Automated AI Video Risk Assessment for Loan Applications

Automated Video Risk Assessment for Loan Applications

1. Initial Application Submission

1.1 User Interface for Application

Loan applicants submit their applications through a secure online platform.

1.2 Data Collection

Collect necessary information including personal details, financial history, and video identification.

2. Video Submission

2.1 Video Identification

Applicants are prompted to record a video introduction, verifying their identity and providing a brief overview of their financial situation.

2.2 Video Upload

Videos are securely uploaded to the assessment platform for analysis.

3. AI-Driven Video Analysis

3.1 Facial Recognition

Utilize AI facial recognition tools such as Amazon Rekognition to verify the identity of the applicant against provided identification documents.

3.2 Sentiment Analysis

Implement sentiment analysis using tools like IBM Watson to assess the emotional tone of the applicant’s video, which may indicate confidence or anxiety.

3.3 Behavioral Analysis

Leverage AI-driven behavioral analysis tools such as Realeyes to evaluate body language and facial expressions during the video assessment.

4. Risk Assessment Report Generation

4.1 Data Aggregation

Aggregate data from video analysis, financial history, and application details to create a comprehensive risk profile.

4.2 Automated Reporting

Generate risk assessment reports using AI tools like Tableau for data visualization and insights.

5. Decision Making

5.1 Risk Evaluation

Utilize AI algorithms to evaluate risk levels based on the generated reports and predefined criteria.

5.2 Approval or Denial

Automated systems provide recommendations for approval or denial based on risk assessment outcomes.

6. Communication of Results

6.1 Automated Notifications

Send automated notifications to applicants regarding the status of their loan application via email or SMS.

6.2 Feedback Mechanism

Provide applicants with a feedback mechanism to understand the decision-making process and areas for improvement.

7. Continuous Improvement

7.1 Data Analysis for Process Enhancement

Regularly analyze the outcomes of loan applications and video assessments to refine AI models and improve accuracy.

7.2 User Experience Feedback

Gather user feedback on the application process to enhance the interface and overall experience.