Ariath glossary: Batch Processing
Handles data in scheduled groups, or batches, rather than record by record as it arrives. It is the counterpart to real-time processing, where each record is handled as soon as it is received.
In brief
- What it does
- Handles data in scheduled groups instead of one record at a time as it arrives.
- How it differs from real-time processing
- Batch results reflect the data as of the last run. Real-time processing keeps results current as records arrive.
- What it needs in a wealth management firm
- Clear schedules, validation, error alerts, and records of each run.
How it works
How batch processing works
A batch run generally moves through the same stages:
Collect the records
Data accumulates until the batch is due to run.
Run on a schedule
At a set time, such as overnight, the system processes the whole group together.
Validate and transform
Records are checked and prepared, for example by matching formats or catching missing fields.
Load and report
Results are written to the destination system, and errors or exceptions are flagged for review.
Some custodian and planning data reaches a firm on a schedule, such as daily files, so downstream systems may update in batches.
Batch processing trades immediacy for efficiency: the data is only as current as the last run.
Comparison
Batch vs. real-time processing
The choice is mainly about how current the data needs to be.
Batch processing
Handles records in groups at set times. It suits large volumes, though results reflect the data as of the last run.
For example
An overnight job that refreshes data in a reporting system.
Real-time processing
Handles each record as it arrives, so results stay current. It can require more continuous processing and monitoring.
For example
A new client record appearing in a connected tool shortly after it is created.
Many firms use both. Teams weigh how current a process needs to be against the volume of data it handles.
In practice
Batch processing examples in wealth management
Work that follows a calendar or handles large volumes often runs in batches. These examples are illustrative.
Custodian data files
Loading scheduled account and position files into the firm's systems.
Fee calculations
Running fee calculations for a billing period so staff can review the results.
Reconciliation
Comparing records across systems on a schedule and listing differences.
Report generation
Producing a group of client reports in one run.
Data clean-up
Standardizing or de-duplicating records in bulk.
Each firm decides which work runs in batches and which needs to stay up to date.
What it needs
What batch processing needs to be reliable
Because a batch handles many records at once, a mistake can spread widely. Teams typically put the following in place:
- Clear schedules and named ownership
- Validation before data is loaded
- Error handling and alerts
- The ability to rerun a batch safely
- A record of each run
- Access controls on the data involved
These are firm decisions, set in line with the firm's own processes and policies.
Common questions
Frequently asked questions about batch processing
How is batch processing different from real-time processing?
Batch processing handles records in groups on a schedule. Real-time processing handles each record as it arrives.
When does batch processing fit?
It can fit when large volumes can be handled on a schedule and immediate updates are not needed. Each firm decides this process by process.
Why might data look out of date in a connected system?
If a system updates in batches, it reflects the data as of its last run, so recent changes elsewhere may not appear until the next one.
This entry is educational. It is not legal or compliance advice and does not guarantee regulatory compliance. Confirm the requirements that apply to your firm with your compliance lead or counsel.
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