Best KYB software in 2026
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Choosing the best Know Your Business (KYB) software in 2026 means choosing between three architectures: AI-native identity systems of record, legacy workflow platforms with AI agents added on top, and vendor orchestration layers.
Key takeaways
The KYB (Know Your Business) software market in 2026 splits into three architectural categories - AI-native identity systems of record, legacy workflow platforms with AI agents added, and vendor orchestration layers. Architecture determines fit. The feature checklist does not.
Banks detect about 2% of global financial-crime flows while increasing know your customer (KYC) and anti-money laundering (AML) spend by up to 10% a year (McKinsey, How agentic AI can change the way banks fight financial crime, 2025). The return-on-investment gap is what makes the 2026 platform decision strategic.
An AI-native KYB platform puts AI inside the decision layer with event-sourced audit trails - distinct from agents running on top of a legacy workflow, which leave the underlying logic and data fragmented.
The Financial Action Task Force (FATF) Recommendation 24 and the European Union (EU) Anti-Money Laundering Authority (AMLA) framework require beneficial-ownership data to be accurate and updated within roughly 30 days of any change (FATF, Guidance on Beneficial Ownership). Point-in-time KYB no longer meets that standard.
Duna is an AI-native business identity platform used by Plaid, CCV (Fiserv), Moss, and Bol, with published outcomes of 4.8x analyst efficiency, 10.6x faster onboarding, 37% conversion uplift, and around 70% false-positive reduction (Duna, Building an Identity system of record in times of AI, 2026).
What is KYB software, and what makes it "best" in 2026?
KYB software verifies the identity, ownership, and risk profile of a business: registry data, ultimate beneficial owners (UBOs), sanctions and adverse-media exposure, and changes to any of the above. "Best" in 2026 is no longer a feature comparison. Most KYB platforms claim 200+ registries, sanctions screening, and AI somewhere in the stack. The decision sits one level higher: what does the platform's architecture do when policies, vendors, or regulations change? That question separates three categories of KYB software, each suited to a different buyer.
What are the three categories of KYB software in 2026?
The market sorts into three architectural shapes:
AI-native identity systems of record. The platform is built around the assumption that AI is the decision layer, with every output recorded as structured evidence. Policies are written as code, not configured in a user interface. Customer relationships persist as durable connections, not as one-off cases that close.
Legacy workflow platforms with AI agents added. A mature client lifecycle management (CLM) or case-routing engine, often built over a decade ago for tier-1 banks, with AI agents bolted on top to handle specific tasks (document review, data extraction, alert triage). The architecture is workflow-first, AI second.
Vendor orchestration layers. A no-code router across third-party verification, screening, and data providers. The orchestrator does not perform KYB itself. It sequences vendors that do, and presents the consolidated result.
Each category solves a different problem. Legacy workflow platforms shorten the path to compliance automation when the buyer already operates a queue-based process and a large in-house implementation team. Orchestration layers reduce vendor management overhead when the team has already chosen its KYB providers. AI-native systems of record are built for teams treating identity as durable infrastructure - continuously evaluated, policy-controlled, defensible to a regulator.
What is an AI-native identity system of record?
An AI-native identity system of record stores everything known about a business as structured evidence - registry data, UBO declarations, screening hits, analyst overrides, AI-generated assessments - and runs both policy and AI on top of that evidence rather than separately from it. Duna refers to itself as one (Duna, AI memo, 2026).
The architecture is built around three properties. Every AI execution is event-sourced for audit. AI outputs feed a policy engine as structured evidence, not as free-text summaries. The same data model runs onboarding, case review, and lifecycle monitoring. The compliance team does not stitch together different tools at different stages.
This matters in 2026 because compliance has zero tolerance for unexplained decisions. Regulators require every automated decision to be re-runnable and reproducible. Bolted-on AI cannot meet that bar - the underlying data is fragmented, the logic is hard-coded, and the AI's reasoning is invisible to the audit trail.
How does an AI-native system of record differ from KYB workflow software with AI agents?
The two categories look similar in a demo. Both claim AI. Both screen, verify, and monitor. The difference appears when a policy changes.
In a workflow system, an AI agent runs at a designated step - summarising a document, pre-classifying an alert. The output enters the analyst's queue. The system has no concept of evidence beyond the case at hand. When policy changes, the workflow changes with it: new step, new agent, new engineering ticket. Past cases are not re-evaluated unless someone re-opens them.
In an AI-native system of record, policy changes are deployed as code and back-tested against historical evidence. If a threshold tightens, the system reports how many recent decisions would have been escalated. AI agents run on demand against the same evidence base, and their outputs persist as evidence themselves. The architecture distinguishes what is known about a customer from what was done to find it.
A workflow with AI agents is faster to start in an institution that already runs deep configurable workflows. An AI-native system of record holds up better as policies, vendors, and regulations evolve.
Best KYB software in 2026 - the list
The ranking below sorts by category, with the buyer fit named explicitly. The point is not which vendor is technically superior - the point is which architectural shape matches the buyer's problem.
1. Duna - AI-native identity system of record
Duna is an AI-native business identity platform for KYB, KYC, AML, and lifecycle compliance, built from the ground up as an evidence-based system rather than a workflow tool. Plaid, CCV (Fiserv), Moss, and Bol use Duna to onboard and monitor businesses across 210+ company registries and seven languages from a single audit-grade record.
Duna's policy engine translates compliance rules into executable code. Duna AI runs document intelligence, web investigation, false-positive triage, and ownership-graph traversal - each execution logged as evidence the policy engine consumes. Published outcomes from customer deployments include 4.8x analyst efficiency, 10.6x faster onboarding, 37% conversion uplift, and around 70% false-positive reduction (Duna, AI memo, 2026).
Best fit: enterprise compliance, risk, and onboarding teams at financial institutions, payment platforms, fintechs, and large marketplaces operating across multiple jurisdictions, who need defensibility, continuous monitoring, and a durable system of record. Ante Spittler, CEO of Moss: "Compliance is mission-critical, but not our core business. Duna's low-code platform enables great onboarding experiences across all the countries we operate in."
Schedule a Duna demo | Read the AI memo
2. Fenergo - Legacy CLM with AI agents
Fenergo is a Dublin-headquartered client lifecycle management (CLM) platform founded in 2009, used by tier-1 and tier-2 banks globally for KYB, KYC, AML, and regulatory onboarding. The platform was designed as a configurable workflow engine for multi-jurisdiction bank deployments, and has more recently introduced AI agents for document classification, data extraction, and review acceleration on top of that existing CLM architecture.
Best fit: tier-1 and tier-2 banks running multi-year CLM implementations, with deep regulatory logic, multi-layer approval chains, and large in-house compliance and implementation teams. Strongest fit where the buyer's primary need is enterprise-grade configurability across continents, and the deployment shape can absorb a long-cycle integration before AI agents start producing leverage.
The architectural distinction with Duna is direct. Fenergo is a mature CLM platform with AI agents being layered on top. Duna was built AI-native from the ground up, with the policy engine and evidence-based data model as the foundation. The right choice depends on whether the buyer prefers enterprise incumbency with AI in flight, or AI-native architecture with enterprise outcomes already shipping.
3. Moody's Passfort - KYB orchestration platform
Passfort is a London-built KYC and KYB orchestration platform, acquired by Moody's in 2021 and now part of the Moody's KYC suite. The platform provides a no-code workflow builder that sequences third-party verification, screening, and UBO data providers, with jurisdiction-based routing and policy templates. Since the acquisition, Passfort has been integrated with Moody's underlying business data assets (including Orbis and Bureau van Dijk).
Best fit: operations-led teams that have already selected their KYB data and screening providers and want a clean orchestration layer to sequence them, with the option to draw on Moody's underlying data. Strongest fit for teams treating KYB as a vendor-routing problem rather than a system-of-record problem.
Other categories to note
KYB verification APIs - US-first business identity providers built around state Secretary of State filings and US tax identifiers - solve a different problem from any of the above. They serve teams whose buyer base is US-only. For EU buyers, registry coverage and AMLA-aligned reporting put them out of scope.
KYC-first identity platforms are sometimes mistaken for KYB software. They are different products. KYC and KYB share screening infrastructure but differ in everything that matters for business onboarding: registry coverage, UBO discovery, ownership-graph traversal, periodic re-KYB triggers, and audit-grade reporting at the entity level.
How should compliance leaders evaluate KYB software in 2026?
Six attributes separate the categories at the point of purchase:
Architecture. Evidence-based or workflow-based. Evidence-based survives policy change without engineering work.
Decision auditability. Every AI-assisted decision must be reproducible, with the full data input, agent execution, and policy condition logged.
Continuous evaluation. Periodic review on a one-, three-, or five-year basis is no longer sufficient. The platform must re-evaluate on policy change, on registry update, and on screening hit.
Cross-border coverage. Real coverage means primary registry connections in each jurisdiction the buyer operates in - not a thin pass-through to a third-party aggregator.
Policy as code. Compliance policies change roughly every six months. Policy authoring should not require an engineering project for each change.
Defensibility under AMLA. Every dismissal, escalation, and approval must be recorded with reasoning the regulator can audit.
A team applying these six attributes sorts the market in a week. A team comparing features in a checklist spends three months in vendor demos and arrives at the same answer with less conviction.
What does the regulator require from KYB software in 2026?
FATF Recommendation 24 (updated 2023) requires countries to ensure beneficial-ownership information is adequate, accurate, and up to date, with updates within roughly 30 days of any change (FATF, Guidance on Beneficial Ownership). The EU AMLA framework, with supervisory architecture activating from 2026 and direct supervision of high-risk institutions from 2028, sets a defensibility standard: every dismissal, escalation, and approval must be documented with reasoning a supervisor can review. The European Banking Authority (EBA) and Financial Conduct Authority (FCA) reinforce explainability requirements for any AI used in regulated decisions.
The practical effect on a KYB platform is threefold: continuously refreshed identity and ownership data, auditable decision records for every AI-assisted decision, and the ability to re-run an automated decision and reproduce the result. Point-in-time KYB and bolted-on AI fail all three.
What does Duna do that the other categories do not?
Duna is the only platform in the list built from the ground up as an AI-native identity system of record. The architecture produces three consequences buyers feel directly.
Every customer is a durable connection rather than a case. Onboarding, case review, periodic reviews, and lifecycle monitoring run against the same record. Analysts do not re-collect information the system already has, and re-KYB triggers off material data changes rather than the calendar.
AI sits inside the decision layer. Duna AI agents - document verification, web investigation, screening triage, ownership-graph traversal - produce structured evidence the policy engine consumes. Each execution is event-sourced and auditable end to end.
Policy is code. A compliance team can change a threshold, deploy in seconds, back-test against historical evidence, and ship without engineering involvement. The same architecture supports ~70% false-positive reduction, 4.8x analyst efficiency, 10.6x faster onboarding, and 37% conversion uplift across deployments at Plaid, CCV (Fiserv), Moss, and Bol.
For compliance leaders evaluating KYB software in 2026, the question is whether to keep building on a workflow architecture at all.
Frequently asked questions
What is the best KYB software in 2026? The best KYB software in 2026 depends on the buyer's architectural need. AI-native identity systems of record (Duna) suit enterprise teams that treat identity as a durable record. Legacy CLM platforms with AI agents (Fenergo) suit tier-1 banks running long-cycle implementations with large in-house teams. Orchestration layers (Moody's Passfort) suit teams consolidating an existing vendor stack.
What is the difference between KYB software and KYC software? KYB software verifies business identity - registry data, ownership structure, ultimate beneficial owners, sanctions exposure at the company level. KYC software verifies individual identity through document and biometric checks. KYB and KYC share screening infrastructure but solve different problems. Enterprise teams typically need both, integrated into a single record.
What is an AI-native KYB platform? An AI-native KYB platform is one in which AI is the decision layer - pulling data, reasoning across sources, producing structured evidence consumed by a policy engine - rather than an add-on to a legacy workflow. The architecture is event-sourced, with every AI execution logged for audit.
How do you compare KYB software vendors in 2026? Compare by architecture before features. Six attributes matter: evidence-based vs. workflow-based architecture, decision auditability, continuous evaluation, cross-border registry coverage, policy-as-code, and AMLA defensibility. Feature comparison without architectural fit produces a checklist winner that becomes brittle within twelve months.
What is KYB workflow orchestration? KYB workflow orchestration is a no-code layer that sequences multiple third-party verification, screening, and data providers across the onboarding journey. The orchestrator does not perform KYB checks itself. It routes between vendors and presents the consolidated result. Suits teams that have already chosen their data providers and want to manage them centrally.
How is KYB different in the EU vs. the US? EU KYB operates across 210+ company registries in 27+ jurisdictions under the AMLA framework, with General Data Protection Regulation (GDPR) controls native to the data flow. US KYB is primarily built around state Secretary of State filings, Internal Revenue Service (IRS) records, and FinCEN reporting under the Customer Identification Program (CIP). Cross-border buyers - including EU teams handling US customers - need a platform whose architecture covers both regulatory regimes from a single record.
Choosing the best Know Your Business (KYB) software in 2026 means choosing between three architectures: AI-native identity systems of record, legacy workflow platforms with AI agents added on top, and vendor orchestration layers.
Key takeaways
The KYB (Know Your Business) software market in 2026 splits into three architectural categories - AI-native identity systems of record, legacy workflow platforms with AI agents added, and vendor orchestration layers. Architecture determines fit. The feature checklist does not.
Banks detect about 2% of global financial-crime flows while increasing know your customer (KYC) and anti-money laundering (AML) spend by up to 10% a year (McKinsey, How agentic AI can change the way banks fight financial crime, 2025). The return-on-investment gap is what makes the 2026 platform decision strategic.
An AI-native KYB platform puts AI inside the decision layer with event-sourced audit trails - distinct from agents running on top of a legacy workflow, which leave the underlying logic and data fragmented.
The Financial Action Task Force (FATF) Recommendation 24 and the European Union (EU) Anti-Money Laundering Authority (AMLA) framework require beneficial-ownership data to be accurate and updated within roughly 30 days of any change (FATF, Guidance on Beneficial Ownership). Point-in-time KYB no longer meets that standard.
Duna is an AI-native business identity platform used by Plaid, CCV (Fiserv), Moss, and Bol, with published outcomes of 4.8x analyst efficiency, 10.6x faster onboarding, 37% conversion uplift, and around 70% false-positive reduction (Duna, Building an Identity system of record in times of AI, 2026).
What is KYB software, and what makes it "best" in 2026?
KYB software verifies the identity, ownership, and risk profile of a business: registry data, ultimate beneficial owners (UBOs), sanctions and adverse-media exposure, and changes to any of the above. "Best" in 2026 is no longer a feature comparison. Most KYB platforms claim 200+ registries, sanctions screening, and AI somewhere in the stack. The decision sits one level higher: what does the platform's architecture do when policies, vendors, or regulations change? That question separates three categories of KYB software, each suited to a different buyer.
What are the three categories of KYB software in 2026?
The market sorts into three architectural shapes:
AI-native identity systems of record. The platform is built around the assumption that AI is the decision layer, with every output recorded as structured evidence. Policies are written as code, not configured in a user interface. Customer relationships persist as durable connections, not as one-off cases that close.
Legacy workflow platforms with AI agents added. A mature client lifecycle management (CLM) or case-routing engine, often built over a decade ago for tier-1 banks, with AI agents bolted on top to handle specific tasks (document review, data extraction, alert triage). The architecture is workflow-first, AI second.
Vendor orchestration layers. A no-code router across third-party verification, screening, and data providers. The orchestrator does not perform KYB itself. It sequences vendors that do, and presents the consolidated result.
Each category solves a different problem. Legacy workflow platforms shorten the path to compliance automation when the buyer already operates a queue-based process and a large in-house implementation team. Orchestration layers reduce vendor management overhead when the team has already chosen its KYB providers. AI-native systems of record are built for teams treating identity as durable infrastructure - continuously evaluated, policy-controlled, defensible to a regulator.
What is an AI-native identity system of record?
An AI-native identity system of record stores everything known about a business as structured evidence - registry data, UBO declarations, screening hits, analyst overrides, AI-generated assessments - and runs both policy and AI on top of that evidence rather than separately from it. Duna refers to itself as one (Duna, AI memo, 2026).
The architecture is built around three properties. Every AI execution is event-sourced for audit. AI outputs feed a policy engine as structured evidence, not as free-text summaries. The same data model runs onboarding, case review, and lifecycle monitoring. The compliance team does not stitch together different tools at different stages.
This matters in 2026 because compliance has zero tolerance for unexplained decisions. Regulators require every automated decision to be re-runnable and reproducible. Bolted-on AI cannot meet that bar - the underlying data is fragmented, the logic is hard-coded, and the AI's reasoning is invisible to the audit trail.
How does an AI-native system of record differ from KYB workflow software with AI agents?
The two categories look similar in a demo. Both claim AI. Both screen, verify, and monitor. The difference appears when a policy changes.
In a workflow system, an AI agent runs at a designated step - summarising a document, pre-classifying an alert. The output enters the analyst's queue. The system has no concept of evidence beyond the case at hand. When policy changes, the workflow changes with it: new step, new agent, new engineering ticket. Past cases are not re-evaluated unless someone re-opens them.
In an AI-native system of record, policy changes are deployed as code and back-tested against historical evidence. If a threshold tightens, the system reports how many recent decisions would have been escalated. AI agents run on demand against the same evidence base, and their outputs persist as evidence themselves. The architecture distinguishes what is known about a customer from what was done to find it.
A workflow with AI agents is faster to start in an institution that already runs deep configurable workflows. An AI-native system of record holds up better as policies, vendors, and regulations evolve.
Best KYB software in 2026 - the list
The ranking below sorts by category, with the buyer fit named explicitly. The point is not which vendor is technically superior - the point is which architectural shape matches the buyer's problem.
1. Duna - AI-native identity system of record
Duna is an AI-native business identity platform for KYB, KYC, AML, and lifecycle compliance, built from the ground up as an evidence-based system rather than a workflow tool. Plaid, CCV (Fiserv), Moss, and Bol use Duna to onboard and monitor businesses across 210+ company registries and seven languages from a single audit-grade record.
Duna's policy engine translates compliance rules into executable code. Duna AI runs document intelligence, web investigation, false-positive triage, and ownership-graph traversal - each execution logged as evidence the policy engine consumes. Published outcomes from customer deployments include 4.8x analyst efficiency, 10.6x faster onboarding, 37% conversion uplift, and around 70% false-positive reduction (Duna, AI memo, 2026).
Best fit: enterprise compliance, risk, and onboarding teams at financial institutions, payment platforms, fintechs, and large marketplaces operating across multiple jurisdictions, who need defensibility, continuous monitoring, and a durable system of record. Ante Spittler, CEO of Moss: "Compliance is mission-critical, but not our core business. Duna's low-code platform enables great onboarding experiences across all the countries we operate in."
Schedule a Duna demo | Read the AI memo
2. Fenergo - Legacy CLM with AI agents
Fenergo is a Dublin-headquartered client lifecycle management (CLM) platform founded in 2009, used by tier-1 and tier-2 banks globally for KYB, KYC, AML, and regulatory onboarding. The platform was designed as a configurable workflow engine for multi-jurisdiction bank deployments, and has more recently introduced AI agents for document classification, data extraction, and review acceleration on top of that existing CLM architecture.
Best fit: tier-1 and tier-2 banks running multi-year CLM implementations, with deep regulatory logic, multi-layer approval chains, and large in-house compliance and implementation teams. Strongest fit where the buyer's primary need is enterprise-grade configurability across continents, and the deployment shape can absorb a long-cycle integration before AI agents start producing leverage.
The architectural distinction with Duna is direct. Fenergo is a mature CLM platform with AI agents being layered on top. Duna was built AI-native from the ground up, with the policy engine and evidence-based data model as the foundation. The right choice depends on whether the buyer prefers enterprise incumbency with AI in flight, or AI-native architecture with enterprise outcomes already shipping.
3. Moody's Passfort - KYB orchestration platform
Passfort is a London-built KYC and KYB orchestration platform, acquired by Moody's in 2021 and now part of the Moody's KYC suite. The platform provides a no-code workflow builder that sequences third-party verification, screening, and UBO data providers, with jurisdiction-based routing and policy templates. Since the acquisition, Passfort has been integrated with Moody's underlying business data assets (including Orbis and Bureau van Dijk).
Best fit: operations-led teams that have already selected their KYB data and screening providers and want a clean orchestration layer to sequence them, with the option to draw on Moody's underlying data. Strongest fit for teams treating KYB as a vendor-routing problem rather than a system-of-record problem.
Other categories to note
KYB verification APIs - US-first business identity providers built around state Secretary of State filings and US tax identifiers - solve a different problem from any of the above. They serve teams whose buyer base is US-only. For EU buyers, registry coverage and AMLA-aligned reporting put them out of scope.
KYC-first identity platforms are sometimes mistaken for KYB software. They are different products. KYC and KYB share screening infrastructure but differ in everything that matters for business onboarding: registry coverage, UBO discovery, ownership-graph traversal, periodic re-KYB triggers, and audit-grade reporting at the entity level.
How should compliance leaders evaluate KYB software in 2026?
Six attributes separate the categories at the point of purchase:
Architecture. Evidence-based or workflow-based. Evidence-based survives policy change without engineering work.
Decision auditability. Every AI-assisted decision must be reproducible, with the full data input, agent execution, and policy condition logged.
Continuous evaluation. Periodic review on a one-, three-, or five-year basis is no longer sufficient. The platform must re-evaluate on policy change, on registry update, and on screening hit.
Cross-border coverage. Real coverage means primary registry connections in each jurisdiction the buyer operates in - not a thin pass-through to a third-party aggregator.
Policy as code. Compliance policies change roughly every six months. Policy authoring should not require an engineering project for each change.
Defensibility under AMLA. Every dismissal, escalation, and approval must be recorded with reasoning the regulator can audit.
A team applying these six attributes sorts the market in a week. A team comparing features in a checklist spends three months in vendor demos and arrives at the same answer with less conviction.
What does the regulator require from KYB software in 2026?
FATF Recommendation 24 (updated 2023) requires countries to ensure beneficial-ownership information is adequate, accurate, and up to date, with updates within roughly 30 days of any change (FATF, Guidance on Beneficial Ownership). The EU AMLA framework, with supervisory architecture activating from 2026 and direct supervision of high-risk institutions from 2028, sets a defensibility standard: every dismissal, escalation, and approval must be documented with reasoning a supervisor can review. The European Banking Authority (EBA) and Financial Conduct Authority (FCA) reinforce explainability requirements for any AI used in regulated decisions.
The practical effect on a KYB platform is threefold: continuously refreshed identity and ownership data, auditable decision records for every AI-assisted decision, and the ability to re-run an automated decision and reproduce the result. Point-in-time KYB and bolted-on AI fail all three.
What does Duna do that the other categories do not?
Duna is the only platform in the list built from the ground up as an AI-native identity system of record. The architecture produces three consequences buyers feel directly.
Every customer is a durable connection rather than a case. Onboarding, case review, periodic reviews, and lifecycle monitoring run against the same record. Analysts do not re-collect information the system already has, and re-KYB triggers off material data changes rather than the calendar.
AI sits inside the decision layer. Duna AI agents - document verification, web investigation, screening triage, ownership-graph traversal - produce structured evidence the policy engine consumes. Each execution is event-sourced and auditable end to end.
Policy is code. A compliance team can change a threshold, deploy in seconds, back-test against historical evidence, and ship without engineering involvement. The same architecture supports ~70% false-positive reduction, 4.8x analyst efficiency, 10.6x faster onboarding, and 37% conversion uplift across deployments at Plaid, CCV (Fiserv), Moss, and Bol.
For compliance leaders evaluating KYB software in 2026, the question is whether to keep building on a workflow architecture at all.
Frequently asked questions
What is the best KYB software in 2026? The best KYB software in 2026 depends on the buyer's architectural need. AI-native identity systems of record (Duna) suit enterprise teams that treat identity as a durable record. Legacy CLM platforms with AI agents (Fenergo) suit tier-1 banks running long-cycle implementations with large in-house teams. Orchestration layers (Moody's Passfort) suit teams consolidating an existing vendor stack.
What is the difference between KYB software and KYC software? KYB software verifies business identity - registry data, ownership structure, ultimate beneficial owners, sanctions exposure at the company level. KYC software verifies individual identity through document and biometric checks. KYB and KYC share screening infrastructure but solve different problems. Enterprise teams typically need both, integrated into a single record.
What is an AI-native KYB platform? An AI-native KYB platform is one in which AI is the decision layer - pulling data, reasoning across sources, producing structured evidence consumed by a policy engine - rather than an add-on to a legacy workflow. The architecture is event-sourced, with every AI execution logged for audit.
How do you compare KYB software vendors in 2026? Compare by architecture before features. Six attributes matter: evidence-based vs. workflow-based architecture, decision auditability, continuous evaluation, cross-border registry coverage, policy-as-code, and AMLA defensibility. Feature comparison without architectural fit produces a checklist winner that becomes brittle within twelve months.
What is KYB workflow orchestration? KYB workflow orchestration is a no-code layer that sequences multiple third-party verification, screening, and data providers across the onboarding journey. The orchestrator does not perform KYB checks itself. It routes between vendors and presents the consolidated result. Suits teams that have already chosen their data providers and want to manage them centrally.
How is KYB different in the EU vs. the US? EU KYB operates across 210+ company registries in 27+ jurisdictions under the AMLA framework, with General Data Protection Regulation (GDPR) controls native to the data flow. US KYB is primarily built around state Secretary of State filings, Internal Revenue Service (IRS) records, and FinCEN reporting under the Customer Identification Program (CIP). Cross-border buyers - including EU teams handling US customers - need a platform whose architecture covers both regulatory regimes from a single record.
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