A. Student Work Area (position copled data here): Excel ninu io: H PCommunt otdining 1 CLEN SWEER UD. CUSTOMER DATA Gatober, 2023 \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{2}{|r|}{ Cuntomer information } & \multicolumn{6}{|c|}{ Schedule of Aged Acrounts Fecelvable } & \multicolumn{3}{|c|}{ Other informathin } \\ \hline Fiedon & Cuitomer Name & Total AR. & 1 so dare. & \begin{tabular}{l} Credit \\ Mutine \end{tabular} & \begin{tabular}{l} Caistnoner \\ flesponse \\ Aate (X) \end{tabular} & \begin{tabular}{c} Write off \\ \end{tabular} \\ \hline Wis: & Clockuork Camultine tnd. & 8,400 & 7,400 & 1,000 & 0 & 0 & o & NA. & 100 & ov \\ \hline Est & Continental Shippiry Ine. & 5,500 & 2,500 & 3,000 & a & 0 & 0 & AMA & 100 . & 14 \\ \hline wist & Cointside Haquet Chib Wit: & 7,500 & 5,200 & 2300 & 0 & 0 & o & AMA & son & \\ \hline West & Crekside Aehatolitatien Centre Ltd. & 5,400 & 3,800 & 1,600 & 0 & 0 & 0 & AM & log6 & on \\ \hline ctmotikat & Decis and Docks ine. & 16,900 & 11,300 & 3,000 & 400 & a & o & AM & eas. & os \\ \hline ruinif & Delia Plimbing tra. & 8.600 & 5,100 & 0 & 700 & 2,200 & 700 & alin & 70 & s \\ \hline & Divine Desian Servaces ine. & 2.900 & 1,100 & 1,000 & 200 & 100 & 100 & a & cos & es \\ \hline \end{tabular} 2/ Estimate AFDA using the following methods: a) Default Risk applied to overall Accounts Receivable b) Default Risk applied to Aged Accounts Receivable c) Credit Score Model (using "predictive analytics") 3/ What conclusions can you make about your analysis? Does one method provide a better estimate over another? Explain. CIEAN SWEE UR. CUSTOMER DATA Oetober, 2009 Part 2 (b) AFDA based on default risk applied to Aged Accounts Receivable [10 marks] Neneconwory. Probability of Mobability of 40 divi he bo day. 91120 days ruli Finment. pericin i1 10marks]1 1 \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \\ \hline \multicolumn{2}{|c|}{\begin{tabular}{l} CUSTOMER DATA \\ October, 2029 \end{tabular}} & \multicolumn{2}{|l|}{$} & & & & & & & \\ \hline \multicolumn{2}{|r|}{ Customet information } & \multicolumn{6}{|c|}{ Schedule of Aged Accounts Recrivabie } & \multicolumn{3}{|c|}{ Other information } \\ \hline Asplon. & 2 Customer Name & Total Ag & 150dan & \begin{tabular}{l} Credat \\ Rabne \end{tabular} & \begin{tabular}{l} Curtomer \\ liespense \\ Hatn (N) \end{tabular} & White of \\ \hline & fereus Masonry Corp. & 4,800 & 2,500 & 0 & 1,100 & 700 & 300 & nats & & 4x \\ \hline cenctiul & Atfor Mll Cross Trainityn ine. & 9,100 & 6.200 & 100 & 800 & 0 & 0 & AMA & 100% & as \\ \hline contreat & Five Mankevi indoor Playeround Ltd. & 5,600 & 4.600 & 1,000 & 0 & o & 0 & ma & 904 & is \\ \hline contral & Galaxy Aeronautical Inepineering Corp. & 9.400 & 6.100 & 3,300 & 0 & 0 & 0 & MA & 100s & ok \\ \hline w: & Georse and Son Contracton ins. & 9,000 & 6,100 & 2,900 & 0 & 0 & c & haA & & is \\ \hline west & Ginger imports inc. & 4,400 & 1,100 & 2,600 & 0 & D & a & AM & gos & os \\ \hline cinmal & Golden Era Cratismen Ltd. & 3.800 & 1300 & 500 & 0 & 0 & & MM & 90s & 25 \\ \hline \end{tabular} write of ainetint by the fotal A/R. What repoin seema to be having a vendicant collectability problem? filde the total wit wraten off for alt racions. mput your resalt inse the Part 2 / warkheet 2. Uhe the information from your Fivot Tabin to complete the mussine "arntunt" information located iscolume 0 2. Calcalne the "probubility of defacol" to be opplied to the amounts from vout pirot table. input your tetuit inte the Part.2c) worksheet. What conclusions can you make about your analysis? Does one method provide a better estimate over another? Explain. CUSTOMER DATA \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{2}{|c|}{ October, 2023} & \multicolumn{2}{|l|}{} & & & & & & & \\ \hline \multicolumn{2}{|r|}{ Centomer informuation } & \multicolumn{6}{|c|}{ Schedule of Aged Accounts Alecrivable } & \multicolumn{3}{|c|}{ Other informution. } \\ \hline Eezion & Cuitomer Name & 14,200TotalAR & 150cmx & \begin{tabular}{l} Credin \\ Roting \end{tabular} & \begin{tabular}{l} Custumet \\ Response \\ Rate py \end{tabular} & \begin{tabular}{c} Write-ent \\ x \end{tabular} \\ \hline Centiat & Dinfer Fabricatons inc & 6,900 & 6,900 & 0 & o & o & o) & uA & 100% & is \\ \hline 105T: & Bnar Logistics ita. & 0,100 & 6,400 & 800 & 1,900 & 0 & o) & m & 906 & is \\ \hline CONTAAL & Della Granite inc. & 4,700 & 2,400 & 0 & 2,300 & 0 & o) & MA & sons & on \\ \hline EAST & Bif Screen fntertainment ttd. & 6,000 & 4,800 & 1200 & & 0 & of & M. & sin & m \\ \hline CENTRA: & find Duct Cleaning ine. & 7,700 & 5,700 & 200 & 1,800 & 0 & of & Mn & 100% & 2s \\ \hline bas & Glun Plate Canering Services tid. & 15,300 & 9,800: & 4500 & 400 & 0 & 600 & ma & lon & JN \\ \hline ASte & & & rann & 1sm & n & n & & AAA & & is \\ \hline \end{tabular} PIVOI TABLE: (Students please parte your pivot table anywhere in the space below.) 17 In order to assist with this task, you have gathered information for each customer which you 18. befieve can help you predict expected credit losses. The information has been summarized in an 19 Excel Spreadsheet: (see the RawData tab): 20 - Schedule of Aged Accounts Receivable - Credit rating: - AAA firms having an above average credit rating - BBB hayirg a below average credit rating CCC firms having a poor credit rating. - Customer Response Rate (CRR) 23. which shows the percentage of time customers have responded to email \& telephone reminders (either by providing payment or by explaining why payment has not been made). 24 . Write-off rate of accounts rece ivabie over the past 3 years. > Cover Sheet QuEsion RawData Part 1 Part 2(a) Part 2(b) Part 2(c) CSM (Input 1) CSM Calculation Mode: Automatic Workbook Statistics 15C Sunny Search - Companies with a BBB rating have a 50% higher default risk compared to AAA companies. - Example: The default risk for a BBB company in the 91-120 day aging category would be (100%95%)1.5=5%1.5=7.5% - Companies with a CCC rating have a twice as high default risk compared to AAA companies. - Example the default risk for a CcC company in the 91-12.0 day aging category would bes (100%95%)2=5%2.0=10% - The consultant has determined that Canadian companies in general are less likely to pay their full Accounts Receivable balance if they nave a poor Customer Response Rate (CRR). In general, the consultant predicts... - companies with a CRR of 100 will pay 99% of their A/R - companies with a CRR of 90 will pay 98% of their A/R - companies with a CR of 80 will pay 97% of their A/R f. 125 manki studnt work Area: \begin{tabular}{|c|c|c|c|c|c|} \hline \\ \hline Ondit hation & Aeine & Amount & \begin{tabular}{l} Probablityc \\ Fullforment \end{tabular} & \begin{tabular}{l} Probebaing of \\ Dotede \end{tabular} & Etimated Non \\ \hline AM & Under 6 den & & 0.85 & & \\ \hline MM & 6050dm & & 975 & & \\ \hline AMA & & & & 3 & \\ \hlineM & 131.16dm & & & = & \\ \hlineM & Dow tso days: & 53 & bon & & \\ \hline sen & Undercodin & & Whats & & \\ \hline Bile & 6090 dews & & & 2= & \\ \hline 138 & 91-120 dion & ? & hwets & & \\ \hline & 121:150 don. & & whis & & \\ \hline 608 & Oever 150 den & & M415 & & \\ \hline \end{tabular} (ahne) Pivetiabe Finda fr You recently hired an independent consultant who specializes in credit risk to help you refine your estimate. The consultant has provided you with the following information: - The consultant determined companies with a AAA rating are of low credit risk. Probability of receiving full payment on AAA customer accounts receivable are as follows: - Companies with a BPE rating have a 50% higher default risk compared to AAA companies. - Example: The - lault risk for a BBB company in the 91.120 day aging category would be 17 CIEAN SWEEP UD. CUSTOMER DATA Cotrober, 202 st 1 Stardunt Clearing ted. Clean Sweep Ltd. is a retalier of several different brands of vacuum cleaners, from hand-hif models to built-in central vacuums. It sells it products to customers across Canada on a 30-di credit basis, Currently, Clean Sweep has 100 credit customers spread across the following reg. Shape, Text Bo - ESTr represents companies in the Maritime provinces - CENTRAL includes Ontario and Quebec; PRAIRIE includes Manitoba, Saskatchewan \& Alberta - WEST includes BC, the Yukon, NWT and Nunavit You are the credit manager at Cloin sweep ltd. In preparation for the quarter-end report, and your boss has asked you to estin the Allowance for Doubtful Accounts (AFDA) using a variety of techniques, including "predictive analytics". CLEN SWEEP LTO. CUSTOMER DATA October, 2023 : \begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline \multicolumn{2}{|r|}{ Cuntomer information } & \multicolumn{6}{|c|}{ Schedule of Aged Accounts Receivable } & \multicolumn{3}{|c|}{ Other irtormation } \\ \hline Realon & Customer Name & Total AR & 150 das & \begin{tabular}{l} Credit \\ Rominf \end{tabular} & \begin{tabular}{l} Cuntooner \\ Response \\ Rate (XY) \end{tabular} & \begin{tabular}{c} Weity-eft \\ s \end{tabular} \\ \hline EALT & Aceccarpentry inc. & 14,800 & 8,700 & 2.500 & 2,500 & 1,100 & & MAA & & 2x \\ \hline West & Addison imvestment Services inc. & 6,400 & 6,300 & 100 & 0 & 0 & g) & ANA & 30s & ox \\ \hline WEST & All Season Outerwear Company inc: & 12,900 & 9,200 & 3,700 & 0 & 9 & 0 & MAA & 90K & os \\ \hline PQAIRIE & Aurora's Antiques Ltd. & 11,400 & 7,200 & 4,200 & 0 & 0 & 9 & MAA & 100% & Qs: \\ \hline EAT & Autumn Tours ltd & 9,400 & 2,000 & 3500 & 2,300 & 800 & 860 & AB & & As \\ \hline GAST & B \& It the Rentaks the. & 14,200 & 10,600 & 3,100 & 0 & 0 & 500 & MA & & 2k \\ \hline CERTHAL & Baxter Fataricators inc. & 6,900 & 6,900 & 0 & 6. & 0 & of & ARA & 100N & ok \\ \hline \end{tabular}