Automated customer support for a leading lending tech platform

About Customer

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Customer is a platform that facilitates loan transactions between borrowers and personal loan providers such as NBFCs/Banks. All loan applications are approved and sanctioned by the NBFCs/Banks registered with the RBI. All details are clearly stated upfront during the Loan application.

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Business Problem

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Facing operational constraints amid business growth, our client's maxed-out customer support team sought an efficient solution to address response times. However, adding more staff proved cost-prohibitive. To address this, they sought to automate their customer support platform. That can streamline customer support, improve efficiency, and facilitate prompt responses in both local languages and English. However, accuracy and cultural nuance were imperative for personalized customer interactions.

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Solution

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• Event-driven Workflow: Utilizing Amazon EventBridge for event-driven architecture, allowing seamless interaction between ticketing system events and downstream processes.

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• Preprocessing with Lambda: Lambda functions preprocess incoming data, enhancing it for further categorization and queuing for efficient handling.

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• Queue-based Processing: Utilization of SQS queues ensures orderly message handling, allowing for scalable and asynchronous processing of messages.

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• GenAI Integration: Amazon Bedrock's foundation model categorizes messages and extracts essential entities, aiding in data understanding and context extraction.

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• API Interaction: Amazon Bedrock agents facilitate interaction with customer API for user information retrieval and validation.

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• Automated Email Draft Generation: Leveraging the foundation model to dynamically generate email drafts based on context in the identified language.

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Business Outcome

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• Reduce mean user ticket resolution time by up to 30% boosting customer satisfaction.
• Our solution supports local languages like(Hindi, Telugu, Tamil, kannada, etc.) support significantly enhanced the customer experience.
• Reduces human errors in drafting responses, ensuring accuracy in the information provided to customers.
• Frees up agents' time, allowing them to focus on more complex customer issues that require nuanced human intervention, leading to higher productivity levels.
• Supports the handling of a larger volume of customer inquiries by automating the drafting process, ensuring seamless scalability as the customer base grows.

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