generated from user_client2024/77
System save at 27/11/2025 12:34 by user_client2024
This commit is contained in:
user_client2024
parent
da51a842da
commit
8ce2096a03
@ -157,7 +157,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 57,
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||||
"execution_count": 77,
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"id": "d220561a-34c9-48d2-8e2f-5d174a87540b",
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"metadata": {
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"tags": []
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@ -189,7 +189,7 @@
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" df.groupby(\"Segment\")[[\"Credit_transaction_amount\",\n",
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" \"Debit_transaction_amount\",\n",
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" \"Wash_Ratio\"]]\n",
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" .quantile(0.98)\n",
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" .quantile(0.90)\n",
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" .reset_index()\n",
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" )\n",
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"\n",
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@ -205,13 +205,13 @@
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"\n",
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" # Step 3: Identify customers above 90th percentile in ANY of the 3 metrics\n",
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" high_pop = (\n",
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" (df[\"Credit_transaction_amount\"] > df[\"P90_Credit\"]) |\n",
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" (df[\"Debit_transaction_amount\"] > df[\"P90_Debit\"]) |\n",
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" # (df[\"Credit_transaction_amount\"] > df[\"P90_Credit\"]) &\n",
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" (df[\"Debit_transaction_amount\"] > df[\"P90_Debit\"]) &\n",
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" (df[\"Wash_Ratio\"] > df[\"P90_Wash\"])\n",
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" )\n",
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"\n",
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" # Step 4: Randomly select 0.1% sample from high-risk population\n",
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" sample_fraction = 0.1 # 0.1%\n",
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" sample_fraction = 0.1 # 0.1%\n",
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" high_pop_indices = df[high_pop].sample(frac=sample_fraction, random_state=42).index\n",
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"\n",
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" # Step 5: Set SAR_FLAG values\n",
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@ -222,299 +222,32 @@
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},
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{
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"cell_type": "code",
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"execution_count": 58,
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"execution_count": 83,
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"id": "2e5a0ea9-64cd-4a8d-9a5d-e5e7b36a401a",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"sen = Scenario()\n",
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"a = sen.logic()"
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"# sen = Scenario()\n",
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"# a = sen.logic()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 59,
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"execution_count": 82,
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"id": "830c7ec3-9707-46db-9b27-ac4f9d46a03a",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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||||
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Focal_id</th>\n",
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" <th>Credit_transaction_amount</th>\n",
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" <th>Total_no_of_credit_transactions</th>\n",
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" <th>Debit_transaction_amount</th>\n",
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" <th>Total_no_of_debit_transactions</th>\n",
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" <th>Wash_Ratio</th>\n",
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" <th>Segment</th>\n",
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" <th>Risk</th>\n",
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" <th>SAR_FLAG</th>\n",
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" <th>P90_Credit</th>\n",
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" <th>P90_Debit</th>\n",
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" <th>P90_Wash</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>PN478710</td>\n",
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" <td>2805352312</td>\n",
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" <td>2020</td>\n",
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" <td>2787126309</td>\n",
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" <td>2025</td>\n",
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" <td>1.006539</td>\n",
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" <td>Corporate Banking</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" <td>6.274828e+09</td>\n",
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" <td>6.259298e+09</td>\n",
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" <td>1.090121</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>PN483125</td>\n",
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" <td>3890052135</td>\n",
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" <td>2797</td>\n",
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" <td>3968882113</td>\n",
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" <td>2850</td>\n",
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" <td>0.980138</td>\n",
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" <td>Govt. Entities</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" <td>6.112897e+09</td>\n",
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" <td>6.072409e+09</td>\n",
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" <td>1.112059</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>PN890403</td>\n",
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" <td>4136296083</td>\n",
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" <td>2937</td>\n",
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" <td>3999785063</td>\n",
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" <td>2824</td>\n",
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" <td>1.034130</td>\n",
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" <td>SME</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" <td>5.709904e+09</td>\n",
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" <td>5.559419e+09</td>\n",
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" <td>1.118816</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>PN531475</td>\n",
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" <td>4183673982</td>\n",
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" <td>2861</td>\n",
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" <td>3987068168</td>\n",
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" <td>2770</td>\n",
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" <td>1.049311</td>\n",
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" <td>Corporate Banking</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" <td>6.274828e+09</td>\n",
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" <td>6.259298e+09</td>\n",
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" <td>1.090121</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>PN147722</td>\n",
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" <td>1775594615</td>\n",
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" <td>1225</td>\n",
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" <td>1641559222</td>\n",
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" <td>1221</td>\n",
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" <td>1.081651</td>\n",
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" <td>SME</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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||||
" <td>5.709904e+09</td>\n",
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||||
" <td>5.559419e+09</td>\n",
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" <td>1.118816</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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||||
" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10009</th>\n",
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" <td>PN955059</td>\n",
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" <td>31106290</td>\n",
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" <td>264</td>\n",
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||||
" <td>25266130</td>\n",
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" <td>369</td>\n",
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||||
" <td>1.231146</td>\n",
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" <td>Priority Banking</td>\n",
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" <td>Low Risk</td>\n",
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||||
" <td>N</td>\n",
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||||
" <td>7.616620e+07</td>\n",
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||||
" <td>5.263062e+07</td>\n",
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" <td>1.921224</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10010</th>\n",
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" <td>PN602067</td>\n",
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" <td>29780658</td>\n",
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" <td>238</td>\n",
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" <td>27796448</td>\n",
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" <td>405</td>\n",
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" <td>1.071384</td>\n",
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" <td>Others</td>\n",
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" <td>High Risk</td>\n",
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" <td>N</td>\n",
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" <td>7.897534e+07</td>\n",
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" <td>5.488447e+07</td>\n",
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" <td>1.931817</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10011</th>\n",
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" <td>PN213487</td>\n",
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" <td>41410071</td>\n",
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" <td>274</td>\n",
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" <td>23896844</td>\n",
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" <td>368</td>\n",
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" <td>1.732868</td>\n",
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" <td>Others</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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" <td>7.897534e+07</td>\n",
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" <td>5.488447e+07</td>\n",
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" <td>1.931817</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10012</th>\n",
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" <td>PN563065</td>\n",
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" <td>34009021</td>\n",
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" <td>251</td>\n",
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" <td>32563582</td>\n",
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" <td>375</td>\n",
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" <td>1.044388</td>\n",
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" <td>Others</td>\n",
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" <td>Low Risk</td>\n",
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" <td>N</td>\n",
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||||
" <td>7.897534e+07</td>\n",
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||||
" <td>5.488447e+07</td>\n",
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" <td>1.931817</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>10013</th>\n",
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" <td>PN388875</td>\n",
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" <td>30904340</td>\n",
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||||
" <td>236</td>\n",
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||||
" <td>21938266</td>\n",
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" <td>344</td>\n",
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" <td>1.408696</td>\n",
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" <td>Mass Market</td>\n",
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" <td>Medium Risk</td>\n",
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" <td>N</td>\n",
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" <td>7.921967e+07</td>\n",
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" <td>5.290545e+07</td>\n",
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" <td>1.915159</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>10014 rows × 12 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" Focal_id Credit_transaction_amount Total_no_of_credit_transactions \\\n",
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"0 PN478710 2805352312 2020 \n",
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"1 PN483125 3890052135 2797 \n",
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"2 PN890403 4136296083 2937 \n",
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"3 PN531475 4183673982 2861 \n",
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"4 PN147722 1775594615 1225 \n",
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"... ... ... ... \n",
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"10009 PN955059 31106290 264 \n",
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"10010 PN602067 29780658 238 \n",
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"10011 PN213487 41410071 274 \n",
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"10012 PN563065 34009021 251 \n",
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"10013 PN388875 30904340 236 \n",
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"\n",
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" Debit_transaction_amount Total_no_of_debit_transactions Wash_Ratio \\\n",
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"0 2787126309 2025 1.006539 \n",
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"1 3968882113 2850 0.980138 \n",
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"2 3999785063 2824 1.034130 \n",
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"3 3987068168 2770 1.049311 \n",
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"4 1641559222 1221 1.081651 \n",
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"... ... ... ... \n",
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"10009 25266130 369 1.231146 \n",
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"10010 27796448 405 1.071384 \n",
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||||
"10011 23896844 368 1.732868 \n",
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"10012 32563582 375 1.044388 \n",
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"10013 21938266 344 1.408696 \n",
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"\n",
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" Segment Risk SAR_FLAG P90_Credit P90_Debit \\\n",
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"0 Corporate Banking Low Risk N 6.274828e+09 6.259298e+09 \n",
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"1 Govt. Entities Low Risk N 6.112897e+09 6.072409e+09 \n",
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"2 SME Low Risk N 5.709904e+09 5.559419e+09 \n",
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"3 Corporate Banking Low Risk N 6.274828e+09 6.259298e+09 \n",
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"4 SME Low Risk N 5.709904e+09 5.559419e+09 \n",
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"... ... ... ... ... ... \n",
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"10009 Priority Banking Low Risk N 7.616620e+07 5.263062e+07 \n",
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"10010 Others High Risk N 7.897534e+07 5.488447e+07 \n",
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"10011 Others Low Risk N 7.897534e+07 5.488447e+07 \n",
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"10012 Others Low Risk N 7.897534e+07 5.488447e+07 \n",
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"10013 Mass Market Medium Risk N 7.921967e+07 5.290545e+07 \n",
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"\n",
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" P90_Wash \n",
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"0 1.090121 \n",
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"1 1.112059 \n",
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"2 1.118816 \n",
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||||
"3 1.090121 \n",
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"4 1.118816 \n",
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||||
"... ... \n",
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||||
"10009 1.921224 \n",
|
||||
"10010 1.931817 \n",
|
||||
"10011 1.931817 \n",
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||||
"10012 1.931817 \n",
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"10013 1.915159 \n",
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"\n",
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"[10014 rows x 12 columns]"
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]
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},
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"execution_count": 59,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"a"
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"# a"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"execution_count": 81,
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"id": "150bb5ce-6be1-44fc-a606-6d375354626d",
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"metadata": {
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"tags": []
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291
main.ipynb
291
main.ipynb
@ -157,7 +157,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 57,
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"execution_count": 77,
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||||
"id": "d220561a-34c9-48d2-8e2f-5d174a87540b",
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||||
"metadata": {
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||||
"tags": []
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@ -189,7 +189,7 @@
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" df.groupby(\"Segment\")[[\"Credit_transaction_amount\",\n",
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" \"Debit_transaction_amount\",\n",
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" \"Wash_Ratio\"]]\n",
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" .quantile(0.98)\n",
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" .quantile(0.90)\n",
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" .reset_index()\n",
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" )\n",
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"\n",
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@ -205,13 +205,13 @@
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"\n",
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" # Step 3: Identify customers above 90th percentile in ANY of the 3 metrics\n",
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" high_pop = (\n",
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" (df[\"Credit_transaction_amount\"] > df[\"P90_Credit\"]) |\n",
|
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" (df[\"Debit_transaction_amount\"] > df[\"P90_Debit\"]) |\n",
|
||||
" # (df[\"Credit_transaction_amount\"] > df[\"P90_Credit\"]) &\n",
|
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" (df[\"Debit_transaction_amount\"] > df[\"P90_Debit\"]) &\n",
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" (df[\"Wash_Ratio\"] > df[\"P90_Wash\"])\n",
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" )\n",
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"\n",
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" # Step 4: Randomly select 0.1% sample from high-risk population\n",
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" sample_fraction = 0.1 # 0.1%\n",
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" sample_fraction = 0.1 # 0.1%\n",
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" high_pop_indices = df[high_pop].sample(frac=sample_fraction, random_state=42).index\n",
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"\n",
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" # Step 5: Set SAR_FLAG values\n",
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@ -222,299 +222,32 @@
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},
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{
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"cell_type": "code",
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"execution_count": 58,
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||||
"execution_count": 83,
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||||
"id": "2e5a0ea9-64cd-4a8d-9a5d-e5e7b36a401a",
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||||
"metadata": {
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||||
"tags": []
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||||
},
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||||
"outputs": [],
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||||
"source": [
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"sen = Scenario()\n",
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"a = sen.logic()"
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"# sen = Scenario()\n",
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"# a = sen.logic()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 59,
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"execution_count": 82,
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||||
"id": "830c7ec3-9707-46db-9b27-ac4f9d46a03a",
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"metadata": {
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||||
"tags": []
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},
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"outputs": [
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||||
{
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||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>Focal_id</th>\n",
|
||||
" <th>Credit_transaction_amount</th>\n",
|
||||
" <th>Total_no_of_credit_transactions</th>\n",
|
||||
" <th>Debit_transaction_amount</th>\n",
|
||||
" <th>Total_no_of_debit_transactions</th>\n",
|
||||
" <th>Wash_Ratio</th>\n",
|
||||
" <th>Segment</th>\n",
|
||||
" <th>Risk</th>\n",
|
||||
" <th>SAR_FLAG</th>\n",
|
||||
" <th>P90_Credit</th>\n",
|
||||
" <th>P90_Debit</th>\n",
|
||||
" <th>P90_Wash</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>PN478710</td>\n",
|
||||
" <td>2805352312</td>\n",
|
||||
" <td>2020</td>\n",
|
||||
" <td>2787126309</td>\n",
|
||||
" <td>2025</td>\n",
|
||||
" <td>1.006539</td>\n",
|
||||
" <td>Corporate Banking</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>6.274828e+09</td>\n",
|
||||
" <td>6.259298e+09</td>\n",
|
||||
" <td>1.090121</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>PN483125</td>\n",
|
||||
" <td>3890052135</td>\n",
|
||||
" <td>2797</td>\n",
|
||||
" <td>3968882113</td>\n",
|
||||
" <td>2850</td>\n",
|
||||
" <td>0.980138</td>\n",
|
||||
" <td>Govt. Entities</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>6.112897e+09</td>\n",
|
||||
" <td>6.072409e+09</td>\n",
|
||||
" <td>1.112059</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>PN890403</td>\n",
|
||||
" <td>4136296083</td>\n",
|
||||
" <td>2937</td>\n",
|
||||
" <td>3999785063</td>\n",
|
||||
" <td>2824</td>\n",
|
||||
" <td>1.034130</td>\n",
|
||||
" <td>SME</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>5.709904e+09</td>\n",
|
||||
" <td>5.559419e+09</td>\n",
|
||||
" <td>1.118816</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>PN531475</td>\n",
|
||||
" <td>4183673982</td>\n",
|
||||
" <td>2861</td>\n",
|
||||
" <td>3987068168</td>\n",
|
||||
" <td>2770</td>\n",
|
||||
" <td>1.049311</td>\n",
|
||||
" <td>Corporate Banking</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>6.274828e+09</td>\n",
|
||||
" <td>6.259298e+09</td>\n",
|
||||
" <td>1.090121</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>PN147722</td>\n",
|
||||
" <td>1775594615</td>\n",
|
||||
" <td>1225</td>\n",
|
||||
" <td>1641559222</td>\n",
|
||||
" <td>1221</td>\n",
|
||||
" <td>1.081651</td>\n",
|
||||
" <td>SME</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>5.709904e+09</td>\n",
|
||||
" <td>5.559419e+09</td>\n",
|
||||
" <td>1.118816</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10009</th>\n",
|
||||
" <td>PN955059</td>\n",
|
||||
" <td>31106290</td>\n",
|
||||
" <td>264</td>\n",
|
||||
" <td>25266130</td>\n",
|
||||
" <td>369</td>\n",
|
||||
" <td>1.231146</td>\n",
|
||||
" <td>Priority Banking</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>7.616620e+07</td>\n",
|
||||
" <td>5.263062e+07</td>\n",
|
||||
" <td>1.921224</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10010</th>\n",
|
||||
" <td>PN602067</td>\n",
|
||||
" <td>29780658</td>\n",
|
||||
" <td>238</td>\n",
|
||||
" <td>27796448</td>\n",
|
||||
" <td>405</td>\n",
|
||||
" <td>1.071384</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>High Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>7.897534e+07</td>\n",
|
||||
" <td>5.488447e+07</td>\n",
|
||||
" <td>1.931817</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10011</th>\n",
|
||||
" <td>PN213487</td>\n",
|
||||
" <td>41410071</td>\n",
|
||||
" <td>274</td>\n",
|
||||
" <td>23896844</td>\n",
|
||||
" <td>368</td>\n",
|
||||
" <td>1.732868</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>7.897534e+07</td>\n",
|
||||
" <td>5.488447e+07</td>\n",
|
||||
" <td>1.931817</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10012</th>\n",
|
||||
" <td>PN563065</td>\n",
|
||||
" <td>34009021</td>\n",
|
||||
" <td>251</td>\n",
|
||||
" <td>32563582</td>\n",
|
||||
" <td>375</td>\n",
|
||||
" <td>1.044388</td>\n",
|
||||
" <td>Others</td>\n",
|
||||
" <td>Low Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>7.897534e+07</td>\n",
|
||||
" <td>5.488447e+07</td>\n",
|
||||
" <td>1.931817</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10013</th>\n",
|
||||
" <td>PN388875</td>\n",
|
||||
" <td>30904340</td>\n",
|
||||
" <td>236</td>\n",
|
||||
" <td>21938266</td>\n",
|
||||
" <td>344</td>\n",
|
||||
" <td>1.408696</td>\n",
|
||||
" <td>Mass Market</td>\n",
|
||||
" <td>Medium Risk</td>\n",
|
||||
" <td>N</td>\n",
|
||||
" <td>7.921967e+07</td>\n",
|
||||
" <td>5.290545e+07</td>\n",
|
||||
" <td>1.915159</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>10014 rows × 12 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Focal_id Credit_transaction_amount Total_no_of_credit_transactions \\\n",
|
||||
"0 PN478710 2805352312 2020 \n",
|
||||
"1 PN483125 3890052135 2797 \n",
|
||||
"2 PN890403 4136296083 2937 \n",
|
||||
"3 PN531475 4183673982 2861 \n",
|
||||
"4 PN147722 1775594615 1225 \n",
|
||||
"... ... ... ... \n",
|
||||
"10009 PN955059 31106290 264 \n",
|
||||
"10010 PN602067 29780658 238 \n",
|
||||
"10011 PN213487 41410071 274 \n",
|
||||
"10012 PN563065 34009021 251 \n",
|
||||
"10013 PN388875 30904340 236 \n",
|
||||
"\n",
|
||||
" Debit_transaction_amount Total_no_of_debit_transactions Wash_Ratio \\\n",
|
||||
"0 2787126309 2025 1.006539 \n",
|
||||
"1 3968882113 2850 0.980138 \n",
|
||||
"2 3999785063 2824 1.034130 \n",
|
||||
"3 3987068168 2770 1.049311 \n",
|
||||
"4 1641559222 1221 1.081651 \n",
|
||||
"... ... ... ... \n",
|
||||
"10009 25266130 369 1.231146 \n",
|
||||
"10010 27796448 405 1.071384 \n",
|
||||
"10011 23896844 368 1.732868 \n",
|
||||
"10012 32563582 375 1.044388 \n",
|
||||
"10013 21938266 344 1.408696 \n",
|
||||
"\n",
|
||||
" Segment Risk SAR_FLAG P90_Credit P90_Debit \\\n",
|
||||
"0 Corporate Banking Low Risk N 6.274828e+09 6.259298e+09 \n",
|
||||
"1 Govt. Entities Low Risk N 6.112897e+09 6.072409e+09 \n",
|
||||
"2 SME Low Risk N 5.709904e+09 5.559419e+09 \n",
|
||||
"3 Corporate Banking Low Risk N 6.274828e+09 6.259298e+09 \n",
|
||||
"4 SME Low Risk N 5.709904e+09 5.559419e+09 \n",
|
||||
"... ... ... ... ... ... \n",
|
||||
"10009 Priority Banking Low Risk N 7.616620e+07 5.263062e+07 \n",
|
||||
"10010 Others High Risk N 7.897534e+07 5.488447e+07 \n",
|
||||
"10011 Others Low Risk N 7.897534e+07 5.488447e+07 \n",
|
||||
"10012 Others Low Risk N 7.897534e+07 5.488447e+07 \n",
|
||||
"10013 Mass Market Medium Risk N 7.921967e+07 5.290545e+07 \n",
|
||||
"\n",
|
||||
" P90_Wash \n",
|
||||
"0 1.090121 \n",
|
||||
"1 1.112059 \n",
|
||||
"2 1.118816 \n",
|
||||
"3 1.090121 \n",
|
||||
"4 1.118816 \n",
|
||||
"... ... \n",
|
||||
"10009 1.921224 \n",
|
||||
"10010 1.931817 \n",
|
||||
"10011 1.931817 \n",
|
||||
"10012 1.931817 \n",
|
||||
"10013 1.915159 \n",
|
||||
"\n",
|
||||
"[10014 rows x 12 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 59,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"a"
|
||||
"# a"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 49,
|
||||
"execution_count": 81,
|
||||
"id": "150bb5ce-6be1-44fc-a606-6d375354626d",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
|
||||
22
main.py
22
main.py
@ -114,7 +114,7 @@ query = """
|
||||
"""
|
||||
|
||||
|
||||
# In[57]:
|
||||
# In[77]:
|
||||
|
||||
|
||||
from tms_data_interface import SQLQueryInterface
|
||||
@ -142,7 +142,7 @@ class Scenario:
|
||||
df.groupby("Segment")[["Credit_transaction_amount",
|
||||
"Debit_transaction_amount",
|
||||
"Wash_Ratio"]]
|
||||
.quantile(0.98)
|
||||
.quantile(0.90)
|
||||
.reset_index()
|
||||
)
|
||||
|
||||
@ -158,13 +158,13 @@ class Scenario:
|
||||
|
||||
# Step 3: Identify customers above 90th percentile in ANY of the 3 metrics
|
||||
high_pop = (
|
||||
(df["Credit_transaction_amount"] > df["P90_Credit"]) |
|
||||
(df["Debit_transaction_amount"] > df["P90_Debit"]) |
|
||||
# (df["Credit_transaction_amount"] > df["P90_Credit"]) &
|
||||
(df["Debit_transaction_amount"] > df["P90_Debit"]) &
|
||||
(df["Wash_Ratio"] > df["P90_Wash"])
|
||||
)
|
||||
|
||||
# Step 4: Randomly select 0.1% sample from high-risk population
|
||||
sample_fraction = 0.1 # 0.1%
|
||||
sample_fraction = 0.1 # 0.1%
|
||||
high_pop_indices = df[high_pop].sample(frac=sample_fraction, random_state=42).index
|
||||
|
||||
# Step 5: Set SAR_FLAG values
|
||||
@ -173,20 +173,20 @@ class Scenario:
|
||||
return df
|
||||
|
||||
|
||||
# In[58]:
|
||||
# In[83]:
|
||||
|
||||
|
||||
sen = Scenario()
|
||||
a = sen.logic()
|
||||
# sen = Scenario()
|
||||
# a = sen.logic()
|
||||
|
||||
|
||||
# In[59]:
|
||||
# In[82]:
|
||||
|
||||
|
||||
a
|
||||
# a
|
||||
|
||||
|
||||
# In[49]:
|
||||
# In[81]:
|
||||
|
||||
|
||||
# a[a["SAR_FLAG"] == "Y"]
|
||||
|
||||
Loading…
Reference in New Issue
Block a user