The Financial Services Reality:
Risk Has Moved Upstream
Financial institutions are increasingly exposed to untrusted data, moving faster than controls can keep up. Across banks, insurers, and asset management, the pattern is consistent:
Data quality issues surface late, showing up in downstream outputs rather than being caught at ingestion
Teams scramble across fragmented systems to diagnose the root cause
Remediation follows impact, arriving only after decisions or automated activity are already underway
Qualytics: Proactive Data Quality Built for Risk Control
Qualytics moves data quality upstream, before issues reach reports, models, or regulators.
Automated coverage from day one
Qualytics automatically generates and maintains ~95% of data quality rules, delivering broad coverage without months of manual effort.
Built for business and data teams
A low/no-code interface enables data leaders, risk teams, analysts, and engineers to co-own quality in a single governed environment.
Governed, audit-ready workflows
Every rule, anomaly, and remediation action is tracked, explainable, and auditable, supporting regulatory review and executive oversight.
Designed for AI risk
Qualytics validates data before it feeds AI models or automated workflows, reducing downstream exposure and accelerating responsible AI adoption.
Banking
Where risk concentrates
- Regulatory controls and reporting: Capital, liquidity, and regulatory metrics require executive sign-off. Errors in Tier 1/Tier 2 ratios, liquidity coverage, or reported balances can result in material penalties and reputational risk.
- KYC, AML, and transaction monitoring: Inconsistencies in customer profiles, cash flow, or wire destinations introduce compliance exposure if not caught immediately.
- Lending and fair lending data: Loan application, credit, and census data must be complete, reasonable, and distribution-aware to support HMDA and fair lending obligations, not just pass basic null checks.
- Trade, settlement, and balance reconciliation: Trades, loans, and deposits must reconcile cleanly across operational, settlement, and accounting systems to ensure accurate and consistent data roll-ups across business lines.
What Qualytics enables
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Continuous validation of high-risk banking data
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Audit-ready regulatory controls with version history
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Automated reconciliation across systems and business units
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Early resolution of issues before reports, models, or filings
A global financial institution automated over 20,000 data quality rules with ~96% automation, achieving an estimated 18x ROI in year one while strengthening regulatory confidence.
Insurance
Where risk concentrates
- Premium leakage and pricing accuracy: Errors in premium, exposure, or policy data lead to under-collection, over-pricing, or unpriced risk, directly impacting profitability and regulatory reporting.
- Underwriting model integrity: Underwriting decisions often run in black-box systems. When input data drifts or violates model assumptions, risk accumulates silently.
- Claims and operational automation: Automated claims and operational workflows amplify data errors if quality issues aren’t detected early across fragmented legacy systems.
What Qualytics enables
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Continuous validation of underwriting and policy data
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Early detection of drift across underwriting and claims systems
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Audit-ready controls aligned to regulatory expectations
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Reduced manual review and exception handling
A global insurer identified and automated controls around data quality issues tied to ~$10M per year in premium leakage, replacing manual checks with continuous validation.
Alternative Asset Management
Where risk concentrates
- Quarter-end performance and valuation reporting: Preliminary quarter-end numbers drive investment decisions before final actuals arrive. Undetected changes between versions introduce material reporting and trading risk.
- Entity-heavy portfolio aggregation: Portfolio companies, administrators, and third parties report data inconsistently, creating reconciliation risk as results roll up to the fund and enterprise level.
- Operational reconciliation at scale: Capital movement depends on accurate calculations across systems. Small discrepancies can materially impact reported performance and LP communications.
What Qualytics enables
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Reduce operational and regulatory risk before impact
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Enable AI with confidence, not exception handling
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Replace reactive firefighting with continuous control
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Scale data quality without scaling headcount
Asset managers using Qualytics have reduced manual reconciliation time by up to 70%, improved reporting accuracy, and scaled oversight without adding headcount.
Discover more insights from the
Qualytics team
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