Data migration

We help clients implement data controls and improve the integrity of their data to ensure that regulatory, financial and management requirements are met. We turn data into information, and information into actionable intelligence.

Our services:

Driving data migrations

Lessor contracts generate large volumes of data throughout the contract term – master data, contract, billing, collections and accounting information, income recognition entries, and more. These large volumes magnify the challenges that would otherwise have less impact, such as:

  • Undetected or uncorrected data can precipitate further data errors as systems continue to generate their monthly transactions. This leaves companies to address two things: the root causes of defects and also correcting data errors that will continue to built up until corrected

 

  • Data remediation following systems implementation or portfolio acquisition can place departments under unusual pressure with staff dealing with normal duties as well as coping with a new system or portfolio, and also possibly using workarounds and fixing defects postponed from go-live

 

  • Income recognition calculations: even without changing accounting basis these calculations are often implemented differently by different companies or in different systems. Data conversions then need to discriminate between valid, subtle calculation differences and data errors. Similarly, a full change in income recognition basis for a portfolio will usually have material profit impacts that then need to be evidenced.

 

Migration strategy, approach & planning

Confirm objectives and scope

  • Strategy & approach document
  • Migration strategy
  • Reconciliation strategy
  • Data quality metrics
  • Data remediation processes

High level requirements

  • Functional requirements
  • Non functional requirements

Migration planning and kick off

  • Identify data owners & conversion roles
  • Build migration team
  • Plan migration
  • Project kick-off

Data mapping

  • Identify data sources & targets
  • Data modeling
  • Data & metadata mappingGap analysis

Data cleansing

  • Define data quality criteria
  • Identify data quality tools
  • Assess source systems data
  • Cleanse data

Tests and rehearsals

  • Unit test migrations
  • Conduct data migration dress rehearsals
  • Income recognition prediction models to validate migrated balances
  • System and UAT conducted using migration rehearsal data
  • Test operational readiness

Deploy to production

  • Go live plans and checklist
  • Run book
  • Initial load
  • Delta load
  • Reconcile data
  • Go-live decision
  • Initiate post go-live data reconciliations

Working with Richmond

Asset finance expertise

Serving our clients for over 20 years

Global reach - local execution

Delivering projects in Europe, the Americas and Asia

Practical and pragmatic

Experienced, knowledgeable, safe