Azimut Group operates an international network of companies handling investment and asset management, mutual funds, hedge funds, and insurance. Founded in Milan, Italy in 1988, Azimut Group today has branches in fifteen countries, including Brazil, China, and the USA.

“We have subsidiaries and manage funds all over the world,” explains Simone Bertolotti, IT Manager at Azimut Holding S.p.a. “That means that any technology that we put in place has to cover needs from many different countries.”

“When complicated analysis has to be executed, we have to increase our table space in a couple of minutes so that the AI can drill down into the data and deliver the information we need.”

—Simone Bertolotti, IT Manager, Azimut Holding S.p.a.

Azimut manages its funds with investment advisors who use information sourced from Bloomberg, Reuters and others. “They use a huge amount of data,” says Simone. “They work with spreadsheets, algorithms, formulae and they analyse data in minutes.” In finance, every second is crucial, which is why Azimut decided to develop a risk management dashboard that can process information even more quickly, then distribute it worldwide.

“When an advisor manages data, that data is used to make immediate decisions on funds, capital movements or whether to sell stock,” says Simone. “They have to be ready to make recommendations for any amount of data that comes to them. For our dashboard, that means that when additional information arrives or complicated analysis has to be executed, we have to increase our table space in a couple of minutes so that the AI can drill down into the data and deliver the information we need.”

Generating insights at speed

Investors and investment managers make decisions based on the most accurate, up-to-date information possible. For Azimut Group, information sourced through financial data vendors such as Bloomberg and Reuters provided only part of the data that the group required.

“We looked to collect information from a range of different providers,” explains Simone, “then analyse it to develop a predictive algorithm that could work faster than an advisor stationed at the terminal. We set ourselves the challenge to try to manipulate that data to add new insights into our matrix, so that every one of our branches across the world can see risk information about the funds in real-time.”

“We compared Google Cloud Platform’s performance with our previous cloud provider, and saw huge benefits of switching to Google. For me, the key performance issue is scaling. With Google Cloud Platform I know that I can increase and decrease my infrastructure quickly, when I need it.

—Simone Bertolotti, IT Manager, Azimut Holding S.p.a.

The first cloud provider Azimut used to build its system struggled to scale quickly to meet different kinds of data challenges. “If we wanted to add more cores, that was fine,” says Simone. “But the previous cloud provider made it complicated to raise the amount of space in a database infrastructure and scale up to demand. Scaling up for more in-depth analysis would take a day, and our need was immediate.”

That’s why Azimut switched one year ago to Google Cloud Platform to run the 150 VMs on its risk analysis platform. “We compared Google Cloud Platform’s performance with our previous cloud provider, and saw huge benefits of switching to Google. For me, the key performance issue is scaling,” says Simone. “With Google Cloud Platform I know that I can increase and decrease my infrastructure quickly, when I need it. Instead of waiting a day to scale up infrastructure, we can request and add space to our database in a couple of minutes.”

The infrastructure of Azimut’s solution handles around 800TB of data per month, and Google’s global network of servers and high-speed connections ensure that it gets to where it’s most needed by the most direct route. Impressed by the speed, security and availability of Google Cloud Platform, Azimut has moved its intranet on to Google Cloud Platform, too, eliminating the need for staff to login with VPNs.

“Instead of waiting a day to scale up infrastructure, we can request and add space to our database in a couple of minutes.”

—Simone Bertolotti, IT Manager, Azimut Holding S.p.a.

Driving ahead with Noovle

For Azimut, migrating the risk management dashboard is the latest of many Google product collaborations with cloud consultancy Noovle. “Everything started five years ago,” says Simone, “when Noovle assisted us in migrating to Gmail from our on-premise email solution. From G Suite to Google Cloud Platform, we’ve had a great relationship. Noovle provides consultancy services, support for mobility, and external advisors who work on our premises, such as when they trained us how to broadcast our meetings on Google Hangouts. As an independent company, we know we can trust them for transparent advice. All they care about is the best way to get a job done and to help us reach our goals.”

New app, new customers

In a business case comparison, Google Cloud Platform cost Azimut 35% less to run than the previous cloud provider. Now the group is building a major new mobile application on Google App Engine to be released in 2018.

“The new mobile application will allow customers to trade directly, without human advisors, by proposing different investment solutions depending on targets the customers set,” says Simone. “So if a customer aims to make money with investments, they enter their relevant personal information and we carry out the necessary regulatory checks and suggest what they could buy. The entire project will be based on Google Cloud Platform, so customers can control their investments through the app while we manage the fund, using Google Cloud Spanner on the backend.”

The COVID-19 pandemic brought dramatic changes to the financial services industry. Already under pressure from nimble young fintechs to modernize, established banks and insurers were undergoing incremental digital transformation. But in 2020, they hit the gas pedal. Branches closed and remote work became the norm. Almost overnight, employees needed secure remote access to corporate systems, and customers expected to be able to complete even complex transactions whenever they wanted, on whatever device. Even as things return to normal, many of these shifts are likely to be permanent. According to Forrester Research, nearly 90% of global financial services CIOs and SVPs believe that improving their application portfolio is key to improving customer experience and driving revenue.¹ The problem? Replacing legacy systems with cloud-based SaaS enterprise software is a massive, time- and resource-intensive process. 

IDG’s recently completed white paper, Financial Services Spotlight: Elevating agility and security in the cloud, highlights an alternative to the all-or-nothing approach to replatforming: “lifting and shifting” on-premises applications and workloads to the cloud without rewriting them. In this way, you keep your organization’s familiar architecture, but give it the scalability and cutting-edge technology of a modern cloud environment. That’s the promise of Google Cloud VMware Engine brings to the financial services industry.

Here’s a quick overview of the insights that the IDG study uncovers. Download the complete white paper.

Simpler migration, rich rewards

Google Cloud VMware Engine helps financial services companies seamlessly migrate and run 

VMware workloads natively on Google Cloud. Once in the cloud, firms can take advantage of Google Cloud services, access a robust third-party cloud ecosystem, and use the same VMware tools, processes, and policies their teams already know. The IDG study found that migrating to Google Cloud with Google Cloud VMware Engine offers multiple benefits:

1. Create new customer experiences. Migrating to Google Cloud puts modern, cloud-native architectures and technologies — such as containers and microservices — easily within reach. These make it possible for financial institutions to quickly and securely launch new applications and update them on a continuous basis using DevOps pipelines. They also allow firms to craft more personalized customer experiences across channels using Google Cloud’s native AI and data analytics.
2. Deliver new services. After migrating, financial services organizations can connect to multiple third-party service providers via cloud-based APIs to bring new, diverse services to their customers — without having to build from scratch. 
3. Make the best use of IT resources. When your data and applications reside in Google Cloud, you’re no longer constrained by the physical storage and compute limits of on-premises infrastructure. This means your company can match capacity to demand — even during unexpected peaks. You also gain more visibility into your hybrid cloud environment with Google Cloud’s operations suite, which offers intelligent analysis and easier troubleshooting for your platform and applications.
4. Gain fresh insights. The key to understanding what customers need and when they need it resides within your data, and data analytics in the cloud help you uncover those insights. Your company can connect to Google Cloud’s serverless data warehouse, BigQuery, which leverages data to deliver valuable insights for personalized customer experiences, rich compliance reporting, new product development, intelligent fraud detection, and more. 
5. Choose what to move. Data governance regulations and requirements specific to the financial services industry mean that some data must remain on premises. Google Cloud VMware Engine lets you easily manage a hybrid cloud/on-premises environment to keep sensitive data fully under your control.
6. Become more resilient. Google Cloud VMware Engine gives financial services firms a distributed architecture and centralized control for their applications to support vital business continuity functions, such as backup and disaster recovery. This is on top of the performance and availability of Google Cloud’s global infrastructure.
7. Improve security. Using cloud-native application frameworks, administrators can issue patches and software updates centrally and automatically across their organizations. This reduces the risk of errors and security vulnerabilities. Firms also tap into the security features and capabilities of Google Cloud, including always-on encryption and AI-powered threat detection.
8. Redirect IT resources. Migrating virtualized workloads to the cloud can free up talent and budget to develop new products and services — time that was previously spent on maintaining complex on-premises infrastructure. That means less effort spent keeping the lights on, and more resources directed toward creating innovative and differentiating customer experiences.

IDG research concluded that migrating business applications to Google Cloud with Google Cloud VMware Engine can help financial services companies stay ahead of change without incurring further technical debt from their legacy IT systems. Working with cloud-based systems can give your financial services company much of the scale, speed, and agility of a startup while still enjoying the benefits of being an established organization.

Read the complete white paper to learn more about the ways in which Google and VMware work together to accelerate digital transformation for financial services firms.

^{1. Vmware-forrester-financial-services-modern-app-report.pdf, A commissioned study conducted by Forrester Consulting on behalf of VMware, 2020}

The combination of a vital need for IT experts among businesses and a digital skills gap is making lifelong learning increasingly critical. Beyond professional development, learning new skills offers additional rewards from building peer connections to boosting your creativity. That’s why in 2020 Krishna Deepak Nallamilli and I launched KIMO.ai to reimagine how people approach learning, especially in developing markets. Our team is building the artificial intelligence needed to generate individual learning paths through a wide range of quality digital learning content.

Google Cloud and its Startup Program have been instrumental in connecting our team with the tools, people, processes, and best practices to grow our business. 

Existing learning platforms lack engagement

Outside of traditional education settings, massive open online learning courses (MOOCs)—often modeled after university courses—can provide a flexible and affordable way to upskill or reskill. But the vast majority of people who participate in MOOC programs fail to complete courses. Based on our research, the challenge with existing learning platforms is a lack of engagement, primarily caused by limited direction on which skills to learn, whether AI, fintech, blockchain, or other in-demand disciplines.   

We’ve also received feedback that many corporate learning management systems–developed as online training systems to upskill employees–tend to be poorly designed and time-consuming to use. 

Overall, a significant challenge with most existing learning platforms is that they’re generic. For example, suppose you’re interested in learning about AI. In that case, you need AI-related coursework that applies to your industry and the job you want because AI in medicine is vastly different from AI in financial services. Today’s online learning options typically take a one-size-fits-all approach and fail to capture the nuances of what learners really need to get ahead. 

Building a future-proof learning platform 

The commitment to highly personalized, accessible learning inspired KIMO.ai, a platform that we believe is the future of education. Depending on your goals, current skills, location, and other factors, our AI-based platform will identify which coursework (and where to find those classes) to build the skills you need. The more personalized, relevant learning recommendations even take into account people’s preferences for podcasts, MOOCs, books, articles, videos, courses, publications, and more.  

In a mix of cooperation and competition we call “coopetition,” KIMO.ai will regularly recommend courses from other established online learning systems if, based on our automated assessment, it’s the best option for a learner. There’s also the option to access free content only. 

Google cultural alignment fosters trust

Our platform started with one developer exploring NLP models and Google APIs. As we’ve grown our team and launched our beta to 110,000 users in developing markets, we discovered there is a lot of interest in our platform, and we believe we can make a significant impact. In feedback forums, we also learned that we need to focus our efforts on the mobile experience to improve engagement since 99% of the beta testers use mobile devices. 

Beyond our team’s high level of trust in Google Cloud solutions, our team also appreciates the cultural alignment with Google. We value Google’s developer-centric approach and rely on tools like Dataflow for batch data processing and Cloud TPU to reliably run machine learning models with AI services on Google Cloud. We also build all of our deployments on Google Kubernetes Engine (GKE), which makes it easy to manage all our containerized workloads 

On the front end, Google App Engine makes it easy to deploy apps and experiment, and it integrates seamlessly with Firebase for authentication and more. BigQuery is our serverless data warehouse that efficiently scales to support the millions of articles, videos, and other learning resources we need to analyze to provide the targeted coursework recommendations our learners require.

As we grow our business having a network of trusted advisors is also extremely valuable. By working closely with DoIT International, the 2020 Google Cloud Global Reseller Partner of the Year, our team has access to their cloud, Kubernetes, and machine learning expertise. DoIT has already helped us quickly resolve IT issues and create analytics dashboards that give us insights to continually enhance our services. 

Building for a growing industry

The dynamic edtech market is growing rapidly and estimated to become an $11B industry by 2025. We’re proud to be part of the next wave of personalized education that has the potential to empower people in developing markets and beyond to grow their skills with coursework tailored to their exact needs and how they like to learn. This year, we will deliver our platform to at least 400,000 more people. We’re excited to see how they use it and where it takes them. 

If you want to learn more about how Google Cloud can help your startup, visit our Startup Program application page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.

Cloud Retail Search, part of Discovery Solutions For Retail portfolio, helps retailers significantly improve the shopping experience on their digital platform with ‘Google-quality’ search. Cloud Retail Search offers advanced search capabilities such as better understanding user intent and self-learning ranking models that help retailers unlock the full potential of their online experience.

Google Cloud’s Discovery Solutions For Retail are a set of services that can help retailers improve their digital engagement and are offered as part of our industry solutions.

Executive Summary

Retailers are always working on trying to keep up with the ever changing consumer expectations and trying to forecast the next trend that can impact sales and revenue.

The pandemic brought its own (and largely new) set of challenges which further complicated the issue over the last two years. The retailers were forced to adapt to the new consumer (low physical touch) behavior in which the browsing and product research was largely digital (endless aisle) and accelerated other trends such as buy online and pick up in stores (BOPIS), curbside pick up and pick up lockers. According to a McKinsey Global Survey from early last year, the pandemic has accelerated the pace of digital transformation by several years.

The National Retail Federation (NRF) estimates that retail sales are expected to grow between 6% and 8% in 2022 (slower growth rate than in 2021), as consumers spend more on services instead of goods, deal with inflation and higher food & gas prices due to geopolitical disruptions in the world.

And the competition continues to be fierce as ever. Amazon continues its dominance in the U.S. retail world and new PYMNTS data shows that Amazon’s share of US Ecommerce sales hit an all-time high of 56.7% in 2021.

Customers now have more choices than ever on how they want to engage with the retailers, where they want to spend the money and make their purchase. They also have increased expectations from the retailers around providing a high quality product discovery experience, which is forcing the retailers to invest heavily on improving customer engagement on their digital platforms to boost conversion rate and overall customer loyalty.

This is where Retail Search can help by providing an enhanced search experience that uses Google-quality search models to understand the customer intent and takes into account the retailer’s first party data (such as promotions, available inventory and price) for ranking results.

How is Google Cloud Retail Search Different

The Ecommerce platform on-site search use case is not new and retailers have been trying to solve it effectively for the last two decades. Most retailers recognize that search is a critical service on the platform and have spent countless resources to improve and fine tune it over the years. Yet the challenge remains. According to a Baymard Institute study in late as 2019, 61% of sites still required their users to search by the exact product type jargon the site uses.

However, users now expect the same robust and intuitive search features as is offered by Google.com and other popular web platforms, who seem to have the uncanny ability to intelligently interpret and yield relevant results to complex search queries.

Google’s decades of experience and research in search technology benefits Cloud Retail Search solution and that is what differentiates it from the competition.

• Advanced Query Understanding: Retail Search can provide more relevant results for the same query due to better query understanding features and knowing when to broaden or narrow the query results. While most search engines still rely largely on keyword based or matching tokens results, Retail Search has the advantage of being able to leverage Google search algorithms to return highly relevant results for product listings and category pages.
• Semantic Search: Intent recognition is a key requirement for semantic search and identifying what the customers mean when they enter the query is a key strength of Retail Search. This is critical for retailers since this has a direct impact on Clickthrough rate, Conversion rate and the Bounce Rate.
• Personalized Search Results: Another key differentiator for Retail Search is its ability to leverage user interaction data and ranking models to provide hyper personalized search results. Retailers are able to optimize search performance to deliver desired outcomes: better engagement, revenue, or conversions.
• Self-Learning and Self-Managed Solution: Retail Search models get better over time because of the self-learning capabilities built into the solution. In addition, the service is fully managed, which saves precious resources needed to keep it running and managing its set up.
• Strong Security Controls: The service runs on Google Cloud and follows security best practices to keep our customers’ data secure. Google never shares model weights or customer data across customers using the Retail API or other Discovery Solution products. For more details about this data use, see a description of Retail API data use.

High Level Conceptual View

Here is a simplified high-level view of Retail Search API. Retailers can call the API for the given search query and get back the results which can then be displayed on their digital properties.

The returned results contains two types of information:

• Search results: Query search results including product listings and category pages based on advanced query understanding and semantic search.
• Dynamic faceted search attributes: Faceted Search is a feature that allows further refinement of the search by providing ways to apply additional filters while returning results.

Retail Search needs the following datasets as input to train its machine learning models for search:

• Product Catalog: Information about the available products including product categories, product description, in-stock availability, and pricing.
• User Events: This is the clickstream data that contains user interaction information such as clicks and purchases.
• Inventory / Pricing Updates: Incremental updates to in-stock availability and pricing as that information is updated.

(Keeping the product catalog up to date and recording user events successfully is crucial for getting high-quality results. Set up Cloud Monitoring alerts to take prompt action in case any issues arise).

Retailers also have the ability to set up business/config rules to customize their search results and optimize for business revenue goals such as Clickthrough rate, Conversion rate, Average size order etc.

How to get started

Retail Search is generally available now and anyone with a Google cloud account can access it. If you don’t already have an account, you can start with a trial account for free here.

Establish a Success Criteria: It’s important to establish a success criteria for measuring the effectiveness of Retail search. Get a consensus on which factor(s) you want to include in scope for measuring the effectiveness of Retail Search. This could include one or two from the following: Search Conversion Rate, Search Average Order Value, Search Revenue Per Visit and Null Search Rate (No Results Found).

• Initial Set Up: Create a Google Cloud Project and set up the Retail API. When you set up the Retail API for a new project, the Google Cloud Console displays the following three panels to help you configure your Retail API project:
  • Catalog: displays product catalog and a link to import catalog.
  • Event: displays user events and a link to import historical user events.
  • Serving configs: contains details on serving configuration and a link to create a new serving configuration.

• Measuring Performance: Retail dashboards provide metrics to help you determine how incorporating the Retail API is affecting the results. You can view summary metrics for your project on the Analytics tab of the Monitoring & Analytics page in Cloud Console.

• Set up A/B Experiments: To measure the performance of Retail Search with another search solution, you can set up A/B tests using a third-party experiment platform such as Google Optimize.

Summary:

As retailers try to navigate through the post-pandemic world where supply chain failures and digital transformation acceleration are major focus areas, they now also have to keep a close eye on the recent geopolitical challenges resulting in rising inflation and costs.

While we can all agree that in-store shopping will continue to be a major source of revenue, it is also important for retailers to tweak the in-store experience for the digital world. Trends such as buy online and pick up in stores (BOPIS), curbside pick up and pick up lockers are here to stay.

Given all the above, consumer engagement and digital experience is more important now than ever before. The cost of search abandonment is way too high and has both short and longer term impact. Retail Search is a great solution to help reduce churn, improve conversion and retention. It provides Google-quality search models to help understand customer intent and the retailers have the ability to set up business/config rules to optimize search results for business revenue goals such as Clickthrough rate, Conversion rate and Average size order.

Google Cloud today announced that it has been selected by the Israeli government to provide public cloud services to help address the country’s challenges within the public sector, including in healthcare, transportation, and education. 

Following a thorough public tender process, Google Cloud was selected for this four-phase project known as “Project Nimbus.” The agreement will deliver cloud services to all government entities from across the state, including ministries, authorities, and government-owned companies. The agreement is also available for higher education, health maintenance organizations and municipalities. The project will run for an initial period of 7 years, and the Israeli government may extend the engagement for up to 23 years in total. 

As part of the agreement, Google Cloud will work with the public sector on the formulation of best practices for cloud migration, integration and migration to the cloud, and optimisation of cloud services. Google Cloud will also provide training to the country’s technical government employees and senior leaders to enhance digital skills. Google Cloud announced last month that it will open a Google Cloud region in Israel to make it easier for customers to serve their own users faster, more reliably and securely. The region in Israel will be available to serve not only the government and related entities but also private commercial companies, just like any other Google Cloud region. 

The Accountant General of Israel, Mr. Yali Rothenberg, congratulates Google on their winning bid in the first tender of “Project Nimbus”, a multi-year flagship project led by the Israeli Government Procurement Administration, that is intended to provide a comprehensive framework for the provision of cloud services to the Government of Israel.

We are delighted to have been chosen to help digitally transform Israel. This builds on the continued success we are seeing with the public sector globally.

Google Cloud region in Israel

In April, we announced that a new Google Cloud region is coming to Israel to make it easier for customers to serve their own users faster, more reliably and securely. Our global network of Google Cloud regions are the foundation of the cloud infrastructure we’re building to support our customers in the Middle East and around the world. With cloud’s 25 regions (and forthcoming Middle East regions in Qatar and Saudi Arabia) and 76 zones around the world, we deliver high-performance, low-latency services and products for Google Cloud’s enterprise and public sector customers.