{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Mortgage Document Classification \n", "\n", "Mortgage companies often need to process large volumes of diverse document types to extract business-critical data. Today, lenders are faced with the challenge of managing a manual, slow, and expensive process to extract data and insights from documents.\n", "\n", "To help address the issue, Amazon Textract Analyze Lending improves business process efficiency through automation and accuracy, reducing loan processing costs and providing the ability to scale quickly based on changing demand.\n", "\n", "\n", "## Analyze Lending \n", "Analyze Lending is a managed intelligent document processing API that fully automates the classification and extraction of information from loan packages. Customers simply upload their mortgage loan documents to the Analyze Lending API and its pre-trained machine learning models will automatically classify and split by document type, and extract critical fields of information from a mortgage loan packet.\n", "\n", "\n", "In this workshop, we will use Analyze Lending for Document Classification in the intelligent document processing workflow.\n", "\n", "At the beginning of our document processing stage, it may not be obvious as do which documents are present in the mortgage packet. Using Amazon Textract Analyze Lending we will first identify these documents into their respective classes. Once we know which documents are present in the packet, we can run any kind of validation such as look for missing/required documents, extract specific document in a specific way such as ID documents and so on. The figure below explains this process.\n", " \n", "\n", "

\n", " \"cfn\"\n", "

" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup Notebook" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "!python -m pip install -q amazon-textract-response-parser amazon-textract-caller amazon-textract-prettyprinter boto3 --upgrade" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import boto3\n", "from textractcaller import call_textract_lending\n", "from textractprettyprinter.t_pretty_print import convert_lending_from_trp2\n", "from IPython.display import Image, display, HTML, JSON, IFrame\n", "import trp.trp2_lending as tl\n", "import json\n", "import sagemaker\n", "import botocore\n", "import os\n", "import pandas as pd\n", "from sagemaker import get_execution_role" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data preparation\n", "\n", "The sample lending package `lending_package.pdf` . For this workshop, we will be a PDF formatted package, that includes the following documents:\n", "\n", "1. Pay Slip\n", "2. Check\n", "3. ID Document\n", "4. Tax form 1099-DIV\n", "5. Bank Statement\n", "6. Tax form W2\n", "7. Homeowners Insurance Application Form\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "document = 'lending_package.pdf'" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "# variables\n", "data_bucket = sagemaker.Session().default_bucket()\n", "region = boto3.session.Session().region_name\n", "account_id = boto3.client('sts').get_caller_identity().get('Account')\n", "\n", "os.environ[\"BUCKET\"] = data_bucket\n", "os.environ[\"REGION\"] = region\n", "role = sagemaker.get_execution_role()\n", "\n", "print(f\"SageMaker role is: {role}\\nDefault SageMaker Bucket: s3://{data_bucket}\")\n", "\n", "s3=boto3.client('s3')\n", "textract = boto3.client('textract', region_name=region)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Upload sample data to S3 bucket\n", "\n", "The sample package has multiple documents in one file (lending_package.pdf). We will upload this to an S3 bucket for processing. " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "# Upload images to S3 bucket:\n", "bucket = sagemaker.Session().default_bucket()\n", "print(f\"SageMaker Bucket: s3://{data_bucket}\")\n", "\n", "!aws s3 cp docs/lending_package.pdf s3://{data_bucket}/idp/textract/ --only-show-errors\n", "\n", "input_file = 's3://' + bucket + '/idp/textract' + '/' + document\n", "print(f\"Lending Package uploaded to S3: {input_file}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Process the document with Textract Analyze Lending\n", "We will process the lending package using the Textract Caller helper library, and then print out details for how the pages were classified. \n", "\n", "For more information, see [Textract Caller helper library.](https://pypi.org/project/amazon-textract-caller/)\n", "\n", "The format of the response JSON returned is described in the Textract Analyze Lenging documentation here: [Link](https://docs.aws.amazon.com/textract/latest/dg/lending-document-classification-extraction.html)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "textract_json = call_textract_lending(input_document=input_file, boto3_textract_client=textract)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "print('Lending Package processed')\n", "print('Pages: {}'.format(textract_json['DocumentMetadata']['Pages']))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will next print the classifications detected for each page of the package\n", "Type – The normalized value associated with a detection. \n", "For a list of all possible document types, please see [link.](https://docs.aws.amazon.com/textract/latest/dg/samples/textract_AnalyzeLending_keys.zip)\n", "\n", "Download and unzip this file. In it you will find a CSV file, with these columns:\n", " - PageType: This is the document type detected. \n", " - PageNumber: This is the page number within that document type. \n", " - Type: These are the fields to be detected in that document\n", "\n", "\n", "As of December 2022, the list of supported PageTypes are:\n", "\n", "- 1003\n", "- 1005\n", "- 1008\n", "- 1040\n", "- 1065\n", "- 1120\n", "- 1040_SCHEDULE_C\n", "- 1040_SCHEDULE_D\n", "- 1040_SCHEDULE_E\n", "- 1040_SE\n", "- 1099_DIV\n", "- 1099_G\n", "- 1099_INT\n", "- 1099_MISC\n", "- 1099_NEC\n", "- 1099_R\n", "- 1099_SSA\n", "- 1120_S\n", "- BANK_STATEMENT\n", "- CHECKS\n", "- CREDIT_CARD_STATEMENT\n", "- DEMOGRAPHIC_ADDENDUM\n", "- HOA_STATEMENT\n", "- HUD_92900_B\n", "- INVESTMENT_STATEMENT\n", "- MORTGAGE_STATEMENT\n", "- PAYOFF_STATEMENT\n", "- PAYSLIPS\n", "- SSA_89\n", "- UTILITY_BILLS\n", "- VBA_26_0551\n", "- W_2\n", "- W_9" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "results = textract_json['Results']\n", " \n", "for page in results:\n", " print(\"Page Number: {}\".format(page[\"Page\"]), \"Page Classification: {}\".format(page[\"PageClassification\"][\"PageType\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "----\n", "\n", "### How does Textract Analyze Lending classify the document pages?\n", "\n", "Let's take a look at the full JSON response from AnalyzeLending. The `results` variable consists of a list with 7 elements for each of the 7 pages in the `lending_package.pdf` document." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "display(JSON(results, expanded=False))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's look at the JSON for the first page in the document." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true, "tags": [] }, "outputs": [], "source": [ "display(JSON(results[0], expanded=True))" ] }, { "attachments": { "analyze-lending-payslip-header.png": { "image/png": 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nEWeYhWfOeImg/BHfeU26VuER1QJTMo3ppl/Ty67xFWffxa2+dz53xnXiX2F8/S4e/nm1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\n3ubNW/h4yq148TiR40+w+xzQU4p3llq7q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} }, "cell_type": "markdown", "metadata": {}, "source": [ "For page 1 of the document, Textract Analyze Lending classified the page as a `PAYSLIP`. On the payslip, it will look for key payslip fields. For Example:\n", "- Start Date: `___` (as there is none on this payslip)\n", "- End date: 7/18/2008\n", "- Pay Date: 7/25/2008\n", "- Borrower Name: John Stiles\n", "\n", "![analyze-lending-payslip-header.png](attachment:analyze-lending-payslip-header.png)\n", "\n", "\n", "\n", "Note that the last page is an unsupported document type, a Homeowners Insurance Application Form. In module 2, we will process the fields extracted from each of the documents. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's next store the JSON output to a file. A file named \"lending-doc-output.json\" will be created locally on this SageMaker Studio instance, in the `aws-ai-intelligent-document-processing directory/industry/mortgage` directory. \n", "We will use the same JSON file for our extractions in the next module. " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "json.dump(textract_json, open(\"lending-doc-output.json\", \"w\"))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "## Use the Textract Response Library to convert the response to an easier format to work with\n", "\n", "We are calling the [Textract Response Parser Library](https://pypi.org/project/amazon-textract-response-parser/) and then convert the Textract Analyze Lending JSON response to a flattened array for CSV export.\n", "\n", "\n", "The convert_lending_from_trp2() method returns a list of `[{page_classification}_{page_number_within_document_type}, page_number_in_document, key, key_confidence, value, value_confidence, key-bounding-box.top, key-bounding-box.height, key-bb.width, key-bb.left, value-bounding-box.top, value-bb.height, value-bb.width, value-bb.left]`" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "trp2_doc: tl.TFullLendingDocument = tl.TFullLendingDocumentSchema().load(textract_json)\n", "lending_array = convert_lending_from_trp2(trp2_doc)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A file named \"lending-doc-output.csv\" will be created locally on this SageMaker Studio instance, `aws-ai-intelligent-document-processing directory/industry/mortgage` directory. \n", "Open the file and use the CSV display to view each element extracted. \n", "You can also download the file to view locally on your laptop in your favorite spreadsheet application. " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "import csv\n", " \n", "index_fields = ['{page_classification}_{page_number_within_document_type}', 'page_number_in_document', 'key','key_confidence','value','value_confidence','key-bounding-box.top','key-bounding-box.height','key-bb.width','key-bb.left','value-bounding-box.top','value-bb.height','value-bb.width','value-bb.left'] \n", "\n", "with open('analyze-lending-output.csv', 'w') as f:\n", " csv_writer = csv.writer(f)\n", " csv_writer.writerow(index_fields)\n", " csv_writer.writerows(lending_array)\n" ] }, { "attachments": { "analyze-lending-payslip-csv-sample.png": { "image/png": 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fKdOzpH8ffPCBbZ9++qllRXEmbcyYMV7UzuP74hhjrUgIFIKAeG0hKFUvzw8/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\nHmr81PLTqf2+afzU/jOq5R5WYvz8HzhlRGj8InN7AAAAAElFTkSuQmCC\n" } }, "cell_type": "markdown", "metadata": {}, "source": [ "Open the CSV file (use the panel on the left, in the `mortgage` directory) and observe the fields extracted, for example:\n", "\n", "![analyze-lending-payslip-csv-sample.png](attachment:analyze-lending-payslip-csv-sample.png)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "instance_type": "ml.t3.medium", "kernelspec": { "display_name": "Python 3 (Data Science)", "language": "python", "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-2:429704687514:image/datascience-1.0" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.10" } }, "nbformat": 4, "nbformat_minor": 4 }