Flexiti Enhances Customer Insights with AI: A Case Study
Use Cases
- Fraud Detection
About The Customer
Flexiti is one of Canada's fastest-growing companies and the leading provider of point-of-sale financing with buy-now, pay-later solutions. The company has a talented risk and analytics team that is responsible for managing and analyzing vast amounts of data. Flexiti's primary goal is to provide its customers with flexible payment solutions that meet their needs. To do this effectively, the company relies heavily on data insights to understand customer behavior and preferences. Therefore, the ability to quickly and accurately analyze data is crucial for Flexiti's operations and success.
The Challenge
Flexiti, a rapidly growing company in Canada, is recognized as the country's leading provider of point-of-sale financing with buy-now, pay-later solutions. Despite its success, the company faced a significant challenge. It sought to empower its talented risk and analytics team to gain greater visibility into data more quickly. The need for faster and more efficient data insights was crucial to maintain its competitive edge and continue its growth trajectory. The challenge was not only to speed up the data analysis process but also to ensure the accuracy and reliability of the insights derived from the data.
The Solution
To overcome this challenge, Flexiti turned to DataRobot, a renowned AI platform. The primary goal was to achieve faster fraud detection, increased collection rates, fairer decision-making, and insights to personalize the customer journey. DataRobot's AI-driven solution was expected to provide the necessary speed and accuracy in data analysis that Flexiti's risk and analytics team needed. The DataRobot team partnered with Flexiti to maximize results from the solution. This partnership aimed to leverage the power of AI to enhance Flexiti's data analysis capabilities and provide the insights needed to drive business growth and maintain a competitive edge.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Largest Production Deployment of AI and IoT Applications
To increase efficiency, develop new services, and spread a digital culture across the organization, Enel is executing an enterprise-wide digitalization strategy. Central to achieving the Fortune 100 company’s goals is the large-scale deployment of the C3 AI Suite and applications. Enel operates the world’s largest enterprise IoT system with 20 million smart meters across Italy and Spain.
Case Study
KeyBank's Digital Transformation with Confluent's Data in Motion
KeyBank, one of the nation's largest bank-based financial services companies, embarked on a national digital bank initiative following the acquisition of Laurel Road, a digital consumer lending business. The initiative aimed to build a digital bank focused on healthcare professionals looking to refinance student loans and buy homes. A significant challenge was reducing the time to market for new products by democratizing data and decoupling systems across the IT landscape. Like many large enterprises, KeyBank had a variety of vendor applications, custom applications, and other systems that were tightly coupled to one another. New projects often required developing specific point-to-point integrations for exchanging data, which did not address the needs of other downstream systems that could benefit from the same data.
Case Study
Bank BRI: Revolutionizing Financial Inclusion in Asia with Digital Banking
Bank Rakyat Indonesia (Bank BRI), one of the largest banks in Indonesia, was faced with the challenge of increasing financial inclusion among unbanked Indonesians. The bank had an ambitious target of having 84 percent of Indonesians participating in the banking system by 2022. However, the bank's legacy technologies were proving to be a hindrance in achieving this goal. Each of the bank's products had their own public APIs, which were difficult to manage, secure, and monetize. Additionally, the process of onboarding new partners using host-to-host and VPN technology was time-consuming, taking up to six months. The bank also faced the challenge of reaching a largely rural population, with an estimated $8.3 billion in currency being held outside the banking system.
Case Study
Neobank Transformation: Enhancing Compliance and Security
The client, a leading specialist digital challenger bank based in the UK, was faced with the challenge of redesigning and rebuilding their mobile banking application. The goal was to provide a more convenient way for their customers, primarily small businesses, entrepreneurs, and consumers, to interact with their platform. Additionally, they needed to implement Open Banking, a mandatory requirement from the UK financial institution. Prior to this, the client had outsourced the development of its mobile app to other vendors. However, they needed a strong team that would take over the development completely and implement new features to improve the functionality for both the client and its customers.
Case Study
Increasing Efficiency Through Automation and Modernization for Boohoo Group
Boohoo Group, a leading British online fashion retailer, faced significant challenges due to rapid growth and acquisition of other retailers. The company needed to modernize several internal systems used for warehouse management and tax calculation to maintain efficiency. The existing systems were causing data discrepancies and issues in product tracking. Additionally, a lot of data was stored in Excel files and had to be processed manually, which slowed down operations and increased expenses. The company aimed to automate these manual processes and modernize the existing solutions to boost their efficiency.
Case Study
Aerospike Achieves One Million Writes Per Second on Google Compute Engine with Just 50 Nodes
Aerospike, an open-source, flash-optimized, in-memory NoSQL database, was looking to push the boundaries of Google's speed on Google Compute Engine. The challenge was to meet high throughput, consistently low latency, and real-time processing, which are characteristic of future cloud applications. The team at Aerospike was inspired by Ivan Santa Maria Filho, Performance Engineering Lead at Google, who demonstrated 1 Million Writes Per Second with Cassandra on Google Compute Engine. The goal was to benchmark Aerospike's product performance on Google Compute Engine and see if it could scale with consistently low latency, require smaller clusters, and be simpler to operate.
