Achieving a Continuous State of Compliance and Readiness on AWS Unlock GRC Innovation on Public Cloud

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1 Achieving a Continuous State of Succeeding with Compliance and Readiness on AWS Data Science in Unlock GRC Innovation on Public Cloud Financial Services How to Unleash Innovation Without Sacrificing Transparency or Governance

2 Just as sales organizations use a core platform, like a CRM, to create maturity and scalability, and engineering teams use JIRA, enterprises are deploying Domino on AWS for more maturity and discipline around their data science work. Introduction Financial services industries are unique: their businesses have been data-driven for decades and their competitive edge often depends on the quality of their models. Yet, they face increased regulatory mandates and pressure to minimize risk. Today s CIO is challenged to centralize data science infrastructure in a way that will facilitate governance without constraining the freedom and flexibility key to continued innovation. Organizations wanting to stay on the cutting edge are finding greater data oversight and control, and more opportunities for innovation when they move data science from the periphery of their enterprise to the core, via a platform that offers: Structure and rigorous best practices Access to the latest tools and technologies Transparency and auditability Close alignment with the business As the flow of data and pace of technical innovation continue to accelerate, CIOs need a way to build a long-term competitive advantage without additional risk. Financial services firms such as Coatue, DBRS, and Moody s Analytics have found success running Domino Data Lab in Amazon Web Services (AWS). AWS provides world-class cloud infrastructure and security, and Domino Data Lab adds capabilities specific to data science workflows, letting teams develop and deploy models faster to deliver sustained business value at scale. Together, Domino Data Lab and AWS provide a powerful data science platform for accelerating innovation while optimizing efficiencies, scalability, and security , Amazon Web Services, Inc. or its affiliates. All rights reserved

3 BENEFIT/SOLUTION 1 Centralized data science: Moving from the periphery to the business core While quantitative models have been popular for decades in some sectors of finance like consumer credit scoring, the latest innovations are having dramatic impact across the entire industry. Data science has become a core organizational capability within financial services, where it empowers credit research, risk calculations, asset evaluations, loss models and more. It s driving significant investment from executives. But it often manifests as a collection of siloed people and tools, resulting in inefficiencies, a lack of visibility, and all too often, underwhelming output relative to expectations. IT can help companies realize the full potential of their investment in data science by providing the critical infrastructure that helps move data science from the periphery to the business core. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk. Domino Data Lab running on AWS provides a central system of record that keeps track of all data science activity across an organization. It serves as the foundation for data science work, housing the artifacts and work product associated with research workflows and optimizing the provisioning and management of compute resources in the cloud. With Domino, data scientists can seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Just as sales organizations use a core platform, like a CRM, to create maturity and scalability, and engineering teams using JIRA, enterprises are deploying Domino on AWS to create more maturity and discipline around their data science work , Amazon Web Services, Inc. or its affiliates. All rights reserved

4 BENEFIT/SOLUTION 2 Accelerating innovation through self-service cloud provisioning and seamless collaboration A centralized system of record only works if it is the place where people naturally do their work. Fortunately, data science workflows are ideally suited for the cloud, because they benefit from burst compute and specialized resources like GPUs. Elastic compute and access to GPUs aligns with the lumpy workloads and increasingly popular deep learning tools of model development cycles. Giving data scientists self-service cloud access to AWS via the Domino data science platform alleviates DevOps work and enables automatic elastic compute, which they ll love. Domino scales Amazon Elastic Compute Cloud (EC2) resources to allow data scientists to run multiple experiments in parallel. Data scientists can be productive faster; they spend less time trying to configure and manage infrastructure and more time doing data science. More experiments can run faster, allowing data scientists to try a variety of tools and approaches. Further, by centralizing all data science work within a shared platform, it s easy for data scientists to interact with each other and collect feedback on their models from business stakeholders. Feedback loops are shortened, and the overall pace of work is faster , Amazon Web Services, Inc. or its affiliates. All rights reserved

5 BENEFIT/SOLUTION 3 Maintaining security and regulatory compliance with transparency and governance While spurring innovation, Domino on AWS also reduces risk a primary concern for IT management operating in regulated environments. Domino lowers regulatory risk by automatically preserving the lineage of a model, which is key for financial regulators who monitor model risk. Domino s reproducibility engine tracks and versions the data, code, software tools, results and discussion that form the backbone of a business-critical model. These are stored immutably in Simple Storage Service (Amazon S3), so they can be discovered and reproduced, months or even years later. Domino with AWS also lowers operational risk by providing IT with cost controls, resource tracking and reporting capabilities. And because the data science platform makes life easier for data scientists while allowing them to use the tools they re most comfortable with, they ll enthusiastically adopt it, reducing occurrences of shadow IT. Running on AWS, the most trusted public cloud environment, offers flexibility and high availability at scale , Amazon Web Services, Inc. or its affiliates. All rights reserved

6 SUMMARY Learn More» Read the Solution Brief» Watch the Video» Why Domino Data Lab? Domino is a platform that provides a UI for data science organizations to run, build, deploy, and share models using the tools they know and love. Under the hood, Domino directly manages AWS resources (EC2, Amazon S3, etc.), either in your VPC or in our managed SaaS environment. Domino automates elastic compute resources, container orchestration, content revisioning and more, while letting IT monitor and control resource usage. Domino s core functionality with AWS: Compute Environment Management lets users define shared, reusable, revisioned environments using Docker, with the necessary packages and configuration to run data science tasks. Through a simple UI, data scientists can choose any type of EC2 instance, and run code in two ways: One-click access to interactive workspaces (e.g., Jupyter, RStudio, SAS Studio), where they can develop models. Oneclick submission of batch experiments. Users can run as many tasks as they wish, and Domino will elastically scale compute resources behind the scenes. This dramatically accelerates the pace of experimentation allowing data scientists to discover and share novel insights with the business faster. As this happens, Domino automatically tracks the work code, data, results, parameters from these experiments and work sessions, and keeps it all stored centrally to facilitate sharing, discussion, and reuse. Finally, Domino lets data scientists publish or deploy their work, exposing it to the business either as dashboards, scheduled reports, or APIs. This brings data science impact (and AWS utilization) into the critical path of value creation. With Domino on AWS you can work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk accelerating research and gaining seamless governance of modeling processes , Amazon Web Services, Inc. or its affiliates. All rights reserved

7 What is Domino Data Lab? , Amazon Web Services, Inc. or its affiliates. All rights reserved