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Progettazione modello

6.5 Modello di credit scoring

6.5.3 Commento

6.5 – Modello di credit scoring

Nel secondo caso, l’errore commesso produce un costo visibile, facilmente osservabile, il quale corrisponde al capitale e agli interessi perduti attraverso l’insolvenza di un’impresa erroneamente classificata come sana, alla quale è stato concesso credito.

Sulla base di queste considerazioni, la banca sceglierà di concedere credito valutando il diverso costo associato alle due tipologie di errore, in modo da misurare il costo atteso dei due errori, pesati per la rispettiva probabilità di verificarsi. In pratica, la banca accetterà di concedere credito a tutte quelle imprese in cui il costo atteso dell’errore di II tipo risulti inferiore al costo atteso dell’errore di I tipo:

C(type II error) · P D < C(type I error) · (1 − P D) . (6.4) In poche parole, si è ritenuto opportuno calcolare e valutare una speciale funzione di costo, estremamente basilare, che tenesse conto del diverso costo associato ai due errori, assegnando due ponderazioni differenti all’errore di I o di II tipo:

Cost F unction= wtype I error· errorF P + wtype II error· errorF N . (6.5) In questo caso, dopo attente riflessioni e valutazioni, calcolando una media dei valori reali più frequenti e aggiungendo uno specifico coefficiente di sicurezza, si è scelto di assegnare una ponderazione pari a wtype I error = 1 e wtype II error = 100, finendo per distanziare gli errori in modo estremamente cautelativo con due ordini di grandezza, in modo da effettuare un calcolo, sicuramente grossolano e approssimativo, ma utile per avere alcune intuizioni interessanti sul problema in questione.

Progettazione modello

Tabella6.3.Reporttecnico:flagdistatusS/A-impresa(analisidicorrelazione).

Modello

InputLayerHiddenLayerOutputLayer

Learning rate

Epoch Batch size

Threshold

TrainingValidationTesting

NeuronActivationLayerNeuronActivationNeuronActivationLossAUCAccuracyLossAUCAccuracyAccuracyCostFunctionFunctionFunction1AC10ReLU28|8ReLU1Sigmoid0,001250320,500000,06990,84610,98070,06660,84610,98070,981880162AC10Sigmoid28|8Sigmoid1Sigmoid0,001250320,500000,06670,82450,98180,07500,82460,98180,9785107073AC10ReLU28|8ReLU1Sigmoid0,001250320,136850,06710,85590,97300,07090,85590,97300,972472744AC10ReLU28|8ReLU1Sigmoid0,001250320,077680,06350,85530,95570,07710,85540,95570,956959705AC10ReLU28|8ReLU1Sigmoid0,001250320,018520,06650,86350,78710,06510,86350,78720,787635001BC10ReLU26|6ReLU1Sigmoid0,001250320,500000,06450,83880,98270,08340,83880,98270,9790111002BC10Sigmoid26|6Sigmoid1Sigmoid0,001250320,500000,06920,84300,98220,05210,84300,98220,9796107013BC10ReLU26|6ReLU1Sigmoid0,001250320,136850,06580,86900,97140,08110,86900,97140,976663614BC10ReLU26|6ReLU1Sigmoid0,001250320,077680,06510,87210,95570,07300,87220,95570,944555415BC10ReLU26|6ReLU1Sigmoid0,001250320,018520,06920,85580,77250,06300,85590,77250,766342071CC10ReLU312|12|12ReLU1Sigmoid0,001250320,500000,05190,90140,98200,07360,90150,98200,982484092CC10Sigmoid312|12|12Sigmoid1Sigmoid0,001250320,500000,06750,82260,98190,07890,82270,98190,980598053CC10ReLU312|12|12ReLU1Sigmoid0,001250320,136850,05390,90810,97070,07530,90810,97070,970358994CC10ReLU312|12|12ReLU1Sigmoid0,001250320,077680,05740,88640,95480,09500,88640,95480,947950285CC10ReLU312|12|12ReLU1Sigmoid0,001250320,018520,05400,90690,81300,07120,90700,81310,776836621DC10ReLU37|7|7ReLU1Sigmoid0,001250320,500000,06100,87300,98300,06940,87300,98300,979498112DC10Sigmoid37|7|7Sigmoid1Sigmoid0,001250320,500000,06980,82090,98110,07240,82090,98110,9805103003DC10ReLU37|7|7ReLU1Sigmoid0,001250320,136850,07100,84220,97260,06660,84220,97260,976065624DC10ReLU37|7|7ReLU1Sigmoid0,001250320,077680,06110,88470,95290,08160,88480,95290,959058605DC10ReLU37|7|7ReLU1Sigmoid0,001250320,018520,06350,88030,78540,07560,88030,78550,799535361EC10ReLU38|3|12ReLU1Sigmoid0,001250320,500000,06250,87630,98250,06580,87630,98250,979687212EC10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,500000,06540,81590,98170,07320,81600,98170,9775109103EC10ReLU38|3|12ReLU1Sigmoid0,001250320,136850,06280,86190,97550,05610,86190,97550,972476704EC10ReLU38|3|12ReLU1Sigmoid0,001250320,077680,06120,87520,95340,08610,87520,95340,934453965EC10ReLU38|3|12ReLU1Sigmoid0,001250320,018520,05640,89140,80140,08180,89140,80140,786939991FC10ReLU36|9|9|3ReLU1Sigmoid0,001250320,500000,06240,86560,98170,09330,86560,98170,981395042FC10Sigmoid36|9|9|3Sigmoid1Sigmoid0,001250320,500000,07180,79860,98000,08030,79870,98000,982294003FC10ReLU36|9|9|3ReLU1Sigmoid0,001250320,136850,05890,87480,97280,08690,87480,97280,975871574FC10ReLU36|9|9|3ReLU1Sigmoid0,001250320,077680,06440,89800,94690,06360,89800,94690,955651855FC10ReLU36|9|9|3ReLU1Sigmoid0,001250320,018520,05920,86170,78230,07950,86170,78230,78594004Top10variabilicorrelazione:KNT/AT,MS,LBV,DT/FN,DT/VA,DT/EBITDA,ROE,DN,OFN/EBITDA,FN/AT

6.5 – Modello di credit scoring

Tabella6.4.Reporttecnico:flagdistatusS/A+L-impresa(analisidicorrelazione).

Modello

InputLayerHiddenLayerOutputLayer

Learningrate Epoc h

Batch size

Threshold

TrainingValidationTesting NeuronActivationLayerNeuronActivationNeuronActivationLossAUCAccuracyLossAUCAccuracyAccuracyCost FunctionFunctionFunction 1AC10ReLU28|8ReLU1Sigmoid0,001250320,500000,30130,80780,88230,33800,80790,88230,886648615 2AC10Sigmoid28|8Sigmoid1Sigmoid0,001250320,500000,30620,80620,88480,30420,80620,88480,879553900 3AC10ReLU28|8ReLU1Sigmoid0,001250320,136850,30290,81470,74120,31800,81470,74120,742510183 1BC10ReLU26|6ReLU1Sigmoid0,001250320,500000,29950,81860,88520,31420,81860,88520,878753805 2BC10Sigmoid26|6Sigmoid1Sigmoid0,001250320,500000,30990,79990,88130,30830,79990,88130,882154183 3BC10ReLU26|6ReLU1Sigmoid0,001250320,136850,29940,81640,75340,31320,81650,75340,753322789 1CC10ReLU312|12|12ReLU1Sigmoid0,001250320,500000,28910,83530,88620,30250,83530,88620,879550039 2CC10Sigmoid312|12|12Sigmoid1Sigmoid0,001250320,500000,29800,81030,88360,33370,81030,88370,882750714 3CC10ReLU312|12|12ReLU1Sigmoid0,001250320,136850,28890,82380,76950,33820,82380,76960,768224393 1DC10ReLU37|7|7ReLU1Sigmoid0,001250320,500000,29790,82120,88290,31150,82120,88290,879650137 2DC10Sigmoid37|7|7Sigmoid1Sigmoid0,001250320,500000,30730,80660,88230,32210,80670,88230,882353687 3DC10ReLU37|7|7ReLU1Sigmoid0,001250320,136850,29320,82070,77350,30820,82070,77350,752724079 1EC10ReLU38|3|12ReLU1Sigmoid0,001250320,500000,31040,81160,88150,30660,81160,88150,887648412 2EC10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,500000,30500,79910,88130,33700,79910,88130,883253583 3EC10ReLU38|3|12ReLU1Sigmoid0,001250320,136850,30760,81970,76650,31560,81970,76650,757822171 1FC10ReLU36|9|9|3ReLU1Sigmoid0,001250320,500000,29970,81430,88320,33390,81430,88320,879554593 2FC10Sigmoid36|9|9|3Sigmoid1Sigmoid0,001250320,500000,31430,80070,87780,29970,80070,87780,885150504 3FC10ReLU36|9|9|3ReLU1Sigmoid0,001250320,136850,30080,81700,74640,30900,81700,74640,743919310 1GC10ReLU38|10|8ReLU1Sigmoid0,001250320,500000,29210,82560,88490,31440,82560,88490,879350733 2GC10Sigmoid38|10|8Sigmoid1Sigmoid0,001250320,500000,31340,79420,88260,30040,79420,88260,881053793 3GC10ReLU38|10|8ReLU1Sigmoid0,001250320,136850,29630,81610,76110,32150,81610,76110,756121784 1HC10ReLU315|7|15|5ReLU1Sigmoid0,001250320,500000,28260,83000,88590,33170,83010,88590,882148738 2HC10Sigmoid315|7|15|5Sigmoid1Sigmoid0,001250320,500000,31140,79930,88230,31910,79930,88230,883253583 3HC10ReLU315|7|15|5ReLU1Sigmoid0,001250320,136850,29430,82430,75770,33240,82440,75760,727917379 1IC10ReLU310|3|10ReLU1Sigmoid0,001250320,500000,30120,82760,88070,31110,82760,88070,879548356 2IC10Sigmoid310|3|10Sigmoid1Sigmoid0,001250320,500000,30540,80300,88370,32310,80310,88370,882353390 3IC10ReLU310|3|10ReLU1Sigmoid0,001250320,136850,30400,81770,75250,31950,81770,75250,747620740 1LC10ReLU35|7|2ReLU1Sigmoid0,001250320,500000,30640,80970,88580,28800,80980,88580,880254391 2LC10Sigmoid35|7|2Sigmoid1Sigmoid0,001250320,500000,31150,78640,87810,30870,78650,87810,884251004 3LC10ReLU35|7|2ReLU1Sigmoid0,001250320,136850,30940,80420,75030,33740,80420,75030,771221803 Top10variabilicorrelazione:DT/VA,ROE,DT/EBITDA,KNT/AT,LBV,AS/CO,AU/AT,ROI,FN/AT,OFN/EBITDA

Progettazione modello

Tabella6.5.Reporttecnico:flagdistatusS/A-impresa(RandomForesteXGBoost).

Modello

InputLayerHiddenLayerOutputLayer

Learning rate

Epoch Batch size

Threshold

TrainingValidationTesting

NeuronActivationLayerNeuronActivationNeuronActivationLossAUCAccuracyLossAUCAccuracyAccuracyCostFunctionFunctionFunction1ARF10ReLU28|8ReLU1Sigmoid0,001250320,500000,05400,87740,98400,07020,87740,98400,980986152ARF10Sigmoid28|8Sigmoid1Sigmoid0,001250320,500000,07040,80900,98140,08010,80900,98140,982283113ARF10Sigmoid28|8Sigmoid1Sigmoid0,001250320,136850,07050,80190,97220,07190,80190,97220,973063804ARF10Sigmoid28|8Sigmoid1Sigmoid0,001250320,077680,06970,81840,95690,05890,81840,95690,961163445ARF10Sigmoid28|8Sigmoid1Sigmoid0,001250320,018520,07110,81340,79990,07400,81350,80000,847938741DRF10ReLU27|7|7ReLU1Sigmoid0,001250320,500000,06590,86300,98360,04770,86300,98360,980094122DRF10Sigmoid27|7|7Sigmoid1Sigmoid0,001250320,500000,06790,79910,98070,07960,79910,98070,980495093DRF10Sigmoid27|7|7Sigmoid1Sigmoid0,001250320,136850,07010,81180,97510,06210,81180,97510,971372804DRF10Sigmoid27|7|7Sigmoid1Sigmoid0,001250320,077680,06860,81640,95270,06310,81650,95280,960560505DRF10Sigmoid27|7|7Sigmoid1Sigmoid0,001250320,018520,07370,79330,77220,07910,79330,77230,802933201ERF10ReLU38|3|12ReLU1Sigmoid0,001250320,500000,05020,85850,98550,07000,85860,98550,981381182ERF10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,500000,07290,81810,98120,07460,81810,98120,982195093ERF10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,136850,06890,83500,97250,06020,83510,97260,966279014ERF10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,077680,06870,81070,95400,08150,81070,95400,963360355ERF10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,018520,07260,80720,80370,06490,80720,80380,825644871AXG10ReLU38|8ReLU1Sigmoid0,001250320,500000,06770,87150,98140,06490,87150,98140,980788142AXG10Sigmoid38|8Sigmoid1Sigmoid0,001250320,500000,07160,82330,98160,07010,82340,98160,982484093AXG10Sigmoid38|8Sigmoid1Sigmoid0,001250320,136850,06860,81150,97270,07690,81160,97270,977774444AXG10Sigmoid38|8Sigmoid1Sigmoid0,001250320,077680,07450,83330,96370,07030,83330,96370,963776175AXG10Sigmoid38|8Sigmoid1Sigmoid0,001250320,018520,07350,81970,73660,05510,81970,73660,756837621DXG10ReLU37|7|7ReLU1Sigmoid0,001250320,500000,06760,84930,98170,07410,84930,98170,983470182DXG10Sigmoid37|7|7Sigmoid1Sigmoid0,001250320,500000,07540,81570,98030,06870,81580,98030,983272173DXG10Sigmoid37|7|7Sigmoid1Sigmoid0,001250320,136850,07180,83260,97190,06810,83260,97190,975669604DXG10Sigmoid37|7|7Sigmoid1Sigmoid0,001250320,077680,06550,80850,95800,06710,80860,95800,967380935DXG10Sigmoid37|7|7Sigmoid1Sigmoid0,001250320,018520,07220,80530,77260,07700,80540,77260,767229151EXG10ReLU38|3|12ReLU1Sigmoid0,001250320,500000,06460,85820,98180,07020,85820,98180,983084062EXG10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,500000,07320,83050,98050,07050,83050,98050,983474143EXG10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,136850,07180,84000,96930,05190,84000,96930,973973654EXG10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,077680,07130,81600,95450,05920,81600,95450,963567275EXG10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,018520,07200,82860,75330,07850,82870,75340,77183683Top10variabiliRandomForest:MS,ln(FN),KCN,DN,RS+RE/AT,KN/DT,AC/AT,KN/AT,LIQ/PC,LIQ/ATTop10variabiliXGBoost:KNT/DT+KN,DT/FN,MS,KCN,EBITDA-OF/AT,ROE,ln(FN),OFN/EBIT,AC/AT,AC/PC

6.5 – Modello di credit scoring

Tabella6.6.Reporttecnico:flagdistatusS/A+L-impresa(RandomForesteXGBoost).

Modello

InputLayerHiddenLayerOutputLayer

Learningrate Epoc h

Batch size

Threshold

TrainingValidationTesting NeuronActivationLayerNeuronActivationNeuronActivationLossAUCAccuracyLossAUCAccuracyAccuracyCost FunctionFunctionFunction 1ARF10ReLU28|8ReLU1Sigmoid0,001250320,500000,28770,83540,88510,31870,83550,88510,891447204 2ARF10Sigmoid28|8Sigmoid1Sigmoid0,001250320,500000,30080,82490,88230,29620,82490,88240,890047805 3ARF10Sigmoid28|8Sigmoid1Sigmoid0,001250320,136850,30920,81360,74740,29590,81370,74740,761421360 1CRF10ReLU212|12|12ReLU1Sigmoid0,001250320,500000,27640,84490,88690,32090,84490,88690,892747197 2CRF10Sigmoid212|12|12Sigmoid1Sigmoid0,001250320,500000,30080,82140,88220,31570,82140,88220,891947300 3CRF10Sigmoid212|12|12Sigmoid1Sigmoid0,001250320,136850,29790,82260,75430,32510,82260,75430,753618233 1ERF10ReLU38|3|12ReLU1Sigmoid0,001250320,500000,29500,83770,88470,30130,83770,88470,887445938 2ERF10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,500000,29800,81030,88360,33370,81030,88370,882749521 3ERF10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,136850,30230,82410,73910,28590,82410,73910,764422928 1FRF10ReLU36|9|9|3ReLU1Sigmoid0,001250320,500000,29130,83530,88860,30110,83530,88860,884048332 2FRF10Sigmoid36|9|9|3Sigmoid1Sigmoid0,001250320,500000,30130,81150,88110,31560,81150,88110,892747989 3FRF10Sigmoid36|9|9|3Sigmoid1Sigmoid0,001250320,136850,29920,81910,74710,29830,81920,74710,816429187 1LRF10ReLU35|7|2ReLU1Sigmoid0,001250320,500000,29680,83170,88650,30480,83170,88650,887649105 2LRF10Sigmoid35|7|2Sigmoid1Sigmoid0,001250320,500000,29970,81600,88290,29670,81600,88290,887049306 3LRF10Sigmoid35|7|2Sigmoid1Sigmoid0,001250320,136850,29520,81400,75640,30210,81400,75640,770822498 1AXG10ReLU38|8ReLU1Sigmoid0,001250320,500000,28690,84120,88640,30640,84130,88640,884950406 2AXG10Sigmoid38|8Sigmoid1Sigmoid0,001250320,500000,29590,82750,88140,31470,82750,88150,889949390 3AXG10Sigmoid38|8Sigmoid1Sigmoid0,001250320,136850,29380,82690,75460,31880,82690,75460,757019205 1CXG10ReLU312|12|12ReLU1Sigmoid0,001250320,500000,27620,85070,88780,30160,85070,88780,885546245 2CXG10Sigmoid312|12|12Sigmoid1Sigmoid0,001250320,500000,29240,83100,88460,29720,83100,88460,885752184 3CXG10Sigmoid312|12|12Sigmoid1Sigmoid0,001250320,136850,29640,83000,74890,29350,83000,74890,756519802 1EXG10ReLU38|3|12ReLU1Sigmoid0,001250320,500000,29900,82920,88620,31660,82920,88620,886653070 2EXG10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,500000,30090,82820,88180,27430,82820,88180,886549903 3EXG10Sigmoid38|3|12Sigmoid1Sigmoid0,001250320,136850,29670,82200,74500,30790,82210,74500,771619920 1FXG10ReLU36|9|9|3ReLU1Sigmoid0,001250320,500000,28210,84370,88810,31500,84370,88820,883451404 2FXG10Sigmoid36|9|9|3Sigmoid1Sigmoid0,001250320,500000,29860,82350,88120,30240,82350,88120,888748307 3FXG10Sigmoid36|9|9|3Sigmoid1Sigmoid0,001250320,136850,29500,81950,74290,29760,81950,74290,755720796 1LXG10ReLU35|7|2ReLU1Sigmoid0,001250320,500000,28420,83850,88760,30160,83850,88760,883153089 2LXG10Sigmoid35|7|2Sigmoid1Sigmoid0,001250320,500000,30330,82120,87880,30980,82120,87880,884646989 3LXG10Sigmoid35|7|2Sigmoid1Sigmoid0,001250320,136850,29160,82730,75330,29100,82730,75330,773925155 Top10variabiliRandomForest:KN/DT,KN/AT,ROE,LBV,ln(FN),MS,KCN,AU-(PS-OS)/AT,DN,RS+RE/AT Top10variabiliXGBoost:KN/AT,KN/DT,AU-(PS-OS)/AT,ln(FN),ROE,CB/CO,DT/EBITDA,DT/FN,AMM/CP,WL/CP

Progettazione modello