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T4AIML004_Indecomm Global Services uses Amazon Textract for document processing automation_Final.pdf
1.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Ā© 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Indecomm Global Services uses Amazon Textract for document processing automation Praveen Hosur Narayanagupta T 4 A I M L 0 0 4 Solutions Architect AWS India Dr. Harish B Kamath Senior Vice President ā Engineering Indecomm Global Services Leveraging Textract to automate mortgage document processing
2.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. ā¢ Scope of document processing in financial and insurance verticals ā¢ How Amazon Textract can help add value to financial and insurance verticals ā¢ Key use cases in finance and insurance verticals ā¢ Amazon Textract capabilities and document processing pipeline ā¢ Automation in the mortgage vertical using Amazon Textract in Indecomm Global Services Agenda
3.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Documents are a primary business tool across industries Finance Insurance Real estate Accounting Tax management Business operations Medical Legal Education And many moreā¦
4.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Grow new products and revenue streams Improve operational and financial efficiency Detect and reduce to business risks Amazon Textract driving financial and insurance verticals
5.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Key uses in finance, mortgage and insurance verticals for document processing Finance and Mortgage ā¢ Customer Onboarding and loan origination ā¢ Identity verification & KYC ā¢ Improving loan underwriting process productivity Insurance ā¢ Customer Onboarding : Health and Financial document processing ā¢ Identity verification & KYC ā¢ Low touch claims processing and Faster turn around 5
6.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Text Handwriting Tables Human-in-the-loop (Amazon A2I) Specialized documents Invoices and receipts Vendor Identity documents Forms 6 Loan Application Amazon Textract capabilities
7.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Processed data is ingested in a application for deriving further insights or in transaction processing system for process automation Data Ingestion Ingest data either real-time for single pagers or collect all scanned documents in Amazon S3 Textract extracts all information from the document including handwritten, tables & key-value pairs with field level confidence scores Depending on use case it can be processed straight - through or after manual review Extraction Review and Validation Ready for Business Decisions Document processing using Amazon Textract
8.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Ā© 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Automation in the mortgage vertical using Amazon Textract in Indecomm Global Services
9.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Ā© 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Indecomm Global Services uses Amazon Textract for document processing automation Dr. Harish B Kamath T 4 A I M L 0 0 4 Senior Vice President ā Engineering Indecomm Global Services Leveraging Amazon Textract to automate mortgage document processing
10.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Harish heads the IT engineering division, which provides PaaS and SaaS based solution offering to mortgage clients. Harish has over 28 years of expertise in the field of building products, specific to mortgage domain. He has a strong passion for product development. He held a variety of managerial and senior technical positions. He has designed several complex systems including Loan Origination Systems for the mortgage industry. He held senior positions at Cognizant and CoreLogic before to joining Indecomm. Harish has a master's in business administration and a degree in information technology. Harish is a dedicated researcher who earned his Ph.D. in "Using Social Media as a dataset for Credit Risk Monitoring, with Special Reference to Mortgage Loans" from Mysore University. He has published numerous research papers in reputable national and international publications on the use of social media datasets in the mortgage industry. He holds several certifications like Microsoft Certified System Engineer, PMP, Machine Learning, Statistical Process Control, Statistical Techniques for Data Mining, and Business Analytics Dr. Harish Kamath SVP ā Engineering, Indecomm Global Services
11.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. 200+ Active clients. Indecomm is modernizing mortgage operations. Founded more than 25 years ago, Indecomm blends intelligent automation with deep mortgage banking expertise to deliver groundbreaking mortgage innovations that help businesses optimize operations and achieve competitive advantage. Backed by a 1500-strong global workforce, Indecommās automation-as-a-service approach benefits mortgage organizations, enabling better borrower experiences by streamlining middle and back-office operations. 3.9 M Transactions a year. 2M Automated extractions per year. 800,000+ Annual audits/ reviews. 1M Loans underwritten. 1500+ Mortgage professionals. 1.5M Documents processed. 3
12.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. ā¢ Automates underwriting and loan decisions ā¢ Evaluates income, credit, assets, and collateral ā¢ Provides āclear to closeā recommendation ā¢ Calculates borrower income ā¢ Integrates with LOS and POS systems ā¢ Blends source data and borrower documents ā¢ Provides cash flow analysis ā¢ Audit process through data verification ā¢ Interactive dashboards ā¢ 3rd party integrations ā¢ Audit trail for compliance tracking ā¢ Streamlines workflow from loan-set up through underwriting ā¢ Accelerates turnaround times with automation-enabled services ā¢ Simplifies complex analysis and decisions with DecisionGenius integration Indecomm has a suite of products under the brand name of GeniusWorksĀ® It is a genius blend of people, processes, and automation, focused on: ā¢ Calculating borrowersā qualifying income and cash flow analysis to process the mortgage loan- IncomeGeniusĀ® ā¢ DecisionGeniusĀ® automates the lending decisions for lenders using four pillars of underwriting: income, Credit, Asset, Collateral ā¢ AuditGeniusĀ® offers automated auditing platform for our clients, their partners and external auditors Business case
13.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Reduction in cost-per-loan during set-up, processing, and underwriting Task automation creating exponential productivity improvements V 70% V 35% Fewer lender touches in the mortgage middle-office 50% Whether our clients automate pieces of their operation, or use our end- to-end technology + talent strategy, we deliver proven and pragmatic solutions that address even your most complex challenges. Meaningful and Metrics-backed solutions
14.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Convert images and pdf into textual data, with higher accuracy in less time and at lower cost Sort the massive pile of images/pdfs into suitable mortgage paperwork Automate the classification as the manual method is time- consuming Allow users to see the automated document classification and remove, add, or modify the classification Extract the data items as well as the area of interest (location of the data) Allow user to examine the data and make the necessary adjustments. Export the data into a repository. Reuse the data that has been reviewed and validated for the same document if it has been submitted more than once At the core of each of the GeniusWorksĀ® platform products, the key process is to Process flow
15.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Documents Evidence of Truth LOS data Source of Truth ā¢ Calculates borrower income ā¢ Integrates with LOS and POS systems ā¢ Blends source data and borrower documents ā¢ Provides cash flow analysis Auto Extracted, Classified, Certified data ā¢ Automates underwriting and loan decisions ā¢ Evaluates income, credit, assets, and collateral ā¢ Provides āclear to closeā recommendation Audit process through data verification Interactive dashboards 3rd party integrations Audit trail for compliance tracking Intelligent data extractor Core of all GeniusworksĀ® products
16.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Problem Statement ADES - The System Required Replacement TURNAROUND TIMES (TAT) ā¢ 30 minutes on average each document, with 100 pages per document as a minimum ā¢ 800+ pages of single documents caused the TAT to rise to 20 hours. VIRTUAL MACHINES ā¢ 12 cloud-based VMs, including D2V2 servers ā¢ Upgrades to D2V4 were required anytime the volume rose VOLUME ā¢ Every day, up to 1700 pages from all documents were processed. ā¢ The wait was (sometimes) up to 5.5 hours due to sequential processing. SOFTWARE ā¢ For document classification and data extraction, two third-party software are deployed along with custom in-house software. MONITORING ā¢ Processing the corrupt files caused the system to crash. ā¢ Required round-the-clock monitoring to look out for delays and system halts To meet SLAs, queued orders required a 2X increase in VM size, which raised the price. RETURN ON INVESTMENT ā¢ Massive server footprint on cloud costs fortune ā¢ Scalability is challenge, causing the server upgrades quite often, increasing the cost ā¢ Third party software licenses adds up ā¢ Reduction of RoI, with every new client onboarding
17.
Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Clients S3 drop folder Amazon Textract Sends Images, PDF documents Classification Validation Extract-Enrich Certification Stored in secured storage on AWS cloud ML based Image to text service by AWS Customized ML based classification by Indecomm Interactive interface to allow users to override Custom algorithms to extract and enrich data Interactive interface to override extracted data IDX ā Core component of all GeniusWorksĀ® suite of products Intelligent document extraction platform Architecture overview
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Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. AWS Services ā¢ Amazon Simple Email Service (SES) ā¢ Amazon APIGateway ā¢ AWS Config ā¢ AWS Secrets Manager ā¢ Amazon CloudFormation ā¢ AWS CloudTrail ā¢ Amazon CloudWatch ā¢ Amazon GuardDuty ā¢ Amazon S3 Glacier ā¢ AWS KMS ā¢ AWS Lambda ā¢ Amazon RDS ā¢ Amazon S3 ā¢ AWS Security Hub ā¢ Amazon SNS ā¢ Amazon SQS ā¢ Amazon Textract ā¢ Amazon VPC ā¢ AWS WAF AWS Lambda User Internet Amazon CloudFront AWS WAF Amazon S3 Bucket- Static Website AWS Secrets Manager Amazon RDS Primary Amazon RDS Secondary AWS KMS Amazon SNS Amazon SQS Amazon Textract Private Subnet Private Subnet Private Subnet Private Subnet Public Subnet Amazon VPC Virtual Private Gateway Internet Gateway NACL NACL NAT Gateway VPC Flow Logs AWS CloudFormation Amazon GuardDuty AWS Config Region AWS IAM Amazon CloudWatch Amazon S3 Glacier AWS CloudTrail VPC Endpoint Production Bucket MFA Amazon APIGateway Router Reference architecture AWS Lambda AWS Lambda AWS Lambda AWS Lambda AWS Lambda
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Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Volume ā¢ A scheduled job running every two minutes pumped the documents to the tune of 1.2 M pages up to 10 days, without break ā¢ Observations: We are now certain that the system can easily handle high volume without any breakages or problems. Turn Around Time ā¢ 50 pages at maximum load in 5 minutes including document OCR, classification, data extraction, data enrichment, data packaging, and logging each processing activity Number of fields and forms configured ā¢ 9,200 fields ā¢ 700 forms ā¢ Note: Forms and fields are configured based on the needs of our use cases / client requirements Accuracy ā¢ Doc classification average of 98%, maximum was 100% ā¢ Data extraction average of 92% and max of 99% (Considering all docs in the package) ā¢ Note: Accuracy is always computed on the entire loan package. Not on individual document. Cost ā¢ Average cost of per page is well within the budgeted price, considering an average of 500- 600 fields extraction per package Amazon Textract Intelligent data extractor - Metrics of success
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Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. PRODUCT EXPANSION ā¢ New products to support new use cases NEW USE CASES ā¢ Move to āback-endā origination process in the form of audits FOOTPRINT EXPANSION ā¢ Expand outside of the mortgage industry into tangential industries (such as commercial banking) Product roadmap
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Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. IMPROVE ACCURACY ā¢ Maintain existing accuracy rate while increasing it by 10%. ā¢ Improve data extraction accuracy with multi-modal data extraction, in parallel ā¢ Obtain information from numerous new forms. ā¢ Improve extraction accuracy ā¢ Results from multi-modal data extraction should then be combined for even greater accuracy. DEVELOP ML-BASED DATA EXTRACTION TURN AROUND TIME ā¢ Improve turnaround times by 5% Enable users with no technical expertise to: ā¢ Make a fresh ML model to classify new documents. ā¢ Document uploading, labelling, and training ā¢ Verify classification precision ā¢ Set new models to use cases or clients BUILD USER INTERFACE REPORTING PORTAL ā¢ Capture accuracy ā¢ Accuracy and TAT analytics over time Architecture goals and roadmap
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Ā© 2022, Amazon
Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Ā© 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. Thank you! Dr. Harish Kamath Senior Vice President ā Engineering Indecomm Global Services Praveen Hosur Narayanagupta Solutions Architect AWS India 22 https://www.linkedin.com/in/harish-kamath-ph-d-7420125
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