Data processing

What kind of data processing work can actually be outsourced?

Data entry, cleansing, validation, digitisation and structured data preparation for downstream systems make up the core of Corpshore's data processing service. This spans a wide range of practical work: entering paper or scanned records into a digital system, cleaning and standardising a dataset before it is loaded into a client's CRM or analytics platform, validating fields against business rules, and preparing structured extracts that feed a client's own reporting or machine learning pipeline. What ties this work together is that it is high-volume, rules-based and benefits from a documented process with a clear audit trail, distinct from back office case management work in that it is usually less about handling individual customer cases and more about processing large volumes of records against a consistent standard.

How is data processing work actually priced?

Data processing engagements are typically priced by volume and turnaround rather than by seat, which is a deliberate difference from a staffing model. A client pays against the number of records processed and the turnaround time agreed, rather than for a fixed number of full-time positions regardless of how much data actually needs processing in a given period. This makes the cost case unusually easy to model: a business can compare its current per-record or per-batch cost, whether that cost is currently absorbed by internal staff time or a smaller existing vendor, directly against a quoted rate, without needing to translate a headcount-based number into a volume-based one first.

How is data kept secure and compliant, especially when it moves offshore?

Data processing work frequently touches personal information, whether that is customer records being cleaned, application forms being digitised, or datasets containing identifiable details being prepared for a downstream system. This puts Australian Privacy Principle 8 and section 16C of the Privacy Act 1988 (Cth) directly in scope: before an Australian business discloses personal information to an offshore data processing provider, it must take reasonable steps to ensure that provider will not breach the Australian Privacy Principles, and under section 16C the Australian entity is treated as if it breached the principle itself if the offshore provider causes a breach. Corpshore builds access controls, data handling terms and audit reporting into every engagement with that ongoing accountability in mind, and aligns its security practices with the Essential Eight, the Australian Cyber Security Centre's recognised set of mitigation strategies covering patching, multi-factor authentication and restricted administrative access, as a working framework.

The Notifiable Data Breaches scheme is also relevant background here: it applies to Australian Government agencies and private or not-for-profit entities with annual turnover over $3 million, plus some smaller entities regardless of turnover, and requires notification of affected individuals and the OAIC where an eligible data breach is likely to cause serious harm. Where the underlying data is health information, this sits alongside the additional considerations covered on the healthcare industry page. For New Zealand clients, the Privacy Act 2020's IPP12 service-provider exception is worth understanding specifically: data sent overseas purely for safe custody or processing on the client's behalf is not treated as a "disclosure" at all under that provision, provided the offshore provider does not use it for its own purposes, which is a lighter compliance position than Australia's APP 8.

How does data processing differ from AI-assisted document intelligence?

Data processing, as delivered here, is primarily a trained human workforce following documented rules to enter, clean, validate and structure data accurately and consistently at volume. Document intelligence is a distinct, AI-assisted service focused on automatically extracting and classifying information from unstructured documents, invoices, contracts, forms, using machine processing rather than manual entry as the primary method. In practice, the two are often complementary rather than competing options: a document intelligence layer can handle the bulk extraction from a large volume of documents, while a human data processing team handles exception cases, validation and the records that do not fit a clean automated pattern. Clients weighing up which approach fits a specific workflow should look at both services together rather than choosing one in isolation.

How much can outsourcing data processing save compared to an in-house team?

PayScale data puts Australian data entry pay at roughly $37.20 an hour, or the equivalent of $70,000 to $75,000 a year on a full-time basis, before the compulsory superannuation guarantee, which reached 12% of ordinary time earnings from 1 July 2025, is added. Against that fully loaded benchmark, reported savings for Australian and New Zealand clients run 60 to 75%, consistent with the range reported across Corpshore's other BPO services, with straightforward, rules-based processing sitting toward the higher end of that range and work requiring more validation judgement sitting somewhat lower. A tailored quote built against actual record volume will give a more precise figure than a general industry percentage.

Can data processing be kept entirely onshore in Australia?

Yes, for clients that need the work kept entirely within Australia, whether for regulatory reasons or internal policy, alongside offshore and blended options for higher volume or lower cost requirements. As with other BPO services, an onshore-only model carries the same Australian salary, superannuation and award costs as an in-house team, so the cost saving is smaller than an offshore or blended arrangement, but it remains an available option rather than something clients are forced to trade away entirely to access outsourced delivery. Delivery through hubs such as the Philippines, the parent group's primary offshore delivery partner for both the Australian and New Zealand markets, is the more common choice for clients prioritising cost and scale.

How do we get started?

A scoped pilot against one dataset or document type, with a clear turnaround and accuracy target agreed up front, is the most reliable way to test both quality and saving before committing to a larger volume. From there, a request for a quote priced against actual record volume, or a discovery call to work through which combination of manual processing and automated document intelligence fits a specific workflow, are the fastest practical next steps.