diff --git a/models/marts/reporting/rep_exchange__survival_analysis.sql b/models/marts/reporting/rep_exchange__survival_analysis.sql
index 046dd4d..15fea1d 100644
--- a/models/marts/reporting/rep_exchange__survival_analysis.sql
+++ b/models/marts/reporting/rep_exchange__survival_analysis.sql
@@ -17,7 +17,7 @@ transaction_orders AS (
 -- LOGIC
 -- duration_table cte computes the survival time and customer churned indicator
 duration_table AS (
-
+ 
     SELECT
         companies.company_id,                   --subject
         companies.company_created_datetime,     -- event start datetime
@@ -107,7 +107,6 @@ compute_censored_subjects AS (
 
 ),
 
-
 compute_probability AS (
 
     SELECT
@@ -115,17 +114,27 @@ compute_probability AS (
 
         -- The survival probability represents the probability of customers that will not churn up to a specific tenure
         -- Example: survival_day = 61, survival_prob = 95%. For customers with 61 days of tenure, the customer has a 95% chance of not churning.
-        EXP(SUM(LN(1 - events / at_risk)) OVER (
-            ORDER BY survival_time_days ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
-        ))      AS survival_probability,
+        -- When events / at_risk = 1, we replace value 1 with a value very near to 1, to prevent log 0 which causes infinity value
+        EXP(SUM(LN
+                (
+                CASE WHEN (1 - events / at_risk) = 0 THEN 0.999999 ELSE (1 - events / at_risk) END
+                )) 
+            OVER (
+                ORDER BY survival_time_days ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
+                ))      AS survival_probability,
 
-        100 * (1 - EXP(SUM(LN(1 - events / at_risk)) OVER (
-            ORDER BY survival_time_days ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
-        )))     AS conversion_percentage,
+        100 * (1 - EXP(SUM(LN
+                (
+                CASE WHEN (1 - events / at_risk) = 0 THEN 0.999999 ELSE (1 - events / at_risk) END
+                )) 
+            OVER (
+                ORDER BY survival_time_days ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
+                )))     AS conversion_percentage,
 
-        SUM(events / at_risk) OVER (
+        SUM(events / at_risk) 
+            OVER (
             ORDER BY survival_time_days ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
-        )       AS cumulative_hazard,
+                 )      AS cumulative_hazard,
 
         '{{ modules.datetime.datetime.now(modules.pytz.timezone("Asia/Kuala_Lumpur")) }}'       AS _dbt_ran_datetime