DocAI Lowers Customer’s Document Processing Cost by 60 Percent. Learn How
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Some of the most important data at your company isn’t living in databases, but in documents, and most business processes begin, involve or end with a document.
Yet most companies are still manually entering data and reliant on guesswork to make sense of it all as the volume and variety of data explodes. Organizations are also leaving heaps of value on the table in the form of new and better customer experiences that can be unlocked with artificial intelligence (AI) applied to documents.
The latest releases of Document (Doc) AI platform, Lending DocAI and Procurement DocAI, built on decades of AI innovation at Google, bring powerful and useful solutions to these challenges. Under the hood are Google’s industry-leading technologies:
- Computer vision (including OCR) and Natural Language Processing (NLP) that creates pre-trained models for high-value, high-volume documents.
- Google Knowledge Graph to validate and enhance the fields in your documents.
- Training and creation of your own custom document models.
- Human interaction with AI to ensure accuracy where needed.
Google Cloud DocAI platform, Lending DocAI and Procurement DocAI are now generally available. Thousands of customers have tried these products in the preview phase—and DocAI has already processed tens of billions of pages of documents across lending, insurance, government and other industries.
“The vast majority of enterprise content still resides in unstructured sources like documents. Google Cloud’s Document AI brings a fresh new perspective to the problem informed by the company’s decades of experience making sense of the largest unstructured corpus in the world—the world wide web.” —Ritu Jyoti, VP of AI Research, IDC
Cut document processing costs by up to 60%
Lending DocAI helps banks, mortgage brokers and other lending institutions fast track the loan application process from weeks to days, dramatically reducing the cost of issuing a loan. And Procurement DocAI enables companies to automate procurement data capture at scale, lowering processing costs by up to 60%.
These solutions are built on DocAI platform, a unified console for document processing that lets you quickly access all parsers and tools. From the platform, you can automate and validate documents to streamline workflows, reduce guesswork, and keep data accurate and compliant.
Get more value from AI with DocAI’s industry-specific solutions
According to Accenture’s AI: Built to Scale report: “Companies that scale successfully see 3x the return on their AI investments compared to those who have not fully rolled out AI capabilities.”
Core to our strategy at Google Cloud is the creation of industry-specific solutions that help companies get maximum value out of their investments in AI. We announced Lending DocAI, our first solution designed specifically for the financial services industry, at the Mortgage Bankers Association convention last year. It processes borrowers’ income and asset documents using a set of specialized machine learning (ML) models, and automates routine document reviews so that mortgage providers can focus on more important work.
Lending DocAI is now generally available and includes more specialized parsers for critical loan documents including paystubs, bank statements, and more. Our goal is to provide the right tools to help borrowers and lenders have a better experience and close home loans faster. For more, watch this video.
Procurement DocAI is also now generally available. This solution helps companies accelerate document processing for invoices, receipts, and other valuable documents in the procurement cycle.
Automating data capture is helping our customers increase accuracy and also lower their procure-to-pay processing costs. We are continually expanding the types of documents Procurement DocAI can process—the latest is a utility parser for electric, water and other bills. In addition, Procurement DocAI leverages Google Knowledge Graph to validate and enrich parsed information to make the data even more useful. Check out this overview video for more details.
One company that lives and breathes AI-enabled document management is AODocs. It uses Procurement DocAI to simplify invoice processing for enterprise customers and launched a new Gmail add-on, Invoice to Sheet, for SMB customers who just want to track their invoices in Google Sheets.
“Google Cloud’s Procurement DocAI service allows our document management platform to better automate the processing of invoices; AODocs customers who have tested our new account payables workflow estimate that the productivity of their A/P team has more than doubled, thanks to the reduction of manual data input brought by the Procurement DocAI.”—Stéphan Donzé, Founder and CEO, AODocs
The new specialized parsers for Lending and Procurement DocAI can be used alongside our existing AutoML Text & Document Classification and AutoML Document Extraction services. These technologies provide a state-of-the-art toolset for creating new document models and have been widely deployed by customers in financial services and other industries.
Partner to accelerate your AI deployment and results
Having the right partner to ease the complexity of rolling out your AI-strategy in mortgage document processing is critical to transforming your customers’ experience. We’re excited to announce a partnership with Mr. Cooper, a leader in mortgage servicing, to provide customers with more automation and workflow tools throughout their entire mortgage life cycle. As part of this agreement, both companies will collaborate on digitizing Mr. Cooper’s core mortgage platform, creating a more personal customer experience utilizing AI, and driving a broader culture of innovation to imagine and develop services and solutions that will transform the mortgage experience for American homeowners.
“Over the last few years, we have made substantial investments in our servicing technology and core mortgage platform that have revolutionized the customer experience, while providing dramatic efficiencies in operating cost. Our partnership with Google Cloud AI will build on those advances and help make these technologies available for the mortgage industry.” —Jay Bray, Chairman and CEO, Mr. Cooper Group
This builds upon the robust partner ecosystem we’re creating to help customers revolutionize the home loan experience, which includes last year’s partnership announcement with Roostify.
Integrate human review into ML predictions
Next up is the general availability of Human-in-the-Loop AI, a new DocAI feature that will help companies achieve higher document processing accuracy with the assurance of human review. Adding human review can increase accuracy and help businesses interpret predictions using purpose-built tools to enable those reviews.
Processing documents quickly and cost-effectively is important. But it’s often necessary to have a high level of assurance on data accuracy for compliance. CIOs and IT decision-makers need highly accurate ML predictions to fulfill compliance requirements, improve employee experience (e.g. less rework), and raise customer satisfaction (e.g. fewer data errors). Including human participation in ML processes allows AI and humans to work together for the best possible results.
Human-in-the-Loop AI provides the workflow to manage human review tasks and produces a percentage confidence score of how “sure” it is that the AI ingested the document correctly. Document AI extracts data from documents with ML, and when paired with Human-in-the-Loop AI, human reviewers are able to verify the data captured. This system is customizable, providing the flexibility to set different thresholds and assign individual groups of reviewers to various stages of the workflow. With Human-in-the-Loop AI, developers can choose trusted reviewers to assign to the task; these reviewers can be from within their own or partner organizations.
More Document AI resources
To learn more, check out the Document AI webpage and watch a demo of how to process sample forms in AI Platform notebooks to inspect data extraction and confidence scores. For more on how customers and partners like Workday, AODocs, and Mr. Cooper are using Document AI, listen to our fireside chat. And stay tuned for the exciting evolution of these technologies in future releases of DocAI.
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Supercharge Marketing with Ready-Made, Centralized Smart Analytics
Your company has lots of valuable marketing data, but it’s spread across many systems and teams. That’s a problem. In fact, only 13% of organisations feel like they’re making the most out of their available customer data today.
And the reason is that data–marketing and customer data–is spread across many different places.
With Cloud, you can bring this data together in one place so you can better analyze and activate it.
Find out how new GCP tools for marketers and hear directly from brands, including Rituals and Waitrose, who are using them to solve use cases like audience segmentation, purchase prediction, and measuring lifetime value.
You’ll learn how Google Cloud is helping IT and marketing teams accelerate digital transformation within their organizations, to be data-driven, and customer-centric.
You’ll walk away with an understanding of how to adopt technology that transforms the way your company delivers marketing campaigns and customer experiences.
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Easy Access to Stream Analytics with Google Cloud
By 2025, more than a quarter of the data created in the global datasphere will be real-time in nature.
“This is important because in the real-time world, “the window of opportunity diminishes and goes away really fast. You want to be able to respond to your customer needs, their asks, and be able to do prediction or maybe detect some problem and really respond to it really fast,” says Evren Eryurek, Director of Product Management for Stream Analytics at Google Cloud.
Today, streaming analysis of application and user events only continue to become more central to how every business operates. With this development comes an accompanying rise in customer expectations for businesses to be aware, prepared, and delivering real-time solutions. Is your business ready?
In this session, Eryurek will showcase Google Cloud’s latest developments to enable easy access to creation and management of real-time data driven experiences.
Learn the latest about the products powering Google’s streaming capabilities and hear directly from the team bringing them to life.
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Public cloud, big data, and AI technologies offer competitive advantages and cost savings for capital markets firms ready to make the transition. This paper discusses the three phases capital markets firms go through in transitioning to public cloud, and the workloads, benefits, and cultural changes that characterize the three phases:
Infrastructure Optimizers: The first step on the public cloud journey, where firms focus on migrating specific workloads to save costs.
Cautious Strategists: Firms build on the success of their first public cloud migrations, and begin to change the way they develop technology to increase cost savings and start taking advantage of capabilities only available on public cloud.
Transformative Innovators: Firms shift to a fully public cloud-enabled mentality, and fully leverage the flexibility and agility of the public cloud to build industry-changing solutions and attract top IT talent.
Additionally, we reveal the five things that capital markets innovators who have advanced to the transformation phase do well in their adoption of cloud, big data, and AI technologies across the front, middle, and back office functions.
How Notified Managed to Boost AI-driven, Dynamic Influencer Discovery and Classify its Content Using NLP
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Notified is a leading communications cloud for events, public relations, and investor relations to drive meaningful insights and outcomes. They provide communications solutions to effectively reach and engage customers, investors, employees, and the media.
One of Notified’s Public Relations solutions is the ‘Media Contact Database’ that allows customers to discover media and influencers in a unique media database powered by AI and human-curated research.
The goal of the initiative is to expand the scope of the AI driven, dynamically discovered influencers, and analyze online news articles using AI/ML technologies to extract entities and classify content. The prior process to extract insights from news articles provided only 30-40% of the desired results, and there were accuracy and stability issues that resulted in a lot of manual intervention.
Journalist Beat
A key outcome of the AI driven process is to identify the ‘Journalist Beat’. A Journalist Beat essentially summarizes the individual’s area of focus such as a sports writer, financial journalist etc.
Three options were evaluated for the AI/ML process to generate the Journalist Beats :
Option 1: Topic ML
Unsupervised ML approach to determine the commonly used terms.
- Pro: Common approach to grouping documents and determine similar text
- Con: Unbounded list of text
Option 2: ML Classification
Build classification models (supervised) to map reference articles to ‘Beats’
- Pro: Aligns to ‘Research Analytics’ existing processes
- Con: Time to build and maintain ML models for hundreds of beats.
Option 3: GCP Context Classification
Leverage GCP’s Natural Language API for initial classification and as input to Notified single model
- Pro: Aligns to ‘Research Analytics’ without building ML models.
Ultimately the GCP Natural Language API solution was chosen because of the speed of execution and a high level of accuracy with the pretrained models. The Notified team was able to launch the product feature within a few weeks, without ever needing to do extensive data collection and train the models.
Here is the high level process that was implemented for Journalist Beats.
Since Notified supports curated media contacts globally, news articles were instantly translated to English using GCP Translation API. GCP Natural Language API’s solution to classify text was used to analyze the translated text and generate the list of content categories.
Solution Architecture
Here is a sample solution architecture for the ‘Discovered Journalist’ process.
Three core principles guided the above architecture – Serverless & Fully Managed, Scalability & Elasticity for flexibility and to optimize costs, API led real-time processing.
In addition to the GCP Natural Language API and Translation API below are a few serverless GCP products that were part of the automated solution:
- BigQuery is Google Cloud’s fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real time.
- Cloud Run is a fully managed serverless platform that can be used to develop and deploy highly scalable containerized applications.
- Cloud Tasks is a fully managed service that allows you to manage the execution, dispatch, and delivery of a large number of distributed tasks.
The powerful pre-trained models of the Natural Language API provide a comprehensive set of features to apply natural language understanding to applications such as sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis.
Notified looks ahead to super-scaling
In an effort to even further improve its best in class ‘Media Contact Database’, Notified looks to super scale the above AI driven Influencer Discovery process to the order of 100+ million news articles per month. It plans to expand the scope of entities extracted from the news articles and provide a news exploration service for its customers by performing intelligent entity-based searches.To watch your markets evolve, see how competitors add AI insights. To actually stay in the market, make AI the main driver of your product road maps. GCP Natural Language API accelerated our ability to adopt AI at scale.
Thomas Squeo, CTO, Notified
Acknowledgments
We’d like to thank our collaborators at Google and Notified for making this blog post possible. Thanks to Arpit Agrawal at MediaAgility for contributing to this blog post.
To learn more about how Google Cloud Natural Language AI can help your enterprise, try out an interactive demo and take the next step, visit the product overview page here.
Home Depot’s Interconnected Retail Experience by Virtue of Google Cloud Migration for SAP Applications
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With nearly 2,300 stores, The Home Depot is the world’s largest home-improvement chain — a brand that professional contractors and DIYers alike have come to depend on. The home improvement industry continues to experience unprecedented demand and dramatic increases in online ordering accompanied by expanding consumer expectations for things like curbside pickup and same day delivery. The Home Depot’s decision to migrate to cloud-based infrastructure, including the migration of the company’s SAP applications on Google Cloud which began in 2017, has set it up for success in an increasingly digital world, and helped the company adapt to changing market conditions quickly.
Interconnected retail at scale
Building on a strong customer-first philosophy, The Home Depot aims to create what it calls interconnected retail—allowing customers to shop however, whenever, and wherever they want. “So many companies are focused on omni-channel retail,” explains Sam Moses, Vice President of Corporate Systems. “At The Home Depot, we wanted to take it to the next level. Interconnected retail puts the customer at the center of everything and enables them to shop in store, online, or both. Customers can begin a transaction online and continue in-store, or vice-versa.”
To support this strategy, the company’s SAP environment needed to be more agile. Running everything on-premises, from central finance to POS systems, meant that The Home Depot’s IT teams experienced redundancy and repetitive, manual processes. Their data warehouse needed an upgrade to process and analyze growing and increasingly diverse data sets. The Home Depot chose to migrate its SAP environment to Google Cloud to support both the velocity and scale needed for the business as well as critical analytics capabilities needed for its bold digital initiatives. “We chose Google Cloud to support our SAP implementation. Our decision had a lot to do with the relationship between Google Cloud and SAP and also for the applications and services that are offered by Google Cloud, like BigQuery, which are helping to enable data and analytics within our organization,” Moses explains.
After migrating its SAP applications—including S/4HANA, its customer activity repository (CAR), general ledger, e-commerce system, enterprise data warehouse and more to Google Cloud, the company now has the speed, scale and flexibility to tackle enormous spikes in the business, all while staying fully available for their customers. Additionally, The Home Depot was able to transform its financial systems and make them more agile to deliver critical information across multiple business functions in real time.
Maximizing data insights to support customer experiences
By migrating to Google Cloud, The Home Depot is leveraging Google Cloud analytics to build the industry’s most efficient supply chain including more robust demand forecasting, supplier lead times, estimated delivery times and more, all while maintaining better security than before. “We experienced unprecedented change in our customers’ behavior and their buying patterns, which puts a lot of pressure on our supply chain,” explains Moses. “So having the ability to leverage data and analytics gives us insights to know exactly what it is that our customers need.”
The company’s analysts now use BigQuery ML for machine learning directly against the company’s BigQuery data and use AutoML to determine the best model for predictions. The Home Depot’s engineers have also adapted BigQuery to monitor, analyze, and act on application performance data across all its stores and warehouses in real time—capabilities that were not as seamless in the on-premises environment.
With hundreds of projects on Google Cloud, The Home Depot’s cloud journey is well on track, but the company is always looking to the future. “As our customers’ needs have continued to evolve, and as technology has continued to evolve, our relationship with Google will continue to advance — to be able to innovate together, to be able to find new solutions together, to better serve our customers.”
Learn more about how The Home Depot is renovating its retail operation with SAP on Google Cloud.
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