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block.py

@@ -16,33 +16,24 @@ logger = logging.getLogger(__name__)
 def __main__(application_id: str, creditBureau: dict) -> Dict:
     """
     Process a single application record via the scoring pipeline.
-    Accepts extra keys; only required features are used and others ignored.
-
     Returns:
         A dict containing:
           - prediction: float
           - grade: str
           - reason_description: str or None
     """
-    # whitelist of required feature keys (lowercase)
-    required_keys = {
-        'application_id',
-        'evtg04','eads66','s004s','utlmag02','cv13','rev231','rev14','g106s','ct320',
-        'mt34s','trv01','g250a','g960s','re36s','rev232','bc102s','utlmag04','re102s',
-        'agg911','p02h','g051s','g417s','bc20s','rev225','duemag01','fi21s','us21s',
-        'us34s','at36s','g102s','bkc14','balmag04','bkc323','bkc84','rev202','cta20',
-        'cta21','agg902','utlmag03','rev84','mt20s','bc21s','st32s','fi34s','rev201',
-        'bc97a','balmag01','g232s','balmag02','index02','bc28s','at28a','rev322','bkc322',
-        'g201a','g416s','walshr02','fi35s','rle904','re28s','rev233','rev224','rev252',
-        'rev253','cv21','rev321','index01','bkc328','br20s','pb34s','g403s','ct319','at28b',
-        'mnpmag03','utlmag01','bc36s','bkc321','agg908','cv25','bc107s','bkc327','g990s',
-        'pb28s','g411s','g221d','bc104s','g405s','p02d','ret12','bc98a','trv02','rev54',
-        'bkc324','s114s','paymnt08','g105s','rev223','rev12','rev13','all231','agg901',
-        'g408s','rev203','rvlr75','rvlr77','cv17','cta11','g242b'
-    }
-
     record = extract_model_variables(creditBureau)
 
+    if not record:
+        final_result = {
+            'application_id': application_id,
+            'prediction':        0.99,
+            'grade':             'M14',
+            'reason_description': "Lack of account information",
+        }
+        logger.info(f"final_result (early exit due to missing or empty extracted variables): {final_result}")
+        return final_result
+
     processed = pre_processing(record)
 
     out = processing(processed)
@@ -62,6 +53,7 @@ def __main__(application_id: str, creditBureau: dict) -> Dict:
 
     return final_result
 
+
 if __name__ == "__main__":
     import json, sys
     with open(sys.argv[1]) as f:

parse_report.py

@@ -125,6 +125,8 @@ def safe_get(d, *keys):
 
 
 def extract_model_variables(creditBureau: dict) -> dict:
+    if not creditBureau:
+        return {}
     variable_code_map = VARIABLE_TO_CODE_MAP
     score_code_map = SCORE_TO_CODE_MAP
     # Step 0: Extract application_id
@@ -146,7 +148,7 @@ def extract_model_variables(creditBureau: dict) -> dict:
 
 
     # Step 2: Flatten values
-    for product in add_ons:
+    for product in add_ons if isinstance(add_ons, list) else []:
         code = product.get("code")
         score_model = safe_get(product, "score_model", "scoreModel")
 

post_processing.py

@@ -4,7 +4,7 @@ def post_processing(processing_output):
     prediction       = processing_output["prediction"]
     shape_reasoncode = processing_output["shape_reasoncode"]
 
-    # grade mapping: [0.00,0.01]→M1, (0.01,0.02]→M2, … cap at M14
+    # grade mapping:
     if prediction < 0:
         grade = "M14"
     else:
@@ -28,21 +28,26 @@ def post_processing(processing_output):
         'ct320':    lambda x: x <= 3,
         'us21s':    lambda x: x <= 3,
         'utlmag02': lambda x: x > 300,
-        'trv01':    lambda x: x > 3,
-        'us34s':    lambda x: x > 90
+        # 'trv01':    lambda x: x > 3,
+        'trv01':    lambda x: x <= 3,
+        'us34s':    lambda x: x > 90     
     }
 
     reason_map = {
         'evtg04':   "System Generated",
         'eads66':   "System Generated",
         's004s':    "Length of time on file is too short",
-        'mt34s':    "Too high open mortgage credit utilization recently",
+        # 'mt34s':    "Too high open mortgage credit utilization recently",
+        'mt34s':    "Not enough balance decreases on mortgage trades in the past 12 months",
         'ct320':    "Insufficient payment activity",
         'us21s':    "Length of time since most recent installment account has been established is too short",
-        'utlmag02': "Too high revolving credit utilization over the last 24 months",
+        # 'utlmag02': "Too high revolving credit utilization over the last 24 months",
+        'utlmag02': "Revolving account balances are too high in proportion to credit limits over the last 24 months",
         'trv01':    "Recency of a balance overlimit on a bankcard account",
-        'us34s':    "Too high open unsecured installment credit utilization recently"
+        # 'us34s':    "Too high open unsecured installment credit utilization recently"
+        'us34s':    "Not enough balance decreases on installment trades in the past 12 months"
     }
+    
 
     for item in shape_reasoncode:
         feat = item["feature"]
@@ -56,6 +61,6 @@ def post_processing(processing_output):
 
     return {
         "grade":             grade,
-        "reason_description": None
+        "reason_description": "No suitable Product Offerings found"
     }