Automated processing for data quality management.

Apply your institution's procedures to every account in your portfolio. Go into exam season knowing your team reviewed every account, not a sample.

100% QC coverage.

Every account in the population gets the same checks, not the slice that fits in the week.

Document it once.

Every check, every finding, and every disposition recorded the same way by the same process.

Stop borrowing people.

No pulling staff off other work to get a review cycle finished before an exam.

Managed quality control for deposit and lending operations.

Polaris Data Quality Management is a managed service for QC teams. We take a core account extract and the supporting documents from imaging, check every account against your own written procedures, and return a scored, account-level list of what failed, what needs a human look, and what could not be checked. Your people keep their systems, their workflow, and their judgment. We handle the reading and the reconciling, and we leave a record of it.

Built for risk, compliance, and QC teams at banks and credit unions.

Risk

Accountable for whether testing coverage is adequate, and for explaining that coverage to a board.

Compliance

Owns monitoring and self-identification, and has to show both held up across the population.

Operations and QC

Running post-close and account review at the regulatory minimum because that is all the bandwidth allows.

Internal audit

Has to assess independently whether QC was performed consistently and whether conclusions were recorded.

The hidden costs of reviewing a sample.

Nobody samples to save money. They sample because reviewing everything by hand would take time the team does not have, or people it would have to pull off their own work. The cost of that never lands in one place. It shows up later, in an exam room, in a rating, and in the week a review cycle takes.

Exam exposure.

A sample never really tells you the whole picture. The findings that turn into exceptions tend to sit in the part nobody opened.

Polaris tests the whole population, so there is no untested remainder left to be surprised by.

A thinner monitoring rating.

Examiners weigh whether monitoring was sufficient, not whether it happened, and coverage set by available bandwidth reads as thin.

Polaris runs the same checks on every account and records them the same way every time.

The credit you give up.

Corrective action and self-identification earn explicit credit in a compliance rating, and you cannot self-identify inside a population you never looked at.

Polaris surfaces it in your own review first, with the record of how you found it.

The people you borrow.

Every review cycle takes somebody off something else, and that interruption never appears as a line item anywhere.

Polaris lets the same team cover the whole portfolio without borrowing anyone.

Every account comes back one of three ways.

Post-close QC happens after the account is already open. Polaris reads the account record from your core alongside the documents filed behind it in imaging, applies your own written procedures to every account in the batch, and returns one of three outcomes for each. Green, amber, or red, the same way your risk reporting already grades everything else. The same rules can run at intake instead of after the fact, which is where this is headed.

Green. It cleared.

Every check passed and you hold the record proving it. No reviewer time spent confirming what was already fine.

Amber. Something could not be verified.

The owner name check needs the signature card that is missing, so it reports as not checked rather than passing quietly. The account comes back for review, not clean.

Red. It has a break.

No signature card in the file. Flagged as a critical error, tied to the account, with the rule that failed named.

The Polaris data engine gets to work.

Six things happen to every account you submit, whether it is one or several hundred.

Two-file intake

A core account extract and a zip file of supporting documents from cold storage. Fiserv, Jack Henry, Symitar, OnBase, Iron Mountain, or whatever you run.

Automatic correlation

Documents are matched back to accounts on their own. Submit one account or several hundred in the same batch.

Validation against your own SOP

Your written procedure becomes the ruleset, assertion by assertion. Change the procedure and the checks change with it, so the review always matches how you actually open accounts.

Breaks ranked and separated

Missing documents, data mismatches, and compliance breaks, split into errors, items needing review, and checks that could not run.

Triage inside the document

Click a finding and the exact spot in the actual document is highlighted. Confirm it, waive it, or mark it a false positive.

Output that lands where you work

A findings document per account plus a structured data file, so results feed a ticketing queue, a spreadsheet, or whatever you track work in today.

Two files in, and the batch runs itself.

Submit a core account extract and the supporting documents, and every file takes the same six steps in the same order. Every stage is visible while it runs, the log is retained as a record of what was evaluated, and your team is notified when the results are ready.

Drop in the extract and the documents

A CSV export from your core and a bundle of the supporting documents from imaging. No integration project, no API work, and no IT ticket to get started.

The batch comes back ranked

Clean, broken, and indeterminate accounts split out, with every break graded critical, major, or minor so your team knows where to start.

Every account scored, worst first

A completeness score per account, with each finding tied to the rule that produced it and the document it came from.

The evidence behind every finding

Open any account and every document the procedure expects is listed, with the values pulled from each one. Any that are missing are named right there beside the ones on file.

Including the checks it could not finish

Here the tax ID on the W-9 was too unclear to match the core record, so it reports as indeterminate and goes to a person rather than quietly passing.

Scored results, ready to export

Every account scored and banded, exportable to your ticket queue, a spreadsheet, or your system of record.

How We Engage

Pilot-to-Partnership: proof before commitment.

We earn trust at every step. No long-term contract required to get started, and no live accounts needed for the proof of concept.

Step 01

Discovery

Free · 1–2 weeks

We map your current QC workflow and identify where Polaris delivers the most immediate value for your team and systems.

Step 02

Proof of Concept

Low cost · 2–4 weeks

Send us a sample account extract and the matching documents from your archive. We return a full findings report and scored results. Compare them against your own review and you will know immediately if it is useful.

Step 03

Pilot

Fixed rate · 3–6 months

Run Polaris in production at discounted fixed pricing. Validate coverage, data quality, and team adoption on live accounts before any long-term commitment.

Step 04

Partnership

SLA-backed · Ongoing

Outcome-based engagement with predictable pricing and SLA-backed delivery. Scales with your account volume as needs evolve.

Your data, held to the standard you would set yourself.

Your account records and member documents are the most sensitive data you hold. We treat them that way, and we hold the certifications to show it.

ISO 27001:2022

Certified against the international standard for information security management.

SOC 2 Type II

Independently audited controls for security, availability, and confidentiality.

Your data stays yours

Encrypted in transit and at rest, access controlled by role, and never used to train anything.

See what 100% QC coverage looks like on your portfolio.

Fifteen minutes on how your team reviews today is enough for us to tell you what full coverage would change and what it would take to get there.