FraudAnalyticsSystem_RCode_/AutoFraud_Unstructure_Business Rules.R at master · MachineLearningCommunity/FraudAnalyticsSystem_RCode_ · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
#!/usr/bin/env Rscript

# Order in which Parameters are to be passed to the code in the command line
# -loss_date 12/20/2013 ; -claim_num C1001

# Code for reading the command line inputs
args <- commandArgs(trailingOnly = TRUE)

# Reading the parameters from the command line and assigning to R varibles

Param1<-args[1]
Loss_date<-as.Date(args[2],format='%m/%d/%Y')
sc1<-args[3]
#Loss_date

Param2<-args[4]
ClaimNum <-args[5]
#ClaimNum

# Connecting to Oracle table
# Extract the record for the specific claim

suppressMessages(require(RODBC))
channel<-odbcConnect("RORACLE",uid="fraudrepo",pwd="fraudrepo",believeNRows=FALSE)
ClaimRecord=sqlQuery(channel,sprintf("select * from RENGINEINVOKE where Claim_id = '%s'",ClaimNum))
#Unstructured Data

unstructureRecord=sqlQuery(channel,sprintf("select * from FAS_POLICE_UNSTRUCTED_DATA where CLAIMID='%s'",ClaimNum))
unstructureRecord$CLAIM_ID = as.character(unstructureRecord$CLAIMID)
unstructureRecord$DATE_OF_INCIDENT = as.Date(as.character(unstructureRecord$DATE_OF_INCIDENT),format='%Y-%m-%d')
unstructureRecord$DATE_OF_POLICE_REPORT = as.Date(as.character(unstructureRecord$DATE_OF_POLICE_REPORT),format='%Y-%m-%d')

options(warn=-1)

# Initializing Fraud Score variable and Triggered business rule list

FraudScore=0
BRList=list();

if(nrow(unstructureRecord)!=0)
{

# Business Rule1

  if(Loss_date!=unstructureRecord$DATE_OF_INCIDENT)
    {
      FraudScore=FraudScore+20
      BRList=c(BRList,"Mismatch between Date of incident and Loss date")
    }

#Business Rule2

  date_pattern<-parse(file = "unstructureRecord", n = NULL, text = unstructureRecord$DATE_OF_POLICE_REPORT)

#CHECK FOR POLICE DATE [UNSTRUCTURED DATA]

  CHECK_POLICE_DATE <- is.na(date_pattern)

  Rule2a <- ClaimRecord$POLICE_REPORT
  Rule2b <- CHECK_POLICE_DATE

  if(Rule2a=="YES" && Rule2b=="TRUE")
    {
      FraudScore=FraudScore+20;
      BRList=c(BRList,"Mismatch in police report data")
    }

  if(Rule2a=="NO" && Rule2b=="FALSE")
    {
      FraudScore=FraudScore+20;
      BRList=c(BRList,"Mismatch in police report data")
    }

#Business Rule3

  Rule3a<-grep("DIDN'T REALIZE",unstructureRecord$REMARKS,ignore.case=F,fixed = TRUE)

  Rule3b<-grep("Careless",unstructureRecord$REMARKS,ignore.case=F,fixed = TRUE)

  Rule3c<-grep("Did not notice",unstructureRecord$REMARKS,ignore.case=F,fixed = TRUE)

  BR_CHECK <- Rule13a||Rule13b||Rule13c != 0
  Rule3 <- isTRUE(BR_CHECK)

  if(Rule3==TRUE)
    {
      FraudScore=FraudScore+20;
      BRList=c(BRList,"Unwanted terms were found")
    }

#Business Rule4

  Rule4 <-is.na(unstructureRecord$REMARKS)

  if(Rule4==TRUE)
    {
      FraudScore=FraudScore+20;
      BRList=c(BRList,"Remarks not present")
    }

# Printing the final outputs
  cat("\n\n\n")

}

if(FraudScore>0)
{
  cat("Fraud Score =",FraudScore)

  cat("\n\n\nThe List of triggered business rules are:\n\n")

  paste(BRList)
}

if(FraudScore==0)
{
  cat("Fraud Score =",FraudScore)

  cat("\n\n\nNo Fraud Business rules were triggered for this claim\n\n")
}

if(nrow(unstructureRecord)==0)
{
  print("CLAIMID NOT FOUND")
}

odbcClose(channel)