Synthetic Data — Generating Customer Journeys in the Mortgage Lifecycle
Creating artificial customer events in the home loan repayment tenure (Part 1/3)
Part 1: Generating synthetic customer journeys for mortgage payments.
Part 2: Next Best Action — Optimizing Long-term Marketing Communications using Markov Decision Process
Part 3: Next Best Action — Learn an optimal policy for maximizing mortgage collection
Synthetic data is a powerful tool for data scientists and researchers who need to work with data that is not available or accessible in the real world. It is artificially generated data that mimics the characteristics and patterns of real data but does not contain any sensitive or personal information. In most cases, it is used for experimenting before substantial real data is captured.
One of the main advantages of synthetic data is that it can overcome the limitations and challenges of real data, such as privacy, security, cost, availability, and quality. For example, synthetic data can be used to create realistic scenarios and simulations that would be difficult or impossible to obtain with real data, such as rare events, extreme cases, or future projections. It can also be used to augment and enrich real data, such as adding noise…
