Financial Crime & Risk
Bad actors hide in fragmented data. The same person or company appears under different names, accounts and addresses in onboarding, core systems, payments and claims, and every control that looks at one record at a time sees a stranger.
For agents. Agents follow resolved links between people, accounts and companies, not name guesses.
Fraud, AML and KYC each see a different, harmless-looking customer. It is one person.
Bad Actors Live Between Your Systems
Financial crime controls are built product by product and team by team. Fraud scores applications, AML monitors accounts, KYC holds onboarding profiles, screening checks names, claims handles claims. Each keeps its own customer records, keyed its own way.
People who want to avoid detection use those seams. They vary a name slightly, use a new email, split activity across accounts, or put a company between themselves and the money. Each control sees a fragment that looks normal.
Teams then rebuild the full picture by hand during investigations, after losses or alerts. It is slow, it differs between analysts, and it happens too late to prevent anything.
Fragmented Customers
The same person appears as different customers in fraud, AML, KYC and claims.
Hidden Networks
Shared phones, addresses, directors and accounts are never linked.
Alert Overload
Name-based checks raise false positives while real connections are missed.
One Identity Layer Under Every Control
Resolve people, companies and accounts once, across every system that holds them, and give each real-world entity one stable ID. Then let fraud scoring, AML monitoring, KYC, screening and claims all work from those entities.
Every control sees the same entity with its full history and connections. Investigations start from linked records instead of rebuilding them, and a change in one system is visible to all the others.
Fraud, AML, KYC and screening all work from this one resolved entity.
Entities, Not Records
Each person and company is resolved once, across onboarding, accounts, payments and claims.
Connections In View
Shared details and ownership link entities into networks you can follow.
Evidence For Every Link
Investigators and auditors can see why records were linked.
Every Control, One Resolved Entity
Fraud Ring Detection
Link synthetic and duplicate identities that share devices, addresses and contact details.
Learn moreAnti-Money Laundering
One identity layer across every AML vector, so transaction monitoring sees the full network.
Learn moreKYC & Perpetual KYC
A customer profile that follows the customer over time, not just the onboarding moment.
Learn moreSanctions & Watchlist Screening
Match against lists with nicknames, transliterations and abbreviations, with fewer false positives.
Learn moreClaims Fraud
Connect claimants, providers and policies to surface repeat and organized claims.
Learn moreThe Identity Layer Under Financial Crime
Zingg runs as a workload inside your data platform and gives every entity one persistent ZINGG_ID. Everything above it reads the same resolved entities.
The same layer powersCustomer Analytics & MarketingPrivacy & ComplianceSupply Chain & ProcurementProduct 360Master Data ManagementAI & Data Foundations
What Zingg Brings
Persistent ZINGG_ID
Every resolved entity keeps one global ID across systems and runs. ZINGG_ID
AI Plus Rules
Matching learned from your labels, combined with deterministic rules where you have them. How Zingg matches
Incremental Flow
Only new and changed records are matched, and IDs persist. Incremental flow
In Your Data Platform
Runs on Databricks, Snowflake, Microsoft Fabric, Google Cloud or AWS. Data never leaves your account.
Financial Crime & Risk Questions
Why does financial crime need entity resolution?
Because bad actors spread activity across records that look unrelated. Resolving those records to real people and companies is what lets fraud, AML and KYC controls see the pattern.
Does Zingg replace fraud, AML or screening tools?
No. Zingg resolves identities and gives each entity a ZINGG_ID. Your existing monitoring, screening and case management tools use those resolved entities.
Can we explain matches to auditors and regulators?
Yes. Zingg’s explainability shows the fields and scores behind every link, so decisions built on resolved entities can be traced back to source records.
Does sensitive data leave our environment?
No. Zingg runs inside your own data platform on Databricks, Snowflake, Microsoft Fabric, Google Cloud or AWS.
See The Entity Behind The Activity
Build one identity layer for fraud, AML, KYC and screening in your own data platform.