Inefficient Customer Support
High volumes of user inquiries led to slow response times, reducing satisfaction levels and limiting scalability of support operations.
The client is a leading fintech company serving over 3 million users. While excelling in digital-first solutions, they faced challenges with scaling customer support, fraud prevention, and delivering personalized services efficiently.
Their business model focuses on enhancing user trust and engagement through intelligent automation and secure, tailored financial experiences. They aim to transform the way users interact with financial platforms by leveraging artificial intelligence to create smarter, safer, and more personalized experiences for both retail and enterprise customers.
The client identified several critical operational and strategic challenges that were limiting their growth and service quality:
High volumes of user inquiries led to slow response times, reducing satisfaction levels and limiting scalability of support operations.
Rising incidents of undetected fraudulent activities threatened platform integrity and eroded user confidence.
Users expected individualized financial products and recommendations to improve engagement and decision-making, but such capabilities were limited.
KYC verification, loan approvals, and other back-end processes were largely manual, causing delays and inefficiencies.
Binary Informatics developed a comprehensive AI-powered platform using an agile development approach, integrating cutting-edge technologies across key areas:
A 24/7 AI-powered chatbot was implemented using Hugging Face Transformers for natural language processing (NLP), integrated with Salesforce API for CRM connectivity. This system handled real-time user inquiries and escalated complex issues to human agents via a priority queue system, significantly improving support responsiveness.
KYC and loan approval workflows were automated using Robotic Process Automation (RPA) with UiPath , integrated with AWS Textract for document verification. This reduced manual errors and accelerated processing times for customer onboarding and loan disbursements.
Real-time collaboration capabilities were introduced via integration with the Microsoft Teams API , supported by MongoDB for storing interaction logs. This improved stakeholder coordination and ensured scalable teamwork.
A robust fraud detection system was built using XGBoost for real-time anomaly detection and risk scoring trained on historical transaction data. Apache Kafka was integrated for streaming transaction data, enabling the system to flag suspicious activities and reduce false positives effectively.
AWS Lambda was used to build an intelligent query routing system that directed inquiries to the appropriate healthcare professionals, ensuring faster and more accurate resolution.
The implementation of the Generative AI-powered communication engine delivered measurable improvements across key performance indicators:
Enhanced service quality led to increased customer retention and brand loyalty
Reduction in average response time
Improvement in fraud detection accuracy
Faster processing times for KYC and loan approvals
Less time spent on repetitive tasks
These results significantly enhanced the client's service quality, patient satisfaction, and overall operational effectiveness.
The following technology stack was used to implement the DevOps solution:
Ready to start your digital transformation? Share your project details, and we’ll help bring your vision to life.
We Schedule a call at your convenience
We do a discovery and consulting
We prepare a proposal
Your Idea is 100% protected by our non disclosure agreement.