3 Week Proof of Concept Azure OpenAI Use cases for BFSI

Taking a customer-centric approach to providing solutions, NOUS has created an extensive set of use cases specific to the BFSI industry. The customers can pick and choose the relevant use cases from those or highlight their specific requirements and we can demonstrate how can AI create value for them. To leverage Azure for this offering, NOUS leverages Azure OpenAI to create tailored AI solutions for the BFSI industry. Below is a snapshot of the top use cases which cut across all the players in the industry.

• Customer service: AI can enable BFSI organizations to provide 24/7 customer service through chatbots, voice assistants, and virtual agents. These AI-powered tools can handle common queries, requests and complaints, as well as provide personalized recommendations and offers. AI can also help BFSI organizations to segment and target customers based on their preferences, behavior and needs.
• Fraud detection and prevention: AI can help BFS organizations to detect and prevent fraud and cyberattacks by analyzing large volumes of data and identifying patterns, anomalies and threats. AI can also help BFSI organizations to comply with regulatory requirements and standards by automating reporting, auditing and verification processes.
• Credit scoring and lending: AI can help BFS organizations to assess the creditworthiness and risk profile of borrowers by using alternative data sources, such as social media, online transactions and behavioral analytics. AI can also help BFS organizations to optimize lending decisions, pricing and terms by using predictive models and simulations.
• Investment and wealth management: AI can help BFS organizations to provide better investment and wealth management services to their clients by using advanced analytics, natural language processing and machine learning. AI can help BFS organizations to generate market insights, forecast trends, identify opportunities and risks, and create personalized portfolios and strategies.

As part of this offering, Nous lets the customer to choose a use case form our Industry wise use case catalogue or a use case specific for a Customer and creates a POC, demonstrating the implementation of Azure OpenAI and how the same can accelerate a Business Process and bring efficiency improvement.

A typical POC program plan will look like following:

1. Identification of AI use case along with the Client
2. Detailed discussion with the Client for the Use case and Problem Statements
3. Architecture for the Solution
4. Define Data Requirements and Readiness
5. Development of the AI Model
6. Train the Model with Data identified in the previous week
7. Test the Model and Fine Tune the same
8. Initial Demo the the Client
9. Final Demo to the Client, incorporating Client feedback from the 1st Demo
10. Document the learning and Recommendations for next steps

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