Imagine flipping the switch on a new Temenos core banking system, only to find customers’ balances are wrong or transactions went missing, a nightmare scenario for any bank.
This is why data validation and reconciliation are the unsung heroes of Temenos data migration. After all the data is mapped and loaded into Temenos Transact, how do you confirm that everything is correct and complete?
Validation is about ensuring the migrated data is accurate, and reconciliation is about proving nothing is lost or out-of-balance between the old and new systems.
This challenge is critical: mistakes in migration can directly impact regulatory compliance, operational stability, and customer trust.
In fact, even “small errors can escalate quickly” in a core banking context, so rigorous validation is non-negotiable.
Background
Temenos implementations typically involve complex data structures; customer profiles, accounts, transactions, general-ledger entries, etc. that all interlink.
A successful Temenos Transact migration means that for every account in the legacy system, the new Temenos environment has an equivalent account with exactly the same balances and attributes. Any discrepancy even off by a few cents can indicate a problem.
Moreover, banks operate under strict regulatory oversight. If data isn’t migrated correctly, it could lead to reporting errors or compliance breaches. For example, a missing transaction might render a customer’s statement inaccurate or a regulatory report (AML, capital adequacy, etc.) incomplete.
Temenos provides built-in tools and methodologies for validation. For instance, during a Temenos upgrade, an official step is to run data comparison utilities between the old and new environments. One such tool compares data sets to ensure data integrity post-upgrade.
However, these utilities often need to be supplemented with custom checks for a full-core migration from a non-Temenos system.
Financial reconciliation is a key part of validation confirming that the general ledger and critical totals match to the penny between source and target. Given Temenos’s robust financial controls, any mismatch can trigger accounting breaks, so banks put heavy emphasis on reconciling balances, transaction counts, and customer records after migration.
Core Pain Point: Data Validation & Reconciliation Challenges
- Scale of Data: A mid-sized bank might be migrating millions of transactions and accounts. Manually sampling or spot-checking is not enough, you need to verify every record, or at least use statistically sound reconciliation across the whole data set. Traditional methods often involve exporting data from both systems into Excel or text files and doing comparisons which is not feasible at scale. Excel-based reconciliation of millions of entries is practically impossible without errors.
- Reliance on Generic Tools: Many banks try to jury-rig generic ETL tools or custom database scripts for reconciliation, but these often miss the subtle, banking-specific checks Temenos requires: multi-book accounting entries, interest-accrual calculations, complex fee structures. Generic tools lack specialized validation methods for Temenos data migration, meaning critical domain checks may be overlooked.
- Hidden Data Quality Issues: If the legacy system harbored poor data quality, missing mandatory fields, miscoded transaction types, duplicate records some records may fail silently during load. Without proactive validation, these dropped or errored records can go unnoticed until customers complain post-go-live.
- Tight Cutover Windows: Validation and reconciliation must happen during narrow dress-rehearsal and final cutover windows. If a mismatch is found late in the process, the team must scramble to identify, correct, or decide to roll back. Inadequate testing is a known root cause in many migration failures; a high-profile example saw insufficient real-data testing contribute to a core banking outage.
- Audit and Compliance Pressure: Regulators demand proof that every record was accounted for. It’s not enough to perform the checks you must demonstrate them. Manually compiling logs, reports, and sign-offs into an audit package is tedious and prone to oversight, leaving gaps in compliance documentation.
Hopp Tech’s Approach & Best Practices
1. End-to-End Reconciliation Strategy
Plan your Temenos data migration reconciliation approach at project kickoff.
Identify all key data domains that must balance between old and new systems total deposits by product, loan portfolio balances, account counts by branch, daily transaction volumes, fee accruals, etc. For each domain, define reconciliation reports that compare legacy versus Temenos figures.
Automate these comparisons whenever possible. Best practice: generate a trial balance from both systems and compare line by line. Flag any variance even a rounding cent for investigation. Aim for zero unapproved differences.
2. Use Specialized Validation Tools
Hopp Tech’s migration solution includes built-in validation and reconciliation engines purpose-built for Temenos Transact migration.
As data is transformed and loaded, the tool continuously monitors for errors or mismatches. Field-level validations enforce Temenos’s expected formats and business rules. If a legacy data value (e.g., an unrecognized account type code) fails validation, the tool flags it immediately.
Continuous error monitoring prevents small issues from snowballing into project-threatening problems.
3. Maintain a Robust Audit Trail
Every migrated record, transformation and error is logged automatically.
This comprehensive audit documentation proves compliance: when auditors ask “Can you prove transaction X migrated correctly?”, you can produce detailed logs and reconciliation reports on demand.
Automated audit trails also accelerate root-cause analysis when issues surface.
4. Dual-Run and Parallel Testing
Conduct mock migrations where you run a day’s transaction file on both legacy and Temenos systems in parallel.
Compare critical processes interest calculations, end-of-day batch runs to uncover discrepancies. Target high-risk areas for focused validation.
Multiple trial runs allow you to fine-tune scripts, tools and reconciliation reports so that the live cutover is smooth and fast.
5. Financial vs. Data-Level Reconciliation
Differentiate between financial (aggregate) and data (item-level) reconciliation.
Financial reconciliation checks totals sum of deposits, loans, fees, etc. to ensure no major gaps. Data reconciliation verifies individual records: control totals and record counts confirm that, say, 1,000,000 customer records extracted resulted in 1,000,000 loaded.
Tools can automatically flag missing, duplicate or failed records based on predefined rules, reducing manual effort and improving accuracy.
6. Post-Migration Validation in Production
Validation doesn’t end at go-live.
Enter a hypercare period where you run reconciliation on nightly batches and month-end processes.
If any residual issues emerge perhaps a rarely used product got mis-mapped you can correct them directly in Temenos with minimal customer impact.
Mini Case Study
During a recent core migration to Temenos Transact, Bank XYZ defined over 50 reconciliation checks from high-level totals (deposits, loans by currency) to detailed counts (accounts per branch, fee sums).
Their validation engine ran comparisons within minutes after each test migration. In one trial, it flagged seven missing customer records. Logs showed a legacy date field had invalid formats, causing load failures.
The team corrected the transformation rule and included those records on the next run.
For final validation, they performed a parallel run of one day’s transactions: the day before cutover, they processed live transaction files on both systems and reconciled the daily general ledger. Every balance matched to the cent. At go-live, first-day reports aligned perfectly.
The CFO noted it was the first migration she’d seen with zero out-of-balance conditions. Regulators reviewed the automated reconciliation reports and audit logs no findings.
Key Takeaways & Next Steps
- Plan for 100% validation. Treat data quality and reconciliation as core deliverables, not an afterthought.
- Automate reconciliation. Manual Excel checks won’t scale for Temenos data migration. Use specialized tools to compare full data sets efficiently.
- Monitor in real time. Catch and correct errors during migration runs—not afterward.
- Leverage parallel testing. Rehearse your validation process under realistic conditions.
- Document everything. Maintain detailed logs and audit reports for compliance and rapid troubleshooting.
Next Steps: Define your reconciliation domains, automate comparisons in your migration pipeline and conduct dual-run tests. Secure stakeholder sign-off on validation criteria, then extend reconciliation into post-go-live monitoring to guarantee ongoing data integrity.