Categorisation & Financial Insights

Solution to understand customers’ financial behaviour

Overview

Financial Insights is developed to help lenders, credit bureaus, and banks to make more informed, fairer, and
faster credit decisions by analyzing borrower's spending history, income, loan repayments, and more.

Features

Transactions Categorization & Analysis
The machine learning algorithms developed by MetaMap transforms raw transaction data into applicable insights.

Comprehensive View of Finances
It incorporates data from all bank accounts in order to give you a full picture of the customer's financial profile.

Instant Access
You will receive the insights with every bank account verification results thus, having quick access to the customer's financial information

Automate Decision Process
With insights, you can accelerate the entire decision process as there is no need to do manual calculations

Financial Insights Structure

Financial Insights aggregates and processes bank transactions to generate a report with the following parts:

Summary analysis of all accounts
To demonstrate customer’s financial situation as a whole

Analysis of each separate account
To show customer’s financial habits for a specific account and provide information which can be used to check customer’s identity.

The report is divided into 3 main sections:

Data Fields

Description

Example

Balance

The balance shows how financially stable the customer is. Large fluctuations can denote an irregular source of income or big swings in spending

"balance": {
"averageMonthly": "40.35",
"highest": "76.91",
"lowest": "34.23"
}

Deposits

The income shows an aggregated view of all inflows, which helps to assess the customer’s income stability and paying capacity

"deposits": {
"topAmount": "9.99",
"topDescription": "Recepcion de la cuenta",
"averageMonthly": "14.28",
"totalMonthly": {
"2022-03": "38.67",
"2022-04": "47.00",
"2022-05": "42.85"
}

Withdrawals

The withdrawals analyses all outflows to show the consolidated picture of the customer’s spending habits

"withdrawals": {
"topAmount": "-999.00",
"topDescription": "STARBUCKS UP TOWN",
"averageMonthly": "-1436.88",
"totalMonthly": {
"2022-03": "3204.98",
"2022-04": "4021.35",
"2022-05": "-4310.63"
}

Webhook Response

"accounts": [
    {
      "name": "CUENTA EFECTIVA DIGITAL",
      "type": null,
      "number": "103727432345",
      "balance": {
        "date": null,
        "current": "",
        "available": ""
      },
      "currency": "MXN",
      "insights": {
        "balance": {
          "lowest": null,
          "highest": null,
          "avgMonthly": null
        },
        "deposits": {
          "topAmount": "0.05",
          "avgMonthly": "0.01",
          "totalMonthly": {
            "2021-12": "0",
            "2022-01": "0",
            "2022-02": "0.05",
            "2022-03": "0",
            "2022-04": "0",
            "2022-05": "0"
          },
          "topDescription": "PAGO DE INTERESES"
        },
        "withdrawals": {
          "topAmount": "-1000.00",
          "topDescription": "RETIRO EFECTIVO CAJERO T137 BANCOPPEL"
          "avgMonthly": "-593.92",
          "totalMonthly": {
            "2021-12": "0",
            "2022-01": "0",
            "2022-02": "-3563.50",
            "2022-03": "0",
            "2022-04": "0",
            "2022-05": "0"
          },
          
        }
      },

How it works?

Step 1:
Customer gives consent for connection to bank account or upload their bank statement via Bank Account Merit.

Step 2:
MetaMap retrieves and analyses the bank transactions data and generates insights based on sophisticated algorithms

Step 3:
Merchant receives the detailed insights via the web hook in real-time and takes the decision


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