import pandas as pd import numpy_financial as npf from datetime import datetime from dateutil.relativedelta import relativedelta from utils import get_cloudwatch_logger logger = get_cloudwatch_logger(stream_name="bpi_rps_generation_stream") async def function1(data): logger.send_log_event(f"INFO: In 5th_emi_date(bpi rps) function - Request received: \n{data}") loan_principal = data["loan_principal"] annualised_interest = data["annualised_interest"] annualised_irr = data["annualised_irr"] remaining_emi = data["remaining_emi"] disbursal_date_str = data["disbursal_date_str"] first_emi_date_str = data["first_emi_date_str"] morat_months = data["morat_months"] morat_start_date_str = data["morat_start_date_str"] annualised_interest = (annualised_interest/100) annualised_irr = (annualised_irr/100) if annualised_interest == 0: emi_amount = loan_principal/remaining_emi else: emi_amount = npf.pmt(annualised_interest/12,remaining_emi,-loan_principal,0) disbursal_date = datetime.strptime(disbursal_date_str,'%d-%m-%Y').date() first_emi_date = datetime.strptime(first_emi_date_str,'%d-%m-%Y').date() # If morat months mentioned then assign morat date, else random morat date if morat_months > 0: morat_start_date = datetime.strptime(morat_start_date_str,'%d-%m-%Y').date() else: morat_start_date = datetime.strptime('05-11-2016','%d-%m-%Y').date() # Logic to calculate pre_emi_date & add extra month if pre_emi present pre_emi_month = 0 scenario = 0 if disbursal_date.day > 5: scenario = 2 pre_emi_date = first_emi_date - relativedelta(months=1) pre_emi_month = 1 elif disbursal_date.day < 5: scenario = 3 pre_emi_date = first_emi_date - relativedelta(months=1) pre_emi_month = 0 else: scenario = 1 pre_emi_date = first_emi_date pre_emi_month = 0 # Logic to calculate pre_emi_days pre_emi_days = 0 if disbursal_date.day == 5: pre_emi_days = 0 else: pre_emi_days = (pre_emi_date - disbursal_date).days # calculate final tenure extended_tenure = remaining_emi + morat_months + pre_emi_month morat_start_date_array = [] current_date = morat_start_date for i in range(morat_months): morat_start_date_array.append(current_date) current_date = current_date + relativedelta(months=1) # RPS Generation if scenario == 1: # disbursal on 5th amort_array = [] emi_date = first_emi_date pos = loan_principal emi = emi_amount emi_dates = [] morat_interest_comp = 0 bpi_interest_comp = 0 for period in range(1,extended_tenure+1): emi_dates.append(emi_date) if emi_date not in morat_start_date_array: emi = emi_amount interest_comp = pos * 30 * annualised_interest/360 principal_comp = emi - interest_comp pos = pos - principal_comp morat_interest_comp = 0 else: morat_interest_comp = pos * 30 * annualised_irr/360 interest_comp = 0 principal_comp = 0 pos = pos - principal_comp emi = interest_comp + principal_comp amort_array.append({ 'installment_number':period, 'emi_date': emi_date, 'emi_amount': emi, 'bpi_interest': bpi_interest_comp, 'morat_interest': morat_interest_comp, 'interest_comp': interest_comp, 'principal_comp': principal_comp, 'principal_outstanding': pos, 'foreclosure_amount': bpi_interest_comp + morat_interest_comp + interest_comp + principal_comp }) emi_date = emi_date + relativedelta(months=1) if scenario == 2: # disbursal 6th - 31st amort_array = [] emi_date = pre_emi_date pos = loan_principal emi = emi_amount emi_dates = [] morat_interest_comp = 0 bpi_interest_comp = 0 for period in range(1,extended_tenure+1): emi_dates.append(emi_date) if emi_date not in morat_start_date_array: morat_interest_comp = 0 if period == 1: bpi_interest_comp = loan_principal * pre_emi_days * annualised_irr/360 interest_comp = 0 principal_comp = 0 pos = pos - principal_comp emi = 0 else: bpi_interest_comp = 0 emi = emi_amount interest_comp = pos * 30 * annualised_interest/360 principal_comp = emi - interest_comp pos = pos - principal_comp else: interest_comp = 0 bpi_interest_comp = 0 morat_interest_comp = pos * 30 * annualised_irr/360 principal_comp = 0 pos = pos - principal_comp emi = interest_comp + principal_comp amort_array.append({ 'installment_number':period, 'emi_date': emi_date, 'emi_amount': emi, 'bpi_interest': bpi_interest_comp, 'morat_interest': morat_interest_comp, 'interest_comp': interest_comp, 'principal_comp': principal_comp, 'principal_outstanding': pos, 'foreclosure_amount': bpi_interest_comp + morat_interest_comp + interest_comp + principal_comp }) emi_date = emi_date + relativedelta(months=1) if scenario == 3: # # disbursal 1th - 4th amort_array = [] emi_date = first_emi_date pos = loan_principal emi = emi_amount emi_dates = [] morat_interest_comp = 0 bpi_interest_comp = 0 for period in range(1,extended_tenure+1): emi_dates.append(emi_date) if emi_date not in morat_start_date_array: morat_interest_comp = 0 if period == 1: emi = emi_amount bpi_interest_comp = loan_principal * pre_emi_days * annualised_irr/360 interest_comp = (pos * 30 * annualised_interest/360) principal_comp = emi - interest_comp pos = pos - principal_comp else: emi = emi_amount bpi_interest_comp = 0 interest_comp = pos * 30 * annualised_interest/360 principal_comp = emi - interest_comp pos = pos - principal_comp else: if period == 1: bpi_interest_comp = loan_principal * pre_emi_days * annualised_irr/360 morat_interest_comp = pos * 30 * annualised_irr/360 interest_comp = 0 principal_comp = 0 pos = pos - principal_comp emi = interest_comp + principal_comp else: bpi_interest_comp = 0 morat_interest_comp = pos * 30 * annualised_irr/360 interest_comp = 0 principal_comp = 0 pos = pos - principal_comp emi = interest_comp + principal_comp amort_array.append({ 'installment_number':period, 'emi_date': emi_date, 'emi_amount': emi, 'bpi_interest': bpi_interest_comp, 'morat_interest': morat_interest_comp, 'interest_comp': interest_comp, 'principal_comp': principal_comp, 'principal_outstanding': pos, 'foreclosure_amount': bpi_interest_comp + morat_interest_comp + interest_comp + principal_comp }) emi_date = emi_date + relativedelta(months=1) df_amort = pd.DataFrame(amort_array) # Last EMI Calculation all_emi_sum = df_amort['emi_amount'].sum() all_emi_sum_excl_last = df_amort['emi_amount'].iloc[:-1].round().sum() last_emi_value = all_emi_sum - all_emi_sum_excl_last df_amort.at[df_amort.index[-1],'emi_amount'] = last_emi_value # recalculate principal comp to match emi amount = principal_comp + interest_comp df_amort['principal_comp'] = df_amort['emi_amount'] - df_amort['interest_comp'] # Round off values df_amort['bpi_interest'] = df_amort['bpi_interest'].round() df_amort['emi_amount'] = df_amort['emi_amount'].round() df_amort['morat_interest'] = df_amort['morat_interest'].round() df_amort['total_payable'] = df_amort[['bpi_interest', 'morat_interest', 'interest_comp', 'principal_comp']].sum(axis=1).round() df_amort['due_date'] = df_amort['emi_date'].apply(lambda x: x + relativedelta(days=1) if x.weekday() == 6 else x) # if emi_date on sunday, add 1 day df_amort['installment_number'] = (df_amort['interest_comp'] != 0).cumsum() df_amort['foreclosure_amount'] = df_amort['principal_outstanding'] + df_amort['interest_comp'].shift(-1).fillna(0) df_amort.at[len(df_amort)-1, 'foreclosure_amount'] = 0 df_amort = df_amort[['installment_number','emi_date','due_date','bpi_interest','morat_interest','interest_comp','principal_comp','emi_amount','total_payable','principal_outstanding','foreclosure_amount']] #apr = (npf.rate(remaining_emi,emi_amount,-(loan_principal-processing_fee-subvention-insurance_amount),0)*12) * 100 result = { "repayable": df_amort['total_payable'].sum(), "principal_amount": df_amort['principal_comp'].sum(), "subvention": 0, "total_interest": df_amort['interest_comp'].sum(), "total_subvention": 0, "interest_rate": 0, "annualized_interest_rate": annualised_interest, "rps_json": df_amort.to_dict(orient='records') } logger.send_log_event(f"INFO: Response generated successfully.") return result