In the world of financial data aggregation, accuracy is more than a measure of quality — it is the foundation of trust. At PCR, we consider data as the product itself. Every interface, conversion, and output is designed with one purpose: data integrity.
This blog brings you behind the scenes of how PCR has cultivated a culture of precision — through technical excellence, sound governance, and continuous improvement. From ingestion to auditability, we verify that what our customers see is not just whole, but demonstrably accurate.
Aggregating financial data across multiple sources — custodians and banks, private investment statements, and the like — is conceptually different from data aggregation in general. These aren't just volume and variety of data challenges but also high-stakes challenges for reporting errors: regulatory non-compliance, miscomputation of NAVs, misreporting client holdings.
At PCR, our customers rely on timely, accurate, and consolidated reporting to present their own clients with confidence. That's why we treat data accuracy not as a result — but as a constant, technical process integrated into our operations.
The initial step to guarantee clean and trustworthy data begins in the manner in which we ingest it. PCR ingests data from numerous sources, each with its own formatting, delivery, and frequency. Our ingestion pipeline is strong, standardised, and extremely secure.
Custom Connectors for Every Source: We develop specialized ingestion connectors, specific to banks, custodians, fund managers, and private equity sources, to manage variations in format between SWIFT, OFX, CSV, XML, and PDFs.
Schema Validation at Source: Data goes through schema validation engines, where it is scanned for field types, missing values, and violations of user-defined logic before entering our staging layer.
Encrypted, Monitored Transfers: Each file transfer is encrypted, tracked, and monitored. This provides for both security and traceability — particularly important in financial settings.
These systems guarantee that from the very point data comes into our system, it's already headed toward structured, verifiable accuracy.
After ingestion, we normalise data into a common schema for seamless reporting. This allows data from multiple institutions to be viewed uniformly.
Our normalisation engine applies:
Reconciliation follows immediately after. Every day, we match:
This phase ensures not just formatting consistency — but financial accuracy that is critical for wealth reporting, compliance, and decision-making.
Even with robust automation, certain exceptions need human judgment — particularly for private assets and alternative investment reports.
Here's the exception handling process that we follow:
Detection: Our system automatically flags any exceptions — such as missing trades, unusual valuations, or misaligned capital call information.
Triage: These are sorted and directed to apposite analysts who specialize in specific asset types or data sources.
Resolution & Feedback Loop: Analysts resolve the exceptions and log them. That information is then fed back into our automation model so that future detection can be enhanced.
By leveraging machine learning and expert analysts, we refine the quality layer continuously — making the system smarter with each cycle.
Transparency is essential in financial data aggregation. Every step — from ingestion to final report generation — must be auditable.
PCR builds end-to-end audit trails that track:
Clients gain visibility into how any data point was derived and can roll back to historical states if needed. This level of data lineage ensures compliance readiness and strengthens institutional trust.
Technology is not sufficient — precision in PCR comes from a company culture. We educate and motivate our staff to maintain data integrity at all stages.
Some of the main cultural practices are:
Weekly Data Quality Huddles: cross-functional teams sit down to discuss error patterns and enhance detection rules.
Client Feedback Loops: We incorporate explicit feedback from RIAs, family offices, and wealth advisors in order to adjust ingestion logic and validation checks.
Continuous Learning: Analysts and engineers undergo continuous training in new asset classes, document forms, and financial standards.
We also have an internal data quality dashboard in which each feed is graded on timeliness, accuracy, and reconciliation success rate.
As PCR grows its financial data aggregation capabilities — including support for more custodians, APIs, and private equity platforms — our focus on accuracy scales along with it.
We’re actively investing in:
These investments help us maintain data accuracy at scale, even as data types, volumes, and client requirements continue to diversify.
For PCR, data accuracy is not a checkbox — it’s a commitment. Every institution, advisor, and client that relies on us for financial data aggregation knows they can trust what they see. We’ve built our systems, people, and culture around this principle: Data is the product.
And that product must be complete, clean, and correct — every single time.