Scraping data from a XHR with request

Question

I want to scrape the data of this website . But the results I get are different from those posted on the website. For example, when I run the code, for 14000 and a duration of 48 months I get 7.03 for the TAE while the value on the site is 6.44. I think the params is wrongly set. Could someone help me?

I changed the params in several ways without it working. I do not know how to find the right params.

import requests
from bs4 import BeautifulSoup
import re
import json
import pandas as pd

#Let's first collect few auth vars
r = requests.Session()
response = r.get("https://simuladores.bancosantander.es/SantanderES/loansimulatorweb.aspx?por=webpublica&prv=publico&m=100&cta=1&ls=0#/t0")
soup = BeautifulSoup(response.content, 'html')
key = soup.find_all('script',text=re.compile('Afi.AfiAuth.Init'))
pattern = r"Afi.AfiAuth.Init\((.*?)\)"

WSSignature = re.findall(pattern,key[0].text)[0].split(',')[-1].replace('\'','')
WSDateTime = re.findall(pattern,key[0].text)[0].split(',')[1].replace('\'','')

headers = {
    'Origin': 'https://simuladores.bancosantander.es',
    'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36',
    'Content-Type': 'application/json;charset=UTF-8',
    'Accept': 'application/json, text/plain, */*',
    'WSSignature': WSSignature,
    'Referer': 'https://simuladores.bancosantander.es/SantanderES/loansimulatorweb.aspx?por=webpublica&prv=publico&m=100&cta=1&ls=0',
    'WSDateTime': WSDateTime,
    'WSClientCode': 'SantanderES',
}

#Those are the standard params of a request
params = {'wsInputs': {'finality': 'prestamo coche',
  'productCode': 'p100',
  'capitalOrInstallment': 5000,
  'monthsTerm': 96,
  'mothsInitialTerm': 12,
  'openingCommission': 1.5,
  'minOpeningCommission': 60,
  'financeOpeningCommission': True,
  'interestRate': 5.5,
  'interestRateReferenceIndex': 0,
  'interestRateSecondaryReferenceIndex': 0,
  'interestRateSecondaryWithoutVinculation': 6.5,
  'interestRateSecondaryWithAllVinculation': 0,
  'interestRateSecondary': 6.5,
  'loanDate': '2019-06-13',
  'birthDate': '2001-06-13',
  'financeLoanProtectionInsurance': True,
  'percentageNotaryCosts': 0.003,
  'loanCalculationMethod': 0,
  'calculationBase': 4,
  'frecuencyAmortization': 12,
  'frecuencyInterestPay': 12,
  'calendarConvention': 0,
  'taeCalculationBaseType': 4,
  'lackMode': 0,
  'amortizationCarencyMonths': 0,
  'typeAmortization': 1,
  'insuranceCostSinglePremium': 0,
  'with123': False,
  'electricVehicle': False}}
#The scraping function
def scrape(amount, duration, params):

    params['wsInputs']['capitalOrInstallment'] = amount
    params['wsInputs']['monthsTerm'] = duration
    response = r.post('https://simuladores.bancosantander.es/WS/WSSantanderTotalLoan.asmx/Calculate', headers=headers, data=json.dumps(params))
    return json.loads(response.content)['d']


Amounts = [13000]
Durations = [ 48, 60, 72, 84, 96]
results = []
for amount in Amounts:
    for duration in Durations:
        result = scrape(amount, duration, params)
        result['Amount'] = amount
        result['Duration'] = duration
        results.append(result)

df = pd.DataFrame(results)

Answer 1

First, as said by @Richard, there is nothing wrong with your code.

The reason why you get 7.03% instead of 6.44% is because the loan simulator that you are using somehow cheats (to appear more competitive). The difference you have lies in the consideration of the Comisión de apertura financiada . This means that if you set the standard parameter 'openingCommission' to 0, you will get 6.45% . What about getting exactly 6.44% ? A suggestion follows.

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Explanation ( using french terminology )

If I compute the TEG and the TAE asociated to the hyperparameter {14k€, 48months, 330.47€/m}, I get 6.26% and 6.44% .

But if I do the same calculation, including the Comisión de apertura financiada of 210€ , I get ~7.03% and 7.23% .

where i above (and below) stands fot the internal rate of return (IRR) , ie the rate that annulates equation (E1):

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Which means that you should consider integrating an IRR-solver within your workflow, using the available pieces of information (mensualities, duration, total amount and even fees) to recompute the TAE.