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b654a31

_,table,row,description,special
1,application_data,SK_ID_CURR,ID of loan in our sample,\N
2,application_data,TARGET,"Target variable (1 - client with payment difficulties: he/she had late payment more than X days on at least one of the first Y installments of the loan in our sample, 0 - all other cases)",\N
5,application_data,NAME_CONTRACT_TYPE,Identification if loan is cash or revolving,\N
6,application_data,CODE_GENDER,Gender of the client,\N
7,application_data,FLAG_OWN_CAR,Flag if the client owns a car,\N
8,application_data,FLAG_OWN_REALTY,Flag if client owns a house or flat,\N
9,application_data,CNT_CHILDREN,Number of children the client has,\N
10,application_data,AMT_INCOME_TOTAL,Income of the client,\N
11,application_data,AMT_CREDIT,Credit amount of the loan,\N
12,application_data,AMT_ANNUITY,Loan annuity,\N
13,application_data,AMT_GOODS_PRICE,For consumer loans it is the price of the goods for which the loan is given,\N
14,application_data,NAME_TYPE_SUITE,Who was accompanying client when he was applying for the loan,\N
15,application_data,NAME_INCOME_TYPE,"Clients income type (businessman, working, maternity leave,…)",\N
16,application_data,NAME_EDUCATION_TYPE,Level of highest education the client achieved,\N
17,application_data,NAME_FAMILY_STATUS,Family status of the client,\N
18,application_data,NAME_HOUSING_TYPE,"What is the housing situation of the client (renting, living with parents, ...)",\N
19,application_data,REGION_POPULATION_RELATIVE,Normalized population of region where client lives (higher number means the client lives in more populated region),normalized
20,application_data,DAYS_BIRTH,Client's age in days at the time of application,time only relative to the application
21,application_data,DAYS_EMPLOYED,How many days before the application the person started current employment,time only relative to the application
22,application_data,DAYS_REGISTRATION,How many days before the application did client change his registration,time only relative to the application
23,application_data,DAYS_ID_PUBLISH,How many days before the application did client change the identity document with which he applied for the loan,time only relative to the application
24,application_data,OWN_CAR_AGE,Age of client's car,\N
25,application_data,FLAG_MOBIL,"Did client provide mobile phone (1=YES, 0=NO)",\N
26,application_data,FLAG_EMP_PHONE,"Did client provide work phone (1=YES, 0=NO)",\N
27,application_data,FLAG_WORK_PHONE,"Did client provide home phone (1=YES, 0=NO)",\N
28,application_data,FLAG_CONT_MOBILE,"Was mobile phone reachable (1=YES, 0=NO)",\N
29,application_data,FLAG_PHONE,"Did client provide home phone (1=YES, 0=NO)",\N
30,application_data,FLAG_EMAIL,"Did client provide email (1=YES, 0=NO)",\N
31,application_data,OCCUPATION_TYPE,What kind of occupation does the client have,\N
32,application_data,CNT_FAM_MEMBERS,How many family members does client have,\N
33,application_data,REGION_RATING_CLIENT,"Our rating of the region where client lives (1,2,3)",\N
34,application_data,REGION_RATING_CLIENT_W_CITY,"Our rating of the region where client lives with taking city into account (1,2,3)",\N
35,application_data,WEEKDAY_APPR_PROCESS_START,On which day of the week did the client apply for the loan,\N
36,application_data,HOUR_APPR_PROCESS_START,Approximately at what hour did the client apply for the loan,rounded
37,application_data,REG_REGION_NOT_LIVE_REGION,"Flag if client's permanent address does not match contact address (1=different, 0=same, at region level)",\N
38,application_data,REG_REGION_NOT_WORK_REGION,"Flag if client's permanent address does not match work address (1=different, 0=same, at region level)",\N
39,application_data,LIVE_REGION_NOT_WORK_REGION,"Flag if client's contact address does not match work address (1=different, 0=same, at region level)",\N
40,application_data,REG_CITY_NOT_LIVE_CITY,"Flag if client's permanent address does not match contact address (1=different, 0=same, at city level)",\N
41,application_data,REG_CITY_NOT_WORK_CITY,"Flag if client's permanent address does not match work address (1=different, 0=same, at city level)",\N
42,application_data,LIVE_CITY_NOT_WORK_CITY,"Flag if client's contact address does not match work address (1=different, 0=same, at city level)",\N
43,application_data,ORGANIZATION_TYPE,Type of organization where client works,\N
44,application_data,EXT_SOURCE_1,Normalized score from external data source,normalized
45,application_data,EXT_SOURCE_2,Normalized score from external data source,normalized
46,application_data,EXT_SOURCE_3,Normalized score from external data source,normalized
47,application_data,APARTMENTS_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
48,application_data,BASEMENTAREA_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
49,application_data,YEARS_BEGINEXPLUATATION_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
50,application_data,YEARS_BUILD_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
51,application_data,COMMONAREA_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
52,application_data,ELEVATORS_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
53,application_data,ENTRANCES_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
54,application_data,FLOORSMAX_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
55,application_data,FLOORSMIN_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
56,application_data,LANDAREA_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
57,application_data,LIVINGAPARTMENTS_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
58,application_data,LIVINGAREA_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
59,application_data,NONLIVINGAPARTMENTS_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
60,application_data,NONLIVINGAREA_AVG,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
61,application_data,APARTMENTS_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
62,application_data,BASEMENTAREA_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
63,application_data,YEARS_BEGINEXPLUATATION_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
64,application_data,YEARS_BUILD_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
65,application_data,COMMONAREA_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
66,application_data,ELEVATORS_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
67,application_data,ENTRANCES_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
68,application_data,FLOORSMAX_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
69,application_data,FLOORSMIN_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
70,application_data,LANDAREA_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
71,application_data,LIVINGAPARTMENTS_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
72,application_data,LIVINGAREA_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
73,application_data,NONLIVINGAPARTMENTS_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
74,application_data,NONLIVINGAREA_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
75,application_data,APARTMENTS_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
76,application_data,BASEMENTAREA_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
77,application_data,YEARS_BEGINEXPLUATATION_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
78,application_data,YEARS_BUILD_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
79,application_data,COMMONAREA_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
80,application_data,ELEVATORS_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
81,application_data,ENTRANCES_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
82,application_data,FLOORSMAX_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
83,application_data,FLOORSMIN_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
84,application_data,LANDAREA_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
85,application_data,LIVINGAPARTMENTS_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
86,application_data,LIVINGAREA_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
87,application_data,NONLIVINGAPARTMENTS_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
88,application_data,NONLIVINGAREA_MEDI,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
89,application_data,FONDKAPREMONT_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
90,application_data,HOUSETYPE_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
91,application_data,TOTALAREA_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
92,application_data,WALLSMATERIAL_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
93,application_data,EMERGENCYSTATE_MODE,"Normalized information about building where the client lives, What is average (_AVG suffix), modus (_MODE suffix), median (_MEDI suffix) apartment size, common area, living area, age of building, number of elevators, number of entrances, state of the building, number of floor",normalized
94,application_data,OBS_30_CNT_SOCIAL_CIRCLE,How many observation of client's social surroundings with observable 30 DPD (days past due) default,\N
95,application_data,DEF_30_CNT_SOCIAL_CIRCLE,How many observation of client's social surroundings defaulted on 30 DPD (days past due),\N
96,application_data,OBS_60_CNT_SOCIAL_CIRCLE,How many observation of client's social surroundings with observable 60 DPD (days past due) default,\N
97,application_data,DEF_60_CNT_SOCIAL_CIRCLE,How many observation of client's social surroundings defaulted on 60 (days past due) DPD,\N
98,application_data,DAYS_LAST_PHONE_CHANGE,How many days before application did client change phone,\N
99,application_data,FLAG_DOCUMENT_2,Did client provide document 2,\N
100,application_data,FLAG_DOCUMENT_3,Did client provide document 3,\N
101,application_data,FLAG_DOCUMENT_4,Did client provide document 4,\N
102,application_data,FLAG_DOCUMENT_5,Did client provide document 5,\N
103,application_data,FLAG_DOCUMENT_6,Did client provide document 6,\N
104,application_data,FLAG_DOCUMENT_7,Did client provide document 7,\N
105,application_data,FLAG_DOCUMENT_8,Did client provide document 8,\N
106,application_data,FLAG_DOCUMENT_9,Did client provide document 9,\N
107,application_data,FLAG_DOCUMENT_10,Did client provide document 10,\N
108,application_data,FLAG_DOCUMENT_11,Did client provide document 11,\N
109,application_data,FLAG_DOCUMENT_12,Did client provide document 12,\N
110,application_data,FLAG_DOCUMENT_13,Did client provide document 13,\N
111,application_data,FLAG_DOCUMENT_14,Did client provide document 14,\N
112,application_data,FLAG_DOCUMENT_15,Did client provide document 15,\N
113,application_data,FLAG_DOCUMENT_16,Did client provide document 16,\N
114,application_data,FLAG_DOCUMENT_17,Did client provide document 17,\N
115,application_data,FLAG_DOCUMENT_18,Did client provide document 18,\N
116,application_data,FLAG_DOCUMENT_19,Did client provide document 19,\N
117,application_data,FLAG_DOCUMENT_20,Did client provide document 20,\N
118,application_data,FLAG_DOCUMENT_21,Did client provide document 21,\N
119,application_data,AMT_REQ_CREDIT_BUREAU_HOUR,Number of enquiries to Credit Bureau about the client one hour before application,\N
120,application_data,AMT_REQ_CREDIT_BUREAU_DAY,Number of enquiries to Credit Bureau about the client one day before application (excluding one hour before application),\N
121,application_data,AMT_REQ_CREDIT_BUREAU_WEEK,Number of enquiries to Credit Bureau about the client one week before application (excluding one day before application),\N
122,application_data,AMT_REQ_CREDIT_BUREAU_MON,Number of enquiries to Credit Bureau about the client one month before application (excluding one week before application),\N
123,application_data,AMT_REQ_CREDIT_BUREAU_QRT,Number of enquiries to Credit Bureau about the client 3 month before application (excluding one month before application),\N
124,application_data,AMT_REQ_CREDIT_BUREAU_YEAR,Number of enquiries to Credit Bureau about the client one day year (excluding last 3 months before application),\N
176,previous_application.csv,SK_ID_PREV,"ID of previous credit in Home credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loan applications in Home Credit, previous application could, but not necessarily have to lead to credit)",hashed
177,previous_application.csv,SK_ID_CURR,ID of loan in our sample,hashed
178,previous_application.csv,NAME_CONTRACT_TYPE,"Contract product type (Cash loan, consumer loan [POS] ,...) of the previous application",\N
179,previous_application.csv,AMT_ANNUITY,Annuity of previous application,\N
180,previous_application.csv,AMT_APPLICATION,For how much credit did client ask on the previous application,\N
181,previous_application.csv,AMT_CREDIT,"Final credit amount on the previous application. This differs from AMT_APPLICATION in a way that the AMT_APPLICATION is the amount for which the client initially applied for, but during our approval process he could have received different amount - AMT_CREDIT",\N
182,previous_application.csv,AMT_DOWN_PAYMENT,Down payment on the previous application,\N
183,previous_application.csv,AMT_GOODS_PRICE,Goods price of good that client asked for (if applicable) on the previous application,\N
184,previous_application.csv,WEEKDAY_APPR_PROCESS_START,On which day of the week did the client apply for previous application,\N
185,previous_application.csv,HOUR_APPR_PROCESS_START,Approximately at what day hour did the client apply for the previous application,rounded
186,previous_application.csv,FLAG_LAST_APPL_PER_CONTRACT,Flag if it was last application for the previous contract. Sometimes by mistake of client or our clerk there could be more applications for one single contract,\N
187,previous_application.csv,NFLAG_LAST_APPL_IN_DAY,Flag if the application was the last application per day of the client. Sometimes clients apply for more applications a day. Rarely it could also be error in our system that one application is in the database twice,\N
188,previous_application.csv,NFLAG_MICRO_CASH,Flag Micro finance loan,\N
189,previous_application.csv,RATE_DOWN_PAYMENT,Down payment rate normalized on previous credit,normalized
190,previous_application.csv,RATE_INTEREST_PRIMARY,Interest rate normalized on previous credit,normalized
191,previous_application.csv,RATE_INTEREST_PRIVILEGED,Interest rate normalized on previous credit,normalized
192,previous_application.csv,NAME_CASH_LOAN_PURPOSE,Purpose of the cash loan,\N
193,previous_application.csv,NAME_CONTRACT_STATUS,"Contract status (approved, cancelled, ...) of previous application",\N
194,previous_application.csv,DAYS_DECISION,Relative to current application when was the decision about previous application made,time only relative to the application
195,previous_application.csv,NAME_PAYMENT_TYPE,Payment method that client chose to pay for the previous application,\N
196,previous_application.csv,CODE_REJECT_REASON,Why was the previous application rejected,\N
197,previous_application.csv,NAME_TYPE_SUITE,Who accompanied client when applying for the previous application,\N
198,previous_application.csv,NAME_CLIENT_TYPE,Was the client old or new client when applying for the previous application,\N
199,previous_application.csv,NAME_GOODS_CATEGORY,What kind of goods did the client apply for in the previous application,\N
200,previous_application.csv,NAME_PORTFOLIO,"Was the previous application for CASH, POS, CAR, …",\N
201,previous_application.csv,NAME_PRODUCT_TYPE,Was the previous application x-sell o walk-in,\N
202,previous_application.csv,CHANNEL_TYPE,Through which channel we acquired the client on the previous application,\N
203,previous_application.csv,SELLERPLACE_AREA,Selling area of seller place of the previous application,\N
204,previous_application.csv,NAME_SELLER_INDUSTRY,The industry of the seller,\N
205,previous_application.csv,CNT_PAYMENT,Term of previous credit at application of the previous application,\N
206,previous_application.csv,NAME_YIELD_GROUP,Grouped interest rate into small medium and high of the previous application,grouped
207,previous_application.csv,PRODUCT_COMBINATION,Detailed product combination of the previous application,\N
208,previous_application.csv,DAYS_FIRST_DRAWING,Relative to application date of current application when was the first disbursement of the previous application,time only relative to the application
209,previous_application.csv,DAYS_FIRST_DUE,Relative to application date of current application when was the first due supposed to be of the previous application,time only relative to the application
210,previous_application.csv,DAYS_LAST_DUE_1ST_VERSION,Relative to application date of current application when was the first due of the previous application,time only relative to the application
211,previous_application.csv,DAYS_LAST_DUE,Relative to application date of current application when was the last due date of the previous application,time only relative to the application
212,previous_application.csv,DAYS_TERMINATION,Relative to application date of current application when was the expected termination of the previous application,time only relative to the application
213,previous_application.csv,NFLAG_INSURED_ON_APPROVAL,Did the client requested insurance during the previous application,\N