Talk #3 - Machine Learning in FinTech
- Lending Space
- Credit underwriting system
- 2% Credit card usage
- 65% of population < 27 yrs
- Digital foot print (mobile)
- Identity (Aadhar)
Use Cases / Scenarios
- Truth Score (Validity of address / person / sources)
- Need Score (Urgency / Time to respond application)
- Saver Score (cash flow real-time analytics)
- Credit Score (Debt to income)
- Credit awareness score
- Continuous risk assessments
- For Safety driving using smartphone sensors
- Spatial / location data
- Road traffic injuries due to distracted driving
- Phone usage - 4x crash risk
- Speedy driving - 45% car crash history
- Driving behavior analysis / driving feedback
- GPS + Inertial Navigational sensors (Accelerometer / Gyroscope / Magnetometer)
- Drive detection
- Event detection
- Collision detection
- Drive summarization and scoring
- Risk modelling
- Events, location of events, duration of events
- Sensors
- Availability - wide variety across devices
- Raw Data - noisy, unevenly spaced time series
- Events - Time scales, combination of sensors
- Model building - Labelled vs unlabelled data, feature engineering
- Algorithms - Stream / batch efficiency
- Cluster data
- Eliminated uninteresting time periods
- Classification / Regression models
- Spectral clustering
- Crop rotation literacy
- Data curation, Query tools on data product
- Visualization and plotting of Agricultural data
- Using Image comparison for Big Cat Counting
- Predicting Big Cat Areas (Territories)
- Observe Nature, Frame Hypothesis, Design Experiments
- Confront with competing hypothesis
- Spacegap program
- Markov chain Monte-Carlo technique
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