FSI Services Spotlight Blog Series
The FSI Service Spotlight Blog series aims to provide financial services customers a deep dive into the following five key considerations of a particular AWS cloud service. This will allow financial services customers to accelerate realization of business value from consuming the particular AWS service—from developing personalized digital experiences, breaking down data silos, launching new products, driving down margins for existing products, to proactively addressing global risk and compliance requirements. The five key areas for consideration include:
1. Achieving compliance
2. Data protection
3. Isolation of compute environments
4. Automating audits with APIs
5. Operational access and security
Each of these five areas will include specific guidance that can help you streamline service approval for the particular AWS service, which may need to be adapted to your specific use case and environment. We can help you navigate the approval process of the wide range of AWS services available, so you can offload undifferentiated heavy lifting to AWS and focus on your core business objectives.
Questions? Email us.
Financial institutions are increasingly adopting Amazon Machine Learning services to easily build and train machine learning models to effectively detect online payment fraud or build a recommendations platform that provides more value to customers and enables data scientists to move projects from design to production quickly. An Amazon SageMaker notebook instance is a machine learning (ML) EC2 instance running the Jupyter Notebook App. SageMaker manages creating the instance and related resources for you.
A common use case for Amazon Comprehend for financial institutions is to analyze call transcriptions from their call centers to gather insights into their customer calls. This allows a financial institution to uncover common trends, personalize messages and offers, and ensure call center staff have all the available information on a given client to provide the best experience.
Amazon Textract is a fully managed AI service that extracts text, handwriting, and other data from scanned documents that goes beyond simple optical character recognition (OCR) to identify and understand the relationship of the data from forms and tables. In financial services, Financial institutions are leveraging Amazon Textract for a number of workloads: to automate the loan applications processing and claims processing pipeline, resulting in a great customer experience while increasing operational efficiencies.
Amazon Transcribe uses a deep learning process called automatic speech recognition (ASR) to recognize speech in audio files and transcribe them into text. Financial services customers can use Amazon Transcribe to convert speech to text and to create applications that incorporate the content of audio files. Managed call centers such as Contact Lens for Amazon Connect builds on Amazon Transcribe to generate call transcripts and provide accurate call transcriptions, redaction of sensitive data, and automated call metrics to determine the effectiveness of the contact center.
Amazon Lex, an AI service for building conversational interfaces for applications using voice and text, is powered by the same technology as Amazon’s voice assistant Alexa and enables any developer to build conversational bots quickly, with no deep learning expertise necessary. By using an Amazon Lex bot, financial institutions can provide their clients 24/7 availability to get questions answered and tasks performed without needing to speak to an agent.
Amazon Athena is a serverless interactive SQL query service that enables customers to query large volumes of data stored on Amazon Simple Storage Service (Amazon S3) or in other sources without the need to manage the underlying infrastructure or having to set up complex ETL processes. Customers simply register their preexisting S3 datasets as Tables in Athena’s underlying metastore and can immediately begin querying it using standard SQL. With the rise in prevalence of data lake and lakehouse architectures, Athena has become a popular option for FSI customers for interactive SQL analytics.
By migrating to AWS, FINRA — the Financial Industry Regulatory Authority— has created a flexible platform that can adapt to changing market dynamics while providing its analysts with the tools to interactively query multi-petabyte data sets. FINRA is dedicated to investor protection and market integrity. It regulates one critical part of the securities industry – brokerage firms doing business with the public in the United States. To respond to rapidly changing market dynamics, FINRA moved about 90 percent of its data volumes to Amazon Web Services, using AWS to capture, analyze, and store a daily influx of 37 billion records.
Intuit provides financial and tax preparation software for small businesses, accountants, and individuals worldwide. The company began using AWS to host TurboTax AnswerXchange, an application that was only active during tax season, reducing its cost by a factor of six. Today, Intuit runs 33 applications on AWS and plans to move the rest of them to the cloud in the coming years. Using AWS enables Intuit to reach new markets, speed development, and better serve its customers.
By using AWS, JKOS cut the IT costs of launching its business by 90 percent and reduced IT administration costs by 83 percent. JKOS has developed the JKOS app for multiple services including food delivery, taxi bookings and payments. The company supports its apps through the AWS Cloud using Amazon EC2 instances for compute, Amazon RDS for warehousing customer and vendor data, and Amazon S3 for storing images.
Using AWS, Mambu helped one of its customers launch the United Kingdom’s first cloud-based bank, and the company is now on track for tenfold growth, giving it a competitive edge in the fast-growing fintech sector. Mambu is an all-in-one SaaS banking platform for managing credit and deposit products quickly, simply, and affordably. The company uses services including AWS Elastic Beanstalk, Amazon EC2, and Amazon RDS to run its entire infrastructure.
The 600 consultants at msg global solutions deliver expertise to clients worldwide in the insurance industry. Having reached the performance limits of its on-premises infrastructure, the company chose AWS to run SAP for Insurance solutions. Processes are now optimized, services are delivered faster, and the company anticipates it will save $500,000 over the next five years.
National Bank of Canada
National Bank of Canada’s Global Equity Derivatives Group (GED) uses AWS to process and analyze hundreds of terabytes of financial data, conduct data manipulations in one minute instead of days, and scale and optimize its operations. GED provides stock-trading solutions and services to a range of organizations throughout the world. The organization runs its data analysis using the TickVault platform on the AWS Cloud.
NuBank, a Brazilian financial services startup, offers its customers a no-fee, low-interest credit card service. The company is using AWS to host its mobile application and credit card processing platform. By using AWS, NuBank reduced its time to market and is now able to launch customer-facing features with ease.
Pacific Life Insurance
Pacific Life Insurance provides financial services and products to individuals, businesses, and pension plans. The company turned to AWS for its hybrid IT strategy, using the AWS cloud in combination with data centers in California and Nebraska to run actuarial workloads used to set insurance pricing and create new product offerings. Using AWS, Pacific Life can quickly scale its compute capacity with less cost and IT overhead compared to adding new hardware to its own data centers.
Robinhood’s lean staff, including just two devops people, used AWS to create a massively scalable securities trading app with strong built-in security and compliance features that supported hundreds of thousands of users at launch. Robinhood is a startup offering no-fee securities trading. The company uses AWS to operate its online business, deliver and update its mobile trading app, securely store customer information and trading data, and perform business analytics.
Berlin-based Solarisbank is Europe’s leading Banking-as-a-Service (BaaS) platform for business customers across all industries. As a bank with a full German banking license, Solarisbank enables other companies to offer their own financial services. In 2020, the FinTech has gone all-in on AWS. Watch Solarisbank share their migration journey to AWS, how their platform is evolving, and how they operate securely and in-compliance using AWS.
Starling Bank is one of UK’s leading fintech startups, and a successful mobile-first disruptor in the retail banking market. Since launching in 2014, Starling Bank has used AWS to build a convenient, transparent, and mobile-first service without sacrificing security, scalability or cost-effectiveness. Using AWS services including AWS Lambda, Amazon S3, and Amazon RDS, Starling has achieved a fast, scalable, and secure cloud infrastructure which enables seamless, compliant functionality updates.
Since 2011, Stripe has delivered its PCI-compliant payment platform entirely on AWS, relying on the security best practices as well as easy auditability of the AWS platform. Stripe wants to make it easier than ever for developers to process payments on their web and mobile applications. Using AWS provides Stripe with access to a world-class infrastructure that helps it scale seamlessly and increase developer productivity.