Buku Panduan Sistem AO BPRS

from decimal import Decimal
from typing import Dict

class ProductionScoringEngine:
    """
    ENGINE SKOR KREDIT PRODUKSI (Production Ready).
    
    Metodologi: Weighted Scorecard (Tabel Bobot).
    Pendekatan ini bersifat transparan (White Box), memudahkan penjelasan ke nasabah 
    dan audit internal, sesuai standar perbankan.
    """
    
    # Konstanta Bobot (Weights) - Dapat disesuaikan oleh Komite Risiko
    BASE_SCORE = 300
    MAX_SCORE = 850
    
    # Threshold Segmen
    SEGMENT_HIGH_RISK_THRESHOLD = 550
    SEGMENT_MED_RISK_THRESHOLD = 700
    
    def calculate_score(self, monthly_income: float, assets: float, loan_amount: float, tenor_months: int) -> Dict:
        """
        Input: Data finansial nasabah.
        Output: Skor Kredit (300-850), Probabilitas Gagal Bayar (%), dan Segmen.
        """
        
        # --- 1. Perhitungan Angsuran (Flat Rate Syariah - Margin) ---
        # Asumsi Margin Standar untuk perhitungan kapasitas bayar (Contoh: 15% flat per tahun)
        margin_rate = 0.15 
        total_margin = loan_amount * margin_rate
        total_debt = loan_amount + total_margin
        monthly_installment = total_debt / tenor_months
        
        # --- 2. Variabel Penilaian (Assessment Variables) ---
        
        # A. Debt Service Ratio (DSR) = Angsuran / Pendapatan Bersih
        # Standar OJK/Bank Umum: DSR aman di bawah 35-40%
        if monthly_income <= 0:
            dsr_score = -200 # Risiko maksimal jika tidak ada penghasilan
        else:
            dsr = monthly_installment / monthly_income
            if dsr <= 0.30:
                dsr_score = 150      # Sangat Sehat
            elif dsr <= 0.40:
                dsr_score = 100      # Sehat
            elif dsr <= 0.50:
                dsr_score = 0        # Waspada (Netral)
            else:
                dsr_score = -150     # Berisiko (Cicilan membebani)

        # B. Asset Coverage Ratio (ACR) = Total Aset / Plafond Pinjaman
        # Jaminan/Agunan yang kuat menurunkan risiko kerugian (Loss Given Default)
        if loan_amount <= 0:
            acr_score = 0
        else:
            acr = assets / loan_amount
            if acr >= 1.2:
                acr_score = 100      # Aset melampaui pinjaman 20%
            elif acr >= 0.8:
                acr_score = 50       # Aset mendekati pinjaman
            else:
                acr_score = -50      # Aset kurang mencukupi

        # C. Tenor Risk (Jangka Waktu)
        # Semakin lama tenor, semakin tinggi ketidakpastian
        if tenor_months <= 12:
            tenor_score = 50
        elif tenor_months <= 24:
            tenor_score = 20
        elif tenor_months <= 36:
            tenor_score = -20
        else:
            tenor_score = -50

        # --- 3. Agregasi Skor ---
        final_score = self.BASE_SCORE + dsr_score + acr_score + tenor_score
        
        # Clamp skor agar tidak melebihi batas min/max
        final_score = max(self.BASE_SCORE, min(self.MAX_SCORE, int(final_score)))
        
        # --- 4. Probabilitas Gagal Bayar (Default Probability) ---
        # Kurva Invers: Skor Tinggi -> Probabilitas Rendah
        # Rumus Linear Sederhana untuk Produksi
        if final_score >= 750:
            pd = 0.01   # 1%
        elif final_score >= 650:
            pd = 0.05   # 5%
        elif final_score >= 550:
            pd = 0.15   # 15%
        else:
            pd = 0.40   # 40% (Sangat berisiko)

        # --- 5. Segmentasi ---
        if final_score >= self.SEGMENT_MED_RISK_THRESHOLD:
            segment = "low"
        elif final_score >= self.SEGMENT_HIGH_RISK_THRESHOLD:
            segment = "medium"
        else:
            segment = "high"

        return {
            "credit_score": final_score,
            "default_probability": float(pd),
            "segment": segment,
            "dsr": round(monthly_installment / monthly_income if monthly_income > 0 else 0, 2),
            "monthly_installment": round(monthly_installment, 2),
            "assessment": {
                "dsr_score": dsr_score,
                "acr_score": acr_score,
                "tenor_score": tenor_score
            }
        }

# Instance Engine
scoring_engine = ProductionScoringEngine()