Guide to XS2A
  • What is XS2A?
  • Customer Cockpit
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    • Integration Variants
      • Javascript-Widget
        • Webview App Integration
      • Mobile SDK (iOS & Android)
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      • EasyOnboarding
    • Integration by Use Case
      • PFM (Personal Finance Management)
      • P2P (Purchase-to-pay)
      • Loan Origination (B2C)
      • Loan Origination (B2B)
      • Insurance
      • PSP (Payment Service Provider)
      • Leasing
      • Age verification check
      • Source of Funds/Wealth
    • Products & Platforms
      • Payment Platform (XS2A.pay)
      • Analytics Platform (XS2A.risk)
      • Open Banking Platform (XS2A.api)
      • OnlineÜberweisen
    • Product Features
      • Testbank 2.0
      • Reconciliation
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    • Additional Guides
      • Errorcodes
      • Categorization
        • The Categorization Taxonomy
        • The Categorization Engine
        • Quality Assurance
      • B2C & B2B Rating Checks
        • B2B Rating
        • B2C Rating
      • Reports
      • PayPlus
      • Reconciliation
        • Automatic Recon OnlineÜberweisen
        • Manual Recon OnlineÜberweisen
        • Recon Payment Platform (XS2A.pay)
      • Webhooks
  • FAQ
    • XS2A
      • Merchant admin
    • OnlineÜberweisen
      • For merchants
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On this page
  • Used platforms
  • Used checks
  • Negative indicators
  • Income
  • Expenditure
  • Additional checks
  • Example configuration

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  1. Integration
  2. Integration by Use Case

Loan Origination (B2C)

Credit Platforms, Bank Credit Application

PreviousP2P (Purchase-to-pay)NextLoan Origination (B2B)

Last updated 2 years ago

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The loan origination process generally includes all the steps from collection all neccessary data during the application, taking a loan decision and to disburse the funds or declining the application.

As there are many different types of loans for B2C business, you are welcome to get in touch with us to discuss your individual needs.

Tink Germany helps you to digitalize your B2C loan origination process as well as to minimize the manual processes, e.g. by pulling account statements automatically, by categorizing the account statements, and by calculation of customizable KPIs.

Used platforms

Used checks

General information about the requested account (account balance, overdraft, etc.). The number of booking dates and bookings and also the average number of bookings per day serve as indicators to see if the account is active and consequently if a general view of the financial and actuarial situation is conveyed.

The cashflow supplies an overview of the financial situation of the account holder on a monthly level.

The holder_identification_check verifies that the transmitted name corresponds to the account_holder. This verification makes sure that the loan applicant is using his own account for the digital account check.

Risk_calculations_check can be configured as needed.

Negative indicators

Payments to collection offices

Payments to collection offices can be a negative indicator of the financial situation. However a minimum limit should be set, as a single payment over 30 EUR six months ago may not be a reason to categorically refuse the loan. The number of different collection offices (distinct_counter_holders), the amount, and the frequency give an insight into how severe the financial situation is.

Returned debit notes

Returned debit notes are also an indication of a negative financial situation. However, the amount and frequency should be considered before denying the loan.

Gambling

Disproportionate expenditures for gambling can be a warning signal and should be looked at closely. Small amounts spent on gambling can be ignored, as playing the lotto is very popular and large parts of the population do this on a regular basis.

Income

Different income KPIs can be calculated adjusted to individual requirements (e.g.: salary payments, child-benefits, etc.). For a predefined set of KPIs, see Income Check below.

Expenditure

Expenditures are often calculated based on lump sums. For certain expense categories, it may make sense to choose the maximum of the lump sum and the actual amount spent.

Rent

Rent payments don’t fluctuate over time, so a median over the last three months can give a good indication.

Insurances

The average of the monthly payments can be used to determine the monthly insurance liabilities. Because insurances are not always paid monthly, the average is the preferred operation.

Loan installments

The current loan installments can be determined by taking the maximum monthly sum of the last two months. This ensures that all current loans are considered.

Alimony

The average alimony obligation over the past three months gives a good indication of the additional financial obligation.

Additional checks

For the relevant income categories (E.1.1, E.1.2, E.2.1, E.3.1 & E.3.2, E.4.1.1, E.4.1.2, E.4.1.3, E.4.1.5 & E.4.3.2, E.4.1.8, E.4.2*) the income check delivers a set of general KPIs per category (sum per month, first payment, last payment, minimum monthly sum, median monthly sum, whether it is a current payment and a forecasted value). Additionally, for salary payments, a set of specific KPIs are calculated based on different employers.

The seizure_check returns true if an indication to a seizure was found in either the account_type (e.g. P-Konto) or the transactions. It is advised to consider the maximum time available.

By means of the fact_sheet_list transactions of a specific category can be listed, for example, all salary payments within the last 90 days. Additionally, the different counter_holder will be listed (in this example: different employers).

The xs2a_rating_b2c_check gives an indication of the financial situation of the account. It is not an indicator for loan default, but considers the information of the digital account check to differentiate between financially stable and unstable accounts.

Example configuration

{
  "language": "de",
  "xs2a_account_status_check": {
    "limit_turnover_days": "365"
  },
  "xs2a_holder_identification_check": {
    "expect_holders": [
      {
        "name": "Mustermann",
        "firstname": "Hartmut"
      }
    ]
  },
  "xs2a_risk_calculations_check": {
    "calculations": [
      {
        "categories": [
          "A.5.4"
        ],
        "functions": [
          "sum",
          "count",
          "distinct_counter_holders"
        ],
        "name": "Inkassozahlungen",
        "days": "180",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "E.3.4.9.1"
        ],
        "functions": [
          "sum",
          "count"
        ],
        "name": "Rücklastschriften mangels Deckung",
        "days": "180",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "K.5.1.4"
        ],
        "functions": [
          "sum",
          "count"
        ],
        "name": "Glücksspiel",
        "days": "90",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "E.1.1"
        ],
        "functions": [
          "median_of_all_month_sums",
          "distinct_counter_holders"
        ],
        "name": "Gehalt",
        "full_months": "3",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "E.4.1.3"
        ],
        "functions": [
          "last"
        ],
        "name": "Kindergeld",
        "days": "45",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "E.4.1.8"
        ],
        "functions": [
          "median_of_all_month_sums"
        ],
        "name": "Elterngeld",
        "full_months": "3",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "E.4.1.2"
        ],
        "functions": [
          "median_of_all_month_sums"
        ],
        "name": "Arbeitsförderung",
        "full_months": "3",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "K.2.1"
        ],
        "functions": [
          "median_of_all_month_sums"
        ],
        "name": "Miete",
        "full_months": "3",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "K.8.1"
        ],
        "functions": [
          "average_of_all_month_sums"
        ],
        "name": "Versicherungen",
        "full_months": "12",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "A.5.1"
        ],
        "functions": [
          "max_of_all_month_sums"
        ],
        "name": "Kreditverpflichtungen",
        "full_months": "2",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
      {
        "categories": [
          "A.3.1"
        ],
        "functions": [
          "average_of_all_month_sums"
        ],
        "name": "Unterhaltszahlungen",
        "full_months": "3",
        "children_categories": "1",
        "match_tags_with_categories": "0"
      },
    ]
  },
  "xs2a_seizure_check": {
    "days": "365"
  },
  "xs2a_income_check": {
    "limit_turnover_days": "365"
  },
  "xs2a_cashflow_overview": [],
  "xs2a_fact_sheet_lists": {
    "limit_turnover_days": "90",
    "fields": [
      {
        "categories": [
          "E.1.1"
        ],
        "name": "Gehaltszahlunge"
      }
    ]
  },
  "xs2a_rating_b2c_check": {
    "days": "180"
  }
}
Analytics Platform (XS2A.risk)