Agivant’s Hyper Intelligent Automation
Some Examples of The Transformative Capabilities of HIA And Its Impact on Businesses Across Industries Are as Follows:
What HIA Can Do in A Real-Life Scenario of Financial Institutions? Some Of the Significant Features Of HIA:
Document Processing Automation:
- Document Classification: AI algorithms analyze incoming loan applications and automatically classify them based on predefined categories (e.g., personal loans, mortgage loans, business loans). This automation reduces the manual effort of sorting and categorizing documents.
- Data Extraction: NLP algorithms extract relevant information from loan application documents, such as personal details, income, employment history, and financial statements. This automated data extraction eliminates the need for manual data entry, reducing errors and improving efficiency.
- Document Validation: Machine learning models are created to verify documents and ensure they comply with all necessary standards and regulations. The system can check for missing information, verify signatures, and cross-reference data with external sources for accuracy.
Intelligent Chatbot Integration
- Application Status Updates: Intelligent chatbots are integrated into the loan application system, allowing customers to inquire about the status of their applications. Chatbots use NLP techniques to understand user queries and provide real-time updates on application progress, ensuring transparency and reducing customer service inquiries.
- Document Submission Assistance: Chatbots guide customers through the document submission process, providing instructions and clarifying any ambiguities. They can verify if the necessary documents have been uploaded, help in case of errors or omissions, and address common queries regarding document requirements.
- Eligibility Assessment: Chatbots can interactively collect additional information from customers to determine their eligibility for specific loan products. Chatbots can assess eligibility criteria by asking relevant questions and analyzing customer responses, such as credit score, income level, and loan-to-value ratios.