Google Cloud results

• Helps enable instant document approval with optical character recognition by Vision API
• Processes 100,000 documents in 20 minutes with automated document processing product Recognic, powered by Vision API and Apigee
• Helps increase the number of applications processed by 30% within the same timeframe

The insurance landscape in India has seen significant changes in recent years with the adoption of new technology. As one of the major insurance providers in the country, ICICI Prudential Life Insurance has aimed to lead in this transformation journey. “There has been a data explosion across India over the past few years, together with a high mobile penetration rate. Today, about 60% of our customers approach us via mobile, for example, which was certainly not the case before,” says Alpesh Karnik, SVP, IT, at ICICI Life Insurance.

Consumer expectations have also evolved, with easier access to information and online services. “Consumers today are more informed on the importance of investing in insurance products, so there’s much more of a pull factor when it comes to sales, but they also want to be able to get these products quickly and easily,” adds Alpesh. To meet the demands of these consumers, ICICI Prudential Life Insurance realized it needed to make its processes even faster and more efficient. Looking to upgrade its infrastructure, the company turned to Google Cloud.

“The biggest benefit of using Recognic and Vision API is that it eliminates the initial waiting time, which can result in drop-offs. Now customers can know immediately whether their documents are sufficient, or if they need to revise or submit any others.”—Alpesh Karnik, SVP, IT, ICICI Prudential Life Insurance

Serving customers better by speeding up processes with Google Cloud

ICICI Prudential Life Insurance’s distributors were already using tablets to input customer data faster and more efficiently, but many of the company’s solutions still required a team at the back end to manually sift through documents for approval. This meant that customers needed to wait five or six hours, or sometimes until the next working day, to know if their documents were approved or needed revision.

That all changed after partnering with Google Cloud Premier Partner Searce to take advantage of its AI/ML powered automated document processing product Recognic, which is built on Google Cloud. Developed using the optical character recognition (OCR) capabilities of Cloud Vision, Recognic reads, understands, and validates documents at scale, enabling organizations that handle massive amounts of paperwork to digitize these documents and then accurately store and index them.

“Google Cloud has cut down the middle- and back-office work, leading to a 30% increase in the number of applications we can process in the same time span without the need for additional resources.”—Alpesh Karnik, SVP, IT, ICICI Prudential Life Insurance

“In the case of ICICI Prudential, the biggest benefit of using Recognic and Vision API is that it eliminates the initial waiting time, which can result in drop-offs. Now customers can know immediately whether their documents are sufficient, or if they need to revise or submit any others,” Alpesh adds.

Alpesh explains that if the details on the application form match the documents provided, the case doesn’t need to go to the underwriter for further checks and can go directly to policy issuance. “Google Cloud has cut down the middle- and back-office work, leading to a 30% increase in the number of applications we can process in the same time span without the need for additional resources.”

ICICI Prudential Life Insurance is also working with Searce to build deep learning models into Recognic so that it can overcome template barriers and input data from a variety of forms. This is particularly helpful for financial and medical documents underwriting because unlike a passport or driving license, financial documents have a higher structural complexity.

As customer data becomes more important in the work of ICICI Prudential Life Insurance, so does protecting it, and the company is taking every measure to safeguard the security and privacy of its customers’ information. “Details of customers’ contactability are automatically removed by Google Cloud after processing is complete. This step in the workflow gives us the confidence that data is not stored at any level of the optical character recognition process,” says Alpesh.

Partnering with the right teams for dedicated support

In achieving the best solution for its business goals, ICICI Prudential Life Insurance recognizes the importance of its decision to work with partners that truly understand the insurance business. “There are many intricacies involved in this business, and it’s clear that both Google Cloud and Searce really took the time to understand our underwriting processes before coming up with a solution,” says Alpesh. He adds that during the implementation process, all findings were well documented and queries were responded to quickly.

“We didn’t want to take any shortcuts deploying Recognic, but at the same time, we didn’t want to draw out the implementation process. The excellent support from both Google Cloud and Searce throughout the journey was reassuring for us as they were always thinking ahead.”

Future-proofing the organization through machine learning and AI

In the coming years, Alpesh foresees the insurance industry to be even more agile than it is today. “I doubt elaborate processes such as underwriting or operations checks will need to be done manually in the future. Everything will be done through machine learning and AI.” In light of this, ICICI Prudential Life Insurance is doing everything it can to prepare, as customers’ expectations are set to keep evolving. “We have to be prepared for the future, and I believe that with Google Cloud, we can do it.”

About ICICI Prudential Life Insurance

ICICI Prudential Life Insurance aims to lead the Indian insurance field through quality products and a hassle-free claim settlement experience. A customer-centric company, it offers long-term savings and protection plans to meet customers’ needs at every stage of life.Industries: Financial Services & InsuranceLocation: India

About Searce

Searce is a niche cloud consulting business with futuristic tech in its DNA, focused on “realizing the Next in the Now” for its clients. Specializing in cloud data engineering, AI/ML, and ad

The Home Depot (THD) is the world’s largest home-improvement chain, growing to more than 2,200 stores and 700,000 products in four decades. Much of that success was driven through the analysis of data. This included developing sales forecasts, replenishing inventory through the supply chain network, and providing timely performance scorecards.

However, to compete in today’s business world, THD has taken this data-driven approach to an entirely new level of success on Google Cloud, providing capabilities not practical on legacy technologies.

The pressures of contemporary growth that drove much of the work are familiar to many businesses. In addition to everything it was doing, THD needed to better integrate the complexities in its related businesses, like tool rental and home services. It needed to better empower teams, including a fast-growing data analysis staff and store associates with mobile computing devices. It wanted to better use online commerce and artificial intelligence to meet customer needs, while maintaining better security.

Even before addressing these new challenges, THD’s existing on-premises data warehouse was under stress as more data was required for analytics and data analysts were utilizing the data with increasingly complex use cases. This drove rapid growth of the data warehouse, but also created constant challenges for the team in managing priorities, performance, and cost.

In order to add capacity to the environment, it was a major planning, architecture, and testing effort. In one case, adding on-premises capacity took six months of planning and a three-day service outage. Within a year, capacity was again scarce, impacting performance and ability to execute all the reporting and analytics workloads required. The capacity refresh cycles were shrinking, and the expecations for data were growing. There had to be a better way.

Still, THD did not take its move to the cloud lightly. A large-scale enterprise data warehouse migration involves tremendous effort among people, process, and technology. After careful consideration, THD chose Google Cloud’s BigQuery for its cloud enterprise data warehouse.

BigQuery, a scalable serverless data warehouse, was better on cost, infrastructure agility, and analytics capability, driving better insights with improved performance. There are no service interruptions when capacity is added, and that capacity can be added within a week (and soon same day). It doesn’t require complex system administration, and its standard SQL support means people can easily ramp up quickly. Valuable BigQuery products like Identity and Access Management meant THD could create many separate Google Cloud projects, while ensuring that different teams weren’t interfering with each other or accessing protected data.

THD also utilizes BigQuery’s flat-rate monthly pricing model that allows teams to budget their capacity based on need and provides billing predictability. The capacity not being used by a given project is available for enterprise use. This ensures no surprises when the monthly bill arrives and provides all analytical users access to significant computing power.

While THD’s legacy data warehouse contained 450 terabytes of data, the BigQuery enterprise data warehouse has over 15 petabytes. That means better decision-making by utilizing new datasets like website clickstream data and by analyzing additional years of data.

As for performance, look at this chart:

With the cloud EDW migration complete, and the legacy on-premises data warehouse retired, analysts now execute more complex and demanding workloads that they would not have been able to complete before, such as utilizing Datalab for orchestrating analytics through Python Notebooks, utilizing BigQuery ML for machine learning directly against the BigQuery data (no movement of large datasets), and AutoML to help determine the best model for predictions.

Additionally, engineers at THD have adapted BigQuery to monitor, analyze, and act on application performance data across all its stores and warehouses in real time, something that was not practical in the on-premises system.

With over 600 projects that THD now has on Google Cloud, the BigQuery story is just one of the many ways that Google Cloud is working with THD to deliver meaningful business results, every day.

Hackensack Meridian Health (HMH) executive Mark Eimer explains how an ambitiously-timed rollout of a comprehensive suite of Google products helped the entire organization—from doctors to IT staff—achieve better security, cultivate a more equitable work environment, and ultimately, improve patient outcomes.

How does a recently merged, 17-hospital healthcare system fast-track a platform migration and hardware rollout securely and in a way that improves work for everyone, regardless of location or role? These are the questions that kept me up at night in early 2020, when the pandemic demanded a “big bang”—something our legacy laptops and operating systems couldn’t handle.

We began our work with Google in 2020 with the adoption of Chrome as our default browser. As we migrated platforms, keeping patient data safe was of the utmost importance to us, along with providing every staff member with the tools they needed to work virtually. Our staff often experienced issues accessing our web-based applications using Internet Explorer or Edge Browser, a problem that went away when we switched to Chrome. Chrome’s versatile compatibility also made it easier for my team to migrate all of our web-based operations, and Chrome’s security and manageability were key components to making this switch a huge win for the organization.

The success of this migration led us to extend our Google partnership to patient care applications—where Google’s expertise in AI and ML helps scale the use of diagnostics tools and improve other aspects of the patient journey.

Achieving security at every step 

Like so many other healthcare organizations, we’ve been concerned about ransomware attacks. This is part of why we moved to Google Workspace and distributed over 3,000 Chrome OS devices in kiosk mode in March of 2020, when many of us went remote due to the pandemic. We were very concerned about team members accessing corporate applications through home devices that were running EOL operating systems (WIN7), as well as a general lack of antivirus and encryption measures.

We were protected by the fact that Google’s software and hardware both had built-in security features that we needed to stave off sophisticated attackers. For example, Chrome OS automatically updates to the latest security update and encrypts data living outside the cloud on the hardware. These features protected us from security-related disruptions, letting us securely move a huge library of file shares and emails across thousands of accounts to Google Chrome OS in just four months.

A year later, in March 2021, we migrated the enterprise over to Google Workspace and saw an immediate reduction in spam by 30% from the inherent built-in AI/ML. This meant staff were less likely to receive (and click through) phishing attempts. My team could connect, create, and collaborate easily and securely—even as more of us were working from home and needed to access sensitive data remotely. 

Leveling the playing field

As an organization, we were surprised by how many team members didn’t have personal computers at home. We quickly decided that if we needed team members to work from home, the health network would have to supply hardware. Chromebooks’ lower price tag compared to PCs—on top of their built-in security controls—allowed us to purchase, deploy, and support that initial distribution of 3,000 Chromebooks to team members in less than three weeks, providing devices to every eligible remote employee instead of just a select few. This was vital to reaching our equitable technology goal as part of our diversity and inclusion initiative: everybody has the same tools to do good work.

When all employees have what they need to do their jobs well, we get better patient outcomes. Before we began this cloud adoption journey, patient and staff experiences were different within the hospitals and outside of them. 

Now it’s the same wherever our staff is, and we’ve seen efficiency and accessibility benefits extend to the patient side. For example, we built a web-based contact center that supports 80 locations that use Workspace and Chrome OS devices. Since customer service, admin, and providers are all on the same system, it has become a one-stop shop for patients.

Furthermore, through the Grow with Google program, we were able to provide another benefit to employees that drove our equity goals. Google trained 50 non-IT staff members—from environmental services, food and nutrition, and other non-tech areas who were interested in making a career change to IT—on the Google products we were using. They may not have thought about switching to a career in IT before the Grow with Google program came to our organization, but through this partnership, they now have that opportunity.

A strategic, long-term partner

With any large-scale rollout, the work doesn’t end once laptops are in employee hands. Google has shown their commitment to long-term collaboration as they continuously optimize their products for the unique needs of healthcare providers and go the extra mile in tailoring tools to our staff’s workflows. 

For example, on the Chrome OS side, the Google team has helped our registration desks and document centers with device integration for hardware like credit card readers and e-signature pads. They’ve also helped us meet security and privacy requirements mandated by state and federal governments around HIPAA, Medicaid, and Medicare reimbursements. Over this next year, we’ll look at a feature roadmap with Google Cloud to deliver further enhancements, iterating on the product itself to meet our needs for the present and the future.

Delivering the future of healthcare

The benefits we’ve seen around security and usability—and the ability to provide all staff with equal access to Google’s technology—are why we’re expanding our partnership with Google to both the administrative and clinical sides of HMH. In addition to further Google rollouts with corporate, next year we’re distributing Chromebooks to all 350 of our ambulatory clinics.

We’re also working with the Google professional services team to create a custom AI model that analyzes 3D mammogram images. This AI model will enable two providers to read mammograms—which adheres to international best practices but is currently rare in the US—without requiring additional time. Conducting double readings of mammograms will yield better health outcomes for our patients, such as a lower patient recall rate and an increased accuracy in detecting breast cancer.

We’re currently building the model using a variety of Google Cloud products, including Cloud Healthcare API. Once complete, this model is expected to be trained, deployed, and maintained in Google’s Vertex AI, allowing our providers to be more productive as they make clinical decisions with AI support. As the model is proven over time, we plan to make the predictive services accessible to other healthcare organizations.

With Google, we’re able to achieve a unified architecture for storing data as well as training and deploying AI models, which enable our staff to work more efficiently and securely from anywhere. While I may not be able to predict the future as accurately as AI can, I foresee our continued partnership with Google as a key part of HMH’s improved provider and patient outcomes.

According to a National Academy of Medicine discussion paper, social determinants of health (SDoH) account for upwards of 80% of a population’s health outcomes. Breaking this down further, 50% come just from socioeconomic and physical environment factors such as education, employment, income, family and social support, community safety, air and water quality, and access to housing and transit. SDoH determine access to and quality of healthcare, and are contributors to a system of disparate access to care.

We believe that to more efficiently provide comprehensive healthcare access to more people, providers will leverage technology to blend in-person and virtual modes of care delivery.

In this article, Amwell and Google Cloud examine five ways telehealth – as part of a provider’s overall care model – can help democratize access to healthcare. (graphic url) 

Remove distance as a barrier to care

8.6 million Americans live more than 30 minutes from their nearest hospital. Long drives can deter patients from seeking care or maintaining routine visits. On the flip side, 92% of Americans nationwide have access to wired broadband in the home or through mobile broadband. Therefore, having a virtual visit just a click away can help remove barriers to care, like distance.

Eliminate the risk of unnecessary exposure

Virtual care means that patients don’t have to worry about potential exposure in transit, while sitting in waiting rooms, or from direct interactions during in-person health visits. This is particularly relevant when it comes to those with chronic diseases or underlying conditions. Telehealth provides patients who may be more susceptible to diseases with access to continuous healthcare without putting them at higher risk for developing more severe symptoms. Virtual visits can occur in the comfort –and safety– of patients’ homes.

Extend access to specialized care

55% of preventable hospitalization or mortality in rural settings is due to lack of access to specialty care. With telehealth, physical proximity to specialized services–typically in urban areas–can be reduced as a limiting factor. Virtual solutions grant everyone access to top specialists, regardless of location.

Save time and money

By augmenting in-person visits with telehealth applications, providers can benefit from greater efficiencies in scheduling, helping to improve their bottom line, and add more flexibility to their workday. Meanwhile, patients can spend less on travel and childcare, limit time taken off work, and save on other costs associated with in-person visits — for a savings of $35 to $690 per visit. In a survey by the COVID-19 Healthcare Coalition, 76% of the 2,000+ patients surveyed across the US responded that transportation was removed as a barrier, 65% reported they no longer had to take time off from work for an appointment, and 67 percent reporting lower costs than an in-person visit.

Combat physician shortage and fatigue

Research shows there will be a shortage of more than 100,000 doctors by 2030. In the midst of a physician shortage, telehealth can help improve care delivery and make it more efficient, ensuring more people can still have their healthcare needs addressed. Additionally, by integrating intelligence such as case triaging along with telehealth into a virtual care model, providers can help reduce clinician burnout.

Amwell and Google Cloud are partnering to deliver transformative telehealth solutions that will make it easier for more patients to receive care and improve patient and clinician experiences across the continuum of care. One example includes embedding real-time captioning and translation services powered by Google Cloud’s AI and NLP technologies within the Amwell platform to increase health access and understanding for more people.

As physicians, we are excited that the future of healthcare will continue to blend cloud technologies like EHR-integrated telehealth platforms, AI, healthcare-trained virtual agents along with in-person care to create an integrated hybrid care model that will improve patient outcomes and unburden providers, all while expanding access to broader patient populations.

To learn more, download the whitepaper “Healthcare’s Virtual Transformation,” written in conjunction with Becker’s Hospital Review.

^{1: “Social Determinants of Health 101 for Health Care: Five Plus Five,” National Academy of Medicine, October 2017}

On Dec 9th and 10th, Wayfair and Google Cloud came together for the inaugural Wayfair-Google Cloud Machine Learning Hackathon. Wayfair firmly believes that hackathons are a great way to fuel a culture of collaboration and experimentation. To fuel Wayfair’s incredible pace of innovation at scale, it’s team of more than 3,000 technologists is constantly experimenting and taking smart risks. It’s test-and-learn culture empowers everyone to think critically and creatively, and take big swings to raise the bar on its world-class experience. 

The Wayfair-Google Cloud Machine Learning Hackathon was all about getting Wayfairians excited about and enabled on new technology. More specifically, this event was a contained test environment for Wayfair innovators to validate AI and ML tools in order to understand how to get better insight from their data. The projects worked on during this hackathon will help Wayfair build new use cases that could impact the business and the end customer in new and productive ways. Google Cloud’s focus for this Hackathon was to enable Wayfairains to harness the power of Machine Learning and AI to enable their own goals around continual improvement and relentless customer focus. 

Prior to the event, Wayfair Data Scientists and Machine Learning Engineers who signed up and submitted ideas for the Hackathon were invited to optional Google Cloud enablement and training sessions. Google Cloud set up classrooms in Qwiklabs on topics including, but not limited to, BigQuery, Vertex AI, and Natural Language AI, so that all Hackathon participants could try out new technologies and tools in a learning environment. Google Cloud subject matter experts were available to field any questions Wayfairians had about the use cases they were hacking on. 

The Hackathon was a hybrid virtual & physical event that hosted 67+ innovators, 49 of which registered for Google Cloud supported ideas. 15 judges from both Google Cloud and Wayfair oversaw the event. The esteemed list of judges included Steven Conine, Wayfair’s Co-Founder and Co-Chairman who has helped pave the way for the development of practical applications of next-generation technologies like augmented reality. The judges measured and evaluated the success of a project based on the following criteria:

• “Wow Factor”: How innovative is the project?
• Impact: How impactful is the project to Wayfair?
• Polish: How complete is the project?
• Presentation Quality: How clear and consistent is the demo? 

The theme of the Hackathon was Machine Learning and AI. Teams were able to collaborate with participants globally, either in-person or virtually, and work together on projects in five categories:  Relentless Customer Focus, Always Improving, Google’s Choice, People’s Choice, and Hackers’ choice. 

At the end of the two days there were winners in all 5 categories. The Google’s Choice award went to “Entity Extraction for Order Matching”. Team “Project Clippy” was named both Hackers’ Choice and the winners of the Relentless Customer Focus category. See below for the results of the 5 categories: 

• Relentless Customer Focus and Hackers’ Choice
  • Winning Team: Project Clippy
  • Hackers: Misha Balyasin, Alex Saad, Leo Smerling, and Gabriele Lanaro
  • This project provided a gamified experience to make the process of leaving a product review even more seamless. 
• Always Improving
  • Winning Team: Customer Causal MetaLeaners
  • Hackers: Colin Gray, Irene Wang, Huy Vo Tran, Wenhao Xu, and Santiago Velez Ferro
  • Team Customer Causal MetaLeaners worked to build lightweight procedure(s) for computationally distributed, multi-target, customized loss functions to make causal meta-learners more applicable to real-world Wayfair problems.
• Google’s Choice Award:
  • Winning Team: Entity Extraction for Order Matching
  • Hackers: Roger Bock, Bradley West, Sina Moeini, and Jonathan de Melker Worms
  • This team built out a solution to use text models to extract and identify the products that customers purchased from user reviews.
• People’s Choice:
  • Winning Team: KNN and ANN on Vertex AI
  • Hackers: Santosh Jhingade, Ashrith Marpaka, Nikhil Bhaip, Adam Schulze, and Brandon Sanders
  • This team used Vertex AI to expand the impact they can have on suppliers and customers by providing accurate and real-time information of products that match either description or image.

Wayfair leaders reflected on the two days and shared their input. Matt Ferrari, Head of Ad Tech, Customer Intelligence, and Machine Learning; Engineering and Product at Wayfair said, “Wayfair has a lot of vendors, but very few strategic partners, and Google is that. Our Partner.” “Thank you all for the participation! I’m grateful to Google, and the many others for helping lead a successful event.” 

Wayfair partners with Google Cloud to optimize performance and resiliency, support scaling data-driven decisions, and Increase employee productivity. “Our category is ripe for innovation, and our partnership with Google Cloud helps us ensure that great ideas can come from anywhere by empowering our technologists with cutting-edge products and solutions,” said Ferrari. “We’re proud to partner on efforts like hackathons that align with our team’s eagerness to work on complex, rewarding problems that push the envelope and challenge us to always think big.”

At first Google Cloud won Wayfair over with the speed, reliability and performance of their technology. Hackathons like this one exemplify that what is equally as important is Google Cloud’s willingness to work side-by-side with Wayfair at every level to enable a culture of innovation. Learn more about the Wayfair-Google Cloud partnership here.