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Case Study: How Cloud-Based ML Services Enhanced The Operational Resilience Of This Fintech Company

Case Study: How Cloud-Based ML Services Enhanced The Operational Resilience Of This Fintech Company

Case Study: How Cloud-Based ML Services Enhanced The Operational Resilience Of This Fintech Company
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A Chennai-based fin-tech company, Intellect Design Arena helps its customers to digitise their processes with their banking, insurance and other financial services. With its offering that includes a suite of vertical and integrated products, the company is committed to taking the banking industry into the digital future. With their expertise, Intellect Design Arena helps its banking customers in their digital transformation initiatives across global consumer banking, central banking, global transaction banking, insurance, risk, treasury, and markets.

With annual revenue of more than USD169 million, Intellect Design Arena claims to be a global leader in serving financial technology for the banking and insurance industry. The company serves more than 240 customers from the BFSI industry across more than 40 countries with quality services using new-age technologies like machine learning, artificial intelligence, and predictive analytics. In fact, in recent news, the company has announced its cloud-native platform, based on API-first architecture — iTurmeric for its banking customers to automatise their business.

With several clients in hand, Intellect Design Arena has to continuously analyse a vast amount of data to help them in evaluating risks and making informed business decisions. For this, the company relies on costly and time-consuming analytics. However, it was important for the company to provide rapid results to its customers. 



Traditionally, in order to build the analysis infrastructure, the company had to undergo long four-five months oriented processes of contacting the vendors, getting quotations, entering into contract negotiations. However, soon the company realised that its a race against time and they needed to build the products and make it market-ready in a shorter time.

According to the Vice President, Solution Architecture / Head – Cloud & DevOps, Sarat Dara, Intellect Design Arena, “If we can provide our clients with reliable real-time data, it reduces the risk for them, however, if the company is working on an infrastructure that has been built on traditional data centres, it takes four to five months to be provisioned.”

Alongside, Intellect Design Arena was going through an innovation challenge where the company was struggling to build the entire stack and meet the necessary security requirement for production. Also, it was tricky for the company to add on new features, fix bugs or make improvements on the stack, which was creating hassles in obtaining visibility of the ROI.

The Solution & Benefits

Intellect Design Arena was looking for an innovative solution that can help them analyse a vast amount of data in a short period to evaluate risks for their customers. Alongside, they also wanted a solution that is accurate as well as cost-effective and fully managed. After careful consideration, the company decided to opt for Amazon SageMaker, which is a fully managed service that has been designed for analytics professionals and developers to build, train, and deploy ML models.

According to AWS, its solutions do the heavy work and help developers to build high-quality ML models. Explaining the process, Dara stated, data scientists are able to push an algorithm into SageMaker for training and retaining based on the analysis provided by the solution, which in turn helped the company to save 80-85% of its costs.

The solution further helped the company to standardise its processes, including the tools and their engineering and analytics team across different products for them to understand the guidelines of using the algorithms. SageMaker provided all the components used for machine learning models to get into production at a much faster rate with fewer efforts.

Alongside, the company also deployed Amazon SageMaker Ground Truth for labelling their data into specific groups of data elements. SageMaker Ground Truth is a solution designed by AWS to build highly accurate training datasets for machine learning models. Consequently, it allows developers to label datasets and also provides them with built-in workflows.

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According to Dara, the company needed to move the elements into different data models, which the subsystems can accurately use, so the company required to label “one data element as belonging to a specific model, and another other data element to another model.” And for this, traditionally the company would have required the help of its developers and a testing team. However, with AWS solutions, the process turned out to be way faster and easier to gain the required outputs.

Intellect Design Arena further utilised AWS’s capacity reservation in the cloud with EC2 to move their workloads. Also, it deployed their Spot Instances for determining instances of a particular region, which helped them to reduce 50% of their costs, without impacting the availability of applications and products.

Apart from cost reduction, the company also managed to drastically reduce their build times to one month for new product implementations. With the advanced solution, the company also removed their vendor lock-in, which helped in speeding up their process path. According to Dara, AWS customer-centric support has been a massive advantage for the company; with easy access to AWS technical architects and product engineering teams. The company has multiple channels of engagement with AWS — from operations to solution architect. “Their support was always available,” said Dara.

AWS has also helped Intellect Design Arena to share their products on their Marketplace to gain a competitive advantage in the market by providing 50-60% of its software as a service product on AWS Marketplace in the future. Lastly, the company decided to align itself entirely with AWS because of its easy deployment process and customer-centric attitude, which was crucial for the company. “AWS, with its flexibility, ease of use, and a wide range of features, helped us exponentially build products and services. Also, it provided us with the advantage of security and cost optimisation,” concluded Dara.

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