diff --git a/main.py b/main.py
index a4ff673..795b4c1 100644
--- a/main.py
+++ b/main.py
@@ -36,8 +36,9 @@ from tabulate import tabulate
 # 프로젝트 모듈
 from data.transition_matrices import (
     load_transition_matrices, compute_ttc_matrix,
-    get_default_rates, display_matrix, RATING_GRADES
+    get_default_rates, display_matrix, RATING_GRADES, RATING_GRADES_8
 )
+from data.ccc_interpolator import expand_to_8x8
 from data.macro_data import load_macro_data, _fallback_macro_data, compute_derived_features
 from models.credit_cycle import estimate_zt_series, estimate_rho_and_zt
 from models.vasicek import conditional_pd, worst_case_pd
@@ -227,7 +228,12 @@ def main():
     print("  [5/7] 50년 Lifetime PD 산출")
     print("=" * 70)
     
-    pd_engine = LifetimePDEngine(ttc_matrix, rho)
+    # 7x7 TTC -> 8x8 TTC (CCC interpolation)
+    ttc_8x8 = expand_to_8x8(ttc_matrix)
+    print(f"\n  7x7 TTC -> 8x8 TTC (CCC interpolated)")
+    print(display_matrix(ttc_8x8, "TTC 8x8 (CCC interpolated)"))
+
+    pd_engine = LifetimePDEngine(ttc_8x8, rho, rating_grades=RATING_GRADES_8)
     pd_results = pd_engine.compute_all_scenarios(z_paths, weights, horizon)
     
     # 누적 PD 테이블
@@ -244,8 +250,8 @@ def main():
     
     # Vasicek Worst-Case 비교
     print("\n  === Basel II Worst-Case PD (99.9% VaR) ===")
-    ttc_pds = ttc_matrix[:-1, -1]
-    for i, grade in enumerate(RATING_GRADES[:-1]):
+    ttc_pds = ttc_8x8[:-1, -1]
+    for i, grade in enumerate(RATING_GRADES_8[:-1]):
         wc = worst_case_pd(ttc_pds[i], rho)
         print(f"    {grade}: TTC={ttc_pds[i]*100:.3f}% → WC={wc*100:.3f}%")