Case Study

AI-powered API Analytics Platform

A Leading Banking & Financial Services Organization Improves its API Performance and Delivers Better Customer Experience

One of the largest national banks in the US optimized its API performance significantly and improved the overall user experience on its online banking platform
Industry & Region: Banking and Financial Services, USA
Technology Stack: Azure | Python | Power BI | Scikit-learn | Time Series Forecasting | App Insights
Client Overview
Our client is a major national bank with a large online banking platform that allows customers to access their accounts, pay bills, sign-up for banking products, and transfer money among various other banking services through their website and mobile app.
Business Challenge
When the bank first approached us, it had been facing numerous API-related issues on its online banking platform. We did an in-depth analysis of their current processes. Some of the API-related challenges that came to the forefront included –
  • Monitoring and managing the performance of their APIs, which were becoming increasingly complex and interdependent.
  • Scaling APIs to meet the needs of its rapidly expanding customer base.
  • Identifying and troubleshooting issues with the APIs, which were causing delays and errors for customers. There was only a partial understanding of the data flow between the APIs, and this made it tough to track and identify potential bottlenecks.
  • Obtaining real-time insights into API performance, which meant the bank could not respond to its customer queries or feedback promptly.
  • Gathering a complete understanding of customer usage patterns and preferences, which made it difficult to improve the overall user experience and build a robust reputation in the market.
All these API-related gaps impacted service delivery and customer experience, resulting in missed sales/cross-sell/upsell opportunities, and jeopardized portfolio expansion for an overall increase in business revenues and reputation.
The profitability, performance, and reputation of their business – all was at stake and our client needed a long-term solution to optimize the performance of APIs and improve the overall user experience on their banking platform.
Solution Offered
To help the client overcome these API-related issues and meet their core objective of improving user experience, we recommended a fully customized AI-powered API analytics platform. We came up with a proof-of-concept (PoC) of our proposed solution to clearly demonstrate how it was envisioned to help the bank transform customer experiences. As the customer was happy with the PoC, we went on to build the AI-powered API analytics solution. And here’s what it offered:
  • Using advanced analytics and AI algorithms, this platform provided insights into the API performance, API usage, API errors, API security, and API scalability to take informed business decisions.
  • Backed by machine learning (ML) algorithms, the platform intelligently monitored and managed the performance of the APIs in real time. These ML algorithms, which could learn from historical data, could predict potential issues and enabled the bank to troubleshoot in time, and made the process chain and service delivery efficient.
  • The AI platform analyzed customer usage patterns and preferences by using natural language processing (NLP) and other AI techniques for insights into how their customers interacted with the bank’s online banking platform. Using this data, the bank could identify which features were the most widely used by customers and prioritize development/upgrades accordingly.
  • Additionally, the AI-powered API analytics platform helped the bank to detect and prevent malicious API requests and ensure a secure API environment.
Value Delivered
  • Reduced occurrences of delays and errors for customers, improving the overall customer satisfaction level.
  • Increased efficiency in identifying and troubleshooting issues with the APIs, which reduced the need for manual intervention and saved time and resources.
  • Empowered the bank with a deeper understanding of customer usage patterns and preferences to make data-driven decisions about how to improve the overall user experience and drive business growth.
  • Improved data security, which in turn enhanced customer trust and loyalty, and enabled the bank to meet its customer retention goals.
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