Specific automation achievements include:

• API intergration of loan origination system (Encompass) with general ledger system (Workday) to automate loan-level funding and purchase journal entries.

  • Partnered with Finance Tech, Encompass engineering team, as well as external consultants, to provide clear technical requirements outlining the vision for what my team required in the integration and how I thought we should get there.

  • Wrote python code from scratch that read off Encompass databases and mapped the loan transactions, exporting to Excel in the proper journal entry format. This served as reference to the engineering teams about where and how to access data from Encompass.

  • Held my team as well as partner teams accountable to scheduled deadlines by fostering an open and collaborative communication environment, including having difficult yet professional conversations when things got off track during development.

  • Since deployment, the automation has successfully processed over 12,000 journal entries and reduced manual time by over 500 hours per year, saving approximately $30,000 annually.

• Automation of loan-level reconciliation between general ledger and Capital Markets system.

  • Custom python script utilizing sqlalchemy to read databases of general ledger and capital markets, pairing the data at the loan-level.

  • Created a new database for storing interest rate lock and loan fair value information, then wrote python script to schedule CRON job to upload complex loan and interest rate lock fair value.

  • Utilized libraries such as pandas and xlsxwriter to transform SQL data and generate output to Excel. Output contained loan-level reconciliation of funding revenue, sold loan revenue, as well as unrealized fair value revenue.

  • Turned a manual process of approximately 5-8 hours per month to a push of a button