90% faster reporting
AI agent for Regulatory Reporting Analysts
From weeks of field mapping to hours
Delegate regulatory field mapping to a specialized AI agent. It reads your internal transaction data, maps fields to Basel III and Dodd-Frank requirements, validates data lineage, and generates submission-ready reports with complete audit trails.
Ideal for
Regulatory Reporting
Compliance Teams
Risk Management
See AI agent for Regulatory Reporting Analysts in action
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See AI agent for Regulatory Reporting Analysts in action
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See AI agent for Regulatory Reporting Analysts in action
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Q3 Basel III Submission
See AI agent for Regulatory Reporting Analysts in action
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Time comparison
Time comparison
Traditional way
2-3 weeks per submission
With V7 Go agents
4-6 hours
Average time saved
90%
Why V7 Go
Why V7 Go
Automated Field Mapping
Reads internal transaction data and automatically maps fields to Basel III, Dodd-Frank, or other regulatory schemas, eliminating manual reconciliation work.
Automated Field Mapping
Reads internal transaction data and automatically maps fields to Basel III, Dodd-Frank, or other regulatory schemas, eliminating manual reconciliation work.
Automated Field Mapping
Reads internal transaction data and automatically maps fields to Basel III, Dodd-Frank, or other regulatory schemas, eliminating manual reconciliation work.
Automated Field Mapping
Reads internal transaction data and automatically maps fields to Basel III, Dodd-Frank, or other regulatory schemas, eliminating manual reconciliation work.
Data Lineage Validation
Traces every mapped field back to its source system and transaction, creating a complete audit trail that satisfies regulatory examination requirements.
Data Lineage Validation
Traces every mapped field back to its source system and transaction, creating a complete audit trail that satisfies regulatory examination requirements.
Data Lineage Validation
Traces every mapped field back to its source system and transaction, creating a complete audit trail that satisfies regulatory examination requirements.
Data Lineage Validation
Traces every mapped field back to its source system and transaction, creating a complete audit trail that satisfies regulatory examination requirements.
Schema Change Detection
Identifies when internal data schemas change and flags fields requiring remapping, preventing submission errors from outdated field definitions.
Schema Change Detection
Identifies when internal data schemas change and flags fields requiring remapping, preventing submission errors from outdated field definitions.
Schema Change Detection
Identifies when internal data schemas change and flags fields requiring remapping, preventing submission errors from outdated field definitions.
Schema Change Detection
Identifies when internal data schemas change and flags fields requiring remapping, preventing submission errors from outdated field definitions.
Multi-Jurisdiction Support
Handles regulatory requirements across jurisdictions, mapping the same transaction data to different reporting standards for global institutions.
Multi-Jurisdiction Support
Handles regulatory requirements across jurisdictions, mapping the same transaction data to different reporting standards for global institutions.
Multi-Jurisdiction Support
Handles regulatory requirements across jurisdictions, mapping the same transaction data to different reporting standards for global institutions.
Multi-Jurisdiction Support
Handles regulatory requirements across jurisdictions, mapping the same transaction data to different reporting standards for global institutions.
Exception Flagging
Identifies transactions that cannot be automatically mapped due to ambiguous codes or missing data, routing them to analysts for manual classification.
Exception Flagging
Identifies transactions that cannot be automatically mapped due to ambiguous codes or missing data, routing them to analysts for manual classification.
Exception Flagging
Identifies transactions that cannot be automatically mapped due to ambiguous codes or missing data, routing them to analysts for manual classification.
Exception Flagging
Identifies transactions that cannot be automatically mapped due to ambiguous codes or missing data, routing them to analysts for manual classification.
Submission File Generation
Produces submission-ready files in the exact format required by regulators, including all mandatory fields, validation checks, and data quality controls.
Submission File Generation
Produces submission-ready files in the exact format required by regulators, including all mandatory fields, validation checks, and data quality controls.
Submission File Generation
Produces submission-ready files in the exact format required by regulators, including all mandatory fields, validation checks, and data quality controls.
Submission File Generation
Produces submission-ready files in the exact format required by regulators, including all mandatory fields, validation checks, and data quality controls.
Maps transaction data to regulatory schemas
For accurate, auditable government filings.
Get started
Get started
Import your files
Snowflake
,
Microsoft SQL Server
,
Microsoft Excel
Import your files from whereever they are currently stored
All types of Finance documents supported
Once imported our system extracts and organises the essentials
Customer voices
Customer voices
Connect AI to your regulatory framework.
Connect AI to your regulatory framework.
Turn field mapping into an automated, auditable process.
Turn field mapping into an automated, auditable process.
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Customer Voices
Industrial equipment sales
We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.
Read the full story
Industrial equipment sales
We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.
Read the full story
Insurance
We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.
Read the full story
Insurance
We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.
Read the full story
Real Estate
Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.
Read the full story
Real Estate
Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.
Read the full story
Industrial equipment sales
We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.
Read the full story
Insurance
We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.
Read the full story
Real Estate
Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.
Read the full story
Finance
“Whenever I think about hiring, I first try to do it in V7 Go.” Discover how HITICCO uses V7 Go agents to accelerate and enrich their prospect research.
Read the full story
Finance
The experience with V7 has been fantastic. Very customized level of support. You feel like they really care about your outcome and objectives.
Read the full story
Features
Features
Results you can actually trust.
Reliable AI document processing toolkit.
Results you can trust.
Trustworthy AI document processing toolkit.
Supporting complex data formats.
From any source system.
Regulatory data comes from multiple core systems with different schemas. This agent handles transaction files from any source, whether they're CSV exports, database queries, or legacy system outputs, and maps them to regulatory requirements.
Input types
Multi-System Sources
Schema Variations
Legacy Formats
Multi-modal
Document types
CSV Files
Database Exports
Complex Tables
XML Files
Spreadsheets
Vendor_US.xlsx
3
Supply_2023.pptx
Review_Legal.pdf
Supporting complex data formats.
From any source system.
Regulatory data comes from multiple core systems with different schemas. This agent handles transaction files from any source, whether they're CSV exports, database queries, or legacy system outputs, and maps them to regulatory requirements.
Input types
Multi-System Sources
Schema Variations
Legacy Formats
Multi-modal
Document types
CSV Files
Database Exports
Complex Tables
XML Files
Spreadsheets
Vendor_US.xlsx
3
Supply_2023.pptx
Review_Legal.pdf
Supporting complex data formats.
From any source system.
Regulatory data comes from multiple core systems with different schemas. This agent handles transaction files from any source, whether they're CSV exports, database queries, or legacy system outputs, and maps them to regulatory requirements.
Input types
Multi-System Sources
Schema Variations
Legacy Formats
Multi-modal
Document types
CSV Files
Database Exports
Complex Tables
XML Files
Spreadsheets
Vendor_US.xlsx
3
Supply_2023.pptx
Review_Legal.pdf
Reach 99% accuracy rate
through GenAI reasoning.
Regulatory submissions demand perfect accuracy. The agent uses multi-step validation workflows to ensure every mapped field is correct, every calculation is precise, and every data point can be traced to its source transaction.
Model providers
Security note
V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.
Answer
Type
Text
Tool
o4 Mini
Reasoning effort
Min
Low
Mid
High
AI Citations
Inputs
Set a prompt (Press @ to mention an input)
Reach 99% accuracy rate
through GenAI reasoning.
Regulatory submissions demand perfect accuracy. The agent uses multi-step validation workflows to ensure every mapped field is correct, every calculation is precise, and every data point can be traced to its source transaction.
Model providers
Security note
V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.
Answer
Type
Text
Tool
o4 Mini
Reasoning effort
Min
Low
Mid
High
AI Citations
Inputs
Set a prompt (Press @ to mention an input)
Reach 99% accuracy rate
through GenAI reasoning.
Regulatory submissions demand perfect accuracy. The agent uses multi-step validation workflows to ensure every mapped field is correct, every calculation is precise, and every data point can be traced to its source transaction.
Model providers
Security note
V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.
Answer
Type
Text
Tool
o4 Mini
Reasoning effort
Min
Low
Mid
High
AI Citations
Inputs
Set a prompt (Press @ to mention an input)
Trustworthy results,
grounded in reality.
Every mapped field is linked to its source transaction with complete data lineage. Regulators can trace any reported value back through the mapping logic to the original system of record, creating a defensible audit trail.
Visual grounding in action
00:54
Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.
Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.
Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.
Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.
Prior Warning and Ignoring Compliance
![](data:image/svg+xml,<svg display="block" role="presentation" viewBox="0 0 198 15" xmlns="http://www.w3.org/2000/svg"><defs ><clipPath id="J0QEw1Ctk-2037569988-stroke"><use href="%23J0QEw1Ctk-2037569988"/></clipPath><path d="M 0 1 C 0 0.448 0.448 0 1 0 L 197 0 C 197.552 0 198 0.448 198 1 L 198 9 C 198 9.552 197.552 10 197 10 L 76 10 L 76 14 C 76 14.552 75.552 15 75 15 L 1 15 C 0.448 15 0 14.552 0 14 Z" id="J0QEw1Ctk-2037569988"/></defs><use fill="rgba(124, 58, 237, 0.1)" height="15px" href="%23J0QEw1Ctk-2037569988" id="J0QEw1Ctk" width="198px"/><use clip-path="url(%23J0QEw1Ctk-2037569988-stroke)" fill="transparent" href="%23J0QEw1Ctk-2037569988" stroke-dasharray="0" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="4" stroke-width="1" stroke="rgb(124, 58, 237)"/></svg>)
02
01
01
02
Trustworthy results,
grounded in reality.
Every mapped field is linked to its source transaction with complete data lineage. Regulators can trace any reported value back through the mapping logic to the original system of record, creating a defensible audit trail.
Visual grounding in action
00:54
Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.
Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.
Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.
Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.
Prior Warning and Ignoring Compliance
02
01
01
02
Trustworthy results,
grounded in reality.
Every mapped field is linked to its source transaction with complete data lineage. Regulators can trace any reported value back through the mapping logic to the original system of record, creating a defensible audit trail.
Visual grounding in action
00:54
Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.
Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.
Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.
Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.
Prior Warning and Ignoring Compliance
02
01
01
02
Enterprise grade security
for high-stake industries.
Regulatory data contains sensitive financial information subject to strict data governance requirements. V7 Go processes all transaction data within your secure environment, ensuring compliance with data residency and privacy regulations.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise grade security
for high-stake industries.
Regulatory data contains sensitive financial information subject to strict data governance requirements. V7 Go processes all transaction data within your secure environment, ensuring compliance with data residency and privacy regulations.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise grade security
for high-stake industries.
Regulatory data contains sensitive financial information subject to strict data governance requirements. V7 Go processes all transaction data within your secure environment, ensuring compliance with data residency and privacy regulations.
Certifications
GPDR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
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Answers
Answers
What you need to know about our
AI agent for Regulatory Reporting Analysts
How does the agent handle changes to regulatory schemas?
The agent connects to your regulatory Knowledge Hub, which contains the latest field definitions and mapping rules. When regulators update schemas, you update the Hub, and the agent automatically applies new mappings to future submissions.
+
How does the agent handle changes to regulatory schemas?
The agent connects to your regulatory Knowledge Hub, which contains the latest field definitions and mapping rules. When regulators update schemas, you update the Hub, and the agent automatically applies new mappings to future submissions.
+
How does the agent handle changes to regulatory schemas?
The agent connects to your regulatory Knowledge Hub, which contains the latest field definitions and mapping rules. When regulators update schemas, you update the Hub, and the agent automatically applies new mappings to future submissions.
+
Can it map data from multiple source systems?
Yes. The agent reads transaction data from multiple core banking systems, trading platforms, and risk databases, consolidating them into a single regulatory view with complete data lineage.
+
Can it map data from multiple source systems?
Yes. The agent reads transaction data from multiple core banking systems, trading platforms, and risk databases, consolidating them into a single regulatory view with complete data lineage.
+
Can it map data from multiple source systems?
Yes. The agent reads transaction data from multiple core banking systems, trading platforms, and risk databases, consolidating them into a single regulatory view with complete data lineage.
+
What happens when a transaction cannot be automatically mapped?
The agent flags ambiguous records and routes them to your compliance team with context about why automatic mapping failed. Analysts review these exceptions and provide the correct classification, which the agent learns from for future submissions.
+
What happens when a transaction cannot be automatically mapped?
The agent flags ambiguous records and routes them to your compliance team with context about why automatic mapping failed. Analysts review these exceptions and provide the correct classification, which the agent learns from for future submissions.
+
What happens when a transaction cannot be automatically mapped?
The agent flags ambiguous records and routes them to your compliance team with context about why automatic mapping failed. Analysts review these exceptions and provide the correct classification, which the agent learns from for future submissions.
+
How does it ensure data accuracy for regulatory submissions?
The agent validates every mapped field against regulatory business rules, performs cross-field consistency checks, and links each data point to its source transaction. This creates an auditable trail that regulators can verify during examinations.
+
How does it ensure data accuracy for regulatory submissions?
The agent validates every mapped field against regulatory business rules, performs cross-field consistency checks, and links each data point to its source transaction. This creates an auditable trail that regulators can verify during examinations.
+
How does it ensure data accuracy for regulatory submissions?
The agent validates every mapped field against regulatory business rules, performs cross-field consistency checks, and links each data point to its source transaction. This creates an auditable trail that regulators can verify during examinations.
+
Does it support both Basel III and Dodd-Frank reporting?
Yes. The agent can map the same internal transaction data to multiple regulatory frameworks simultaneously, ensuring consistency across different submission requirements.
+
Does it support both Basel III and Dodd-Frank reporting?
Yes. The agent can map the same internal transaction data to multiple regulatory frameworks simultaneously, ensuring consistency across different submission requirements.
+
Does it support both Basel III and Dodd-Frank reporting?
Yes. The agent can map the same internal transaction data to multiple regulatory frameworks simultaneously, ensuring consistency across different submission requirements.
+
What is the final output format?
The agent generates submission files in the exact format required by your regulator, whether that's XML for Basel III, CSV for Dodd-Frank, or custom formats for other jurisdictions. All files include validation reports and data quality metrics.
+
What is the final output format?
The agent generates submission files in the exact format required by your regulator, whether that's XML for Basel III, CSV for Dodd-Frank, or custom formats for other jurisdictions. All files include validation reports and data quality metrics.
+
What is the final output format?
The agent generates submission files in the exact format required by your regulator, whether that's XML for Basel III, CSV for Dodd-Frank, or custom formats for other jurisdictions. All files include validation reports and data quality metrics.
+
Next steps
Next steps
Still mapping regulatory fields manually every quarter?
Send us a sample transaction file and your regulatory template. We'll show you how the agent maps fields, validates data lineage, and generates submission files automatically.
Uncover hidden liabilities
in
supplier contracts.
V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:
Uncover hidden liabilities
in
supplier contracts.
V7 Go transforms documents into strategic assets. 150+ enterprises are already on board: