Overview

Migrating existing lending products, accounts, and customers from another system over to Canopy is less scary than you may think.

We've simplified the migration of data from your legacy system into Canopy by taking a hands on approach to map basic attributes of your historical data to the various API endpoints and allow the Canopy engine to recreate the history and objects (AM schedules, statements, interest charges, etc.) In all cases we input data into our system with the effective dates at which they occurred.

Data Source

Products

By migration time the Canopy Solutions team will have worked with you to configure the product set. Our data model allows for flexibility on several attributes of the product during account creation which can reduce the number of combinations required. For large product sets, Canopy will import these programatically.

Customers and Accounts

This is the loan data that contains names, addresses, and attributes about the loan or credit line. Canopy separates these into two objects and has a many-to-many relationship between them so we can satisfy several product types. The resulting customer-account object also gives you the ability to pass along your internal IDs and other key value pairs (custom fields) to keep congruity with existing systems up and downstream.

Line items

Typically the largest data set during a migration, but also the most straightforward. Examples: Charges, payments, credits, and reversals.

Timing

During the kickoff of your implementation project the Canopy Solutions team will start the discussion for data migration and begin gathering requirements. The typical migration will contain a few test imports into your Canopy UAT environment for review and sign off. The final data migration can be measured in hours and typically corresponds with your integration cutover to minimize downtime.

General Steps

1. Prep Work

Meet to discuss:

Number of records
Set approximate dates
Data delivery format
Legacy system data model

2. Data Delivery

Secured transfer of any sensitive PII data

3. Data Mapping Validation

Canopy team reviews data cleanliness and begins mapping to API
Review meeting to discuss any irregularities or gaps

4. Test Import

Canopy imports data to UAT env

5. UAT Review

Customer to review imported data and validate data

6. Pre-Prod Preparation

Meet to sign off on data; Set date and players
New enrollments are live on Canopy production

7. Production Import

Customer delivers final data set
Canopy pauses event processing and imports data

8. Post-Import

Canopy enables event processing
Canopy and Customer review data