90% faster data extraction

AI Actuarial Analysis Agent

From weeks of data gathering to hours of analysis

Delegate the data extraction phase to a specialized AI agent. It reads financial statements, claims reports, policy documents, and regulatory filings to pull mortality rates, claims frequencies, policy counts, and other actuarial metrics. Your team gets clean, structured data ready for modeling—freeing actuaries to focus on assumptions and valuations.

Ideal for

Actuarial Teams

Risk Management

Insurance Operations

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See AI Actuarial Analysis Agent in action

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    Paige logo
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See AI Actuarial Analysis Agent in action

Play video

  • Mercedes-Benz logo
    SMC  logo
    Mercedes-Benz logo
    Centerline logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Alaris logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Sony logo
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    Bayer Logo
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See AI Actuarial Analysis Agent in action

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Pension Plan Valuation Data Extraction

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    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
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See AI Actuarial Analysis Agent in action

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Time comparison

Time comparison

Traditional way

3-4 weeks

With V7 Go agents

4-8 hours

Average time saved

90%

Why V7 Go

Why V7 Go

Automated Mortality & Claims Extraction

Pulls mortality rates, claims frequencies, claim amounts, and policy counts from financial statements, claims reports, and regulatory filings into structured, analysis-ready formats.

Automated Mortality & Claims Extraction

Pulls mortality rates, claims frequencies, claim amounts, and policy counts from financial statements, claims reports, and regulatory filings into structured, analysis-ready formats.

Automated Mortality & Claims Extraction

Pulls mortality rates, claims frequencies, claim amounts, and policy counts from financial statements, claims reports, and regulatory filings into structured, analysis-ready formats.

Automated Mortality & Claims Extraction

Pulls mortality rates, claims frequencies, claim amounts, and policy counts from financial statements, claims reports, and regulatory filings into structured, analysis-ready formats.

Multi-Source Data Consolidation

Gathers actuarial data from disparate sources—PDFs, spreadsheets, legacy systems, regulatory documents—and normalizes it into a single, consistent dataset for modeling.

Multi-Source Data Consolidation

Gathers actuarial data from disparate sources—PDFs, spreadsheets, legacy systems, regulatory documents—and normalizes it into a single, consistent dataset for modeling.

Multi-Source Data Consolidation

Gathers actuarial data from disparate sources—PDFs, spreadsheets, legacy systems, regulatory documents—and normalizes it into a single, consistent dataset for modeling.

Multi-Source Data Consolidation

Gathers actuarial data from disparate sources—PDFs, spreadsheets, legacy systems, regulatory documents—and normalizes it into a single, consistent dataset for modeling.

Policy & Coverage Detail Parsing

Extracts policy-level details including coverage types, benefit limits, deductibles, and rider information from complex policy documents and schedules.

Policy & Coverage Detail Parsing

Extracts policy-level details including coverage types, benefit limits, deductibles, and rider information from complex policy documents and schedules.

Policy & Coverage Detail Parsing

Extracts policy-level details including coverage types, benefit limits, deductibles, and rider information from complex policy documents and schedules.

Policy & Coverage Detail Parsing

Extracts policy-level details including coverage types, benefit limits, deductibles, and rider information from complex policy documents and schedules.

Historical Trend Analysis

Processes multi-year financial and claims data to identify trends in mortality, morbidity, lapse rates, and expense ratios for assumption-setting.

Historical Trend Analysis

Processes multi-year financial and claims data to identify trends in mortality, morbidity, lapse rates, and expense ratios for assumption-setting.

Historical Trend Analysis

Processes multi-year financial and claims data to identify trends in mortality, morbidity, lapse rates, and expense ratios for assumption-setting.

Historical Trend Analysis

Processes multi-year financial and claims data to identify trends in mortality, morbidity, lapse rates, and expense ratios for assumption-setting.

Regulatory Compliance Data

Extracts required regulatory metrics and disclosures from 10-K filings, statutory statements, and compliance reports to support audit and filing requirements.

Regulatory Compliance Data

Extracts required regulatory metrics and disclosures from 10-K filings, statutory statements, and compliance reports to support audit and filing requirements.

Regulatory Compliance Data

Extracts required regulatory metrics and disclosures from 10-K filings, statutory statements, and compliance reports to support audit and filing requirements.

Regulatory Compliance Data

Extracts required regulatory metrics and disclosures from 10-K filings, statutory statements, and compliance reports to support audit and filing requirements.

Verifiable Data Lineage

Every extracted data point is linked back to its source document with AI Citations, creating a complete audit trail for valuation support and regulatory review.

Verifiable Data Lineage

Every extracted data point is linked back to its source document with AI Citations, creating a complete audit trail for valuation support and regulatory review.

Verifiable Data Lineage

Every extracted data point is linked back to its source document with AI Citations, creating a complete audit trail for valuation support and regulatory review.

Verifiable Data Lineage

Every extracted data point is linked back to its source document with AI Citations, creating a complete audit trail for valuation support and regulatory review.

Extracts actuarial data from any source

To accelerate your valuation and modeling work.

Get started

Get started

Import your files

Microsoft Sharepoint Online

,

Microsoft Excel

,

Snowflake

Import your files from whereever they are currently stored

Customer voices

Customer voices

Connect AI to your actuarial process.

Connect AI to your actuarial process.

Free your team from data extraction.

Free your team from data extraction.

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Customer Voices

Features

Features

Results you can actually trust.
Reliable AI document processing toolkit.

Results you can trust.
Trustworthy AI document processing toolkit.

Supporting complex documents.

Up to 200 pages.

Actuarial data lives in many formats. This agent handles financial statements, claims reports, policy schedules, regulatory filings, and legacy system exports. It extracts structured data regardless of document layout or source system.

Input types

Complex Tables

Multi-Year Data

200 pages

Legacy Formats

Document types

PDFs

Spreadsheets

Tables

Scanned Documents

Data Exports

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Actuarial data lives in many formats. This agent handles financial statements, claims reports, policy schedules, regulatory filings, and legacy system exports. It extracts structured data regardless of document layout or source system.

Input types

Complex Tables

Multi-Year Data

200 pages

Legacy Formats

Document types

PDFs

Spreadsheets

Tables

Scanned Documents

Data Exports

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Actuarial data lives in many formats. This agent handles financial statements, claims reports, policy schedules, regulatory filings, and legacy system exports. It extracts structured data regardless of document layout or source system.

Input types

Complex Tables

Multi-Year Data

200 pages

Legacy Formats

Document types

PDFs

Spreadsheets

Tables

Scanned Documents

Data Exports

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Reach 99% accuracy rate

through GenAI reasoning.

Actuarial work demands precision. This agent uses multi-step validation to ensure mortality rates, claim counts, and policy data are extracted with exceptional accuracy, ready for modeling without manual correction.

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.

Actuarial work demands precision. This agent uses multi-step validation to ensure mortality rates, claim counts, and policy data are extracted with exceptional accuracy, ready for modeling without manual correction.

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.

Actuarial work demands precision. This agent uses multi-step validation to ensure mortality rates, claim counts, and policy data are extracted with exceptional accuracy, ready for modeling without manual correction.

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 extracted data point is visually linked back to its source document. This creates a complete audit trail for valuation support, regulatory review, and peer review—eliminating ambiguity about data origins.

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 extracted data point is visually linked back to its source document. This creates a complete audit trail for valuation support, regulatory review, and peer review—eliminating ambiguity about data origins.

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 extracted data point is visually linked back to its source document. This creates a complete audit trail for valuation support, regulatory review, and peer review—eliminating ambiguity about data origins.

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.

Actuarial data includes sensitive policyholder and financial information. V7 Go processes all data within your secure environment with encryption and compliance controls for HIPAA, GLBA, and regulatory standards.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Actuarial data includes sensitive policyholder and financial information. V7 Go processes all data within your secure environment with encryption and compliance controls for HIPAA, GLBA, and regulatory standards.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Actuarial data includes sensitive policyholder and financial information. V7 Go processes all data within your secure environment with encryption and compliance controls for HIPAA, GLBA, and regulatory standards.

Certifications

GPDR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

More agents

More agents

Explore more agents to help you

Explore more agents to help you

accelerate your insurance and risk workflows

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Answers

Answers

What you need to know about our

AI Actuarial Analysis Agent

How accurate is the data extraction for actuarial work?

The agent achieves high accuracy through multi-step validation workflows that cross-reference data across documents. Every extracted figure is visually linked to its source, allowing actuaries to verify critical assumptions before modeling.

+

How accurate is the data extraction for actuarial work?

The agent achieves high accuracy through multi-step validation workflows that cross-reference data across documents. Every extracted figure is visually linked to its source, allowing actuaries to verify critical assumptions before modeling.

+

How accurate is the data extraction for actuarial work?

The agent achieves high accuracy through multi-step validation workflows that cross-reference data across documents. Every extracted figure is visually linked to its source, allowing actuaries to verify critical assumptions before modeling.

+

Can it handle legacy systems and non-standard formats?

Yes. The agent processes PDFs, scanned documents, spreadsheets, and data exports from legacy systems. It adapts to varying document structures and formats common in insurance operations.

+

Can it handle legacy systems and non-standard formats?

Yes. The agent processes PDFs, scanned documents, spreadsheets, and data exports from legacy systems. It adapts to varying document structures and formats common in insurance operations.

+

Can it handle legacy systems and non-standard formats?

Yes. The agent processes PDFs, scanned documents, spreadsheets, and data exports from legacy systems. It adapts to varying document structures and formats common in insurance operations.

+

How does it handle confidential policyholder data?

V7 Go processes all data within your secure environment with enterprise-grade encryption. The platform adheres to HIPAA, GLBA, and other regulatory standards for sensitive insurance data.

+

How does it handle confidential policyholder data?

V7 Go processes all data within your secure environment with enterprise-grade encryption. The platform adheres to HIPAA, GLBA, and other regulatory standards for sensitive insurance data.

+

How does it handle confidential policyholder data?

V7 Go processes all data within your secure environment with enterprise-grade encryption. The platform adheres to HIPAA, GLBA, and other regulatory standards for sensitive insurance data.

+

What output formats does the agent provide?

The agent delivers structured outputs in JSON, CSV, or Excel formats. Data can be customized to populate your actuarial modeling software, valuation systems, or internal databases.

+

What output formats does the agent provide?

The agent delivers structured outputs in JSON, CSV, or Excel formats. Data can be customized to populate your actuarial modeling software, valuation systems, or internal databases.

+

What output formats does the agent provide?

The agent delivers structured outputs in JSON, CSV, or Excel formats. Data can be customized to populate your actuarial modeling software, valuation systems, or internal databases.

+

Can it extract data for different product lines simultaneously?

Absolutely. The agent processes multiple product lines, segments, and business units in parallel, consolidating results into a unified dataset for comparative analysis.

+

Can it extract data for different product lines simultaneously?

Absolutely. The agent processes multiple product lines, segments, and business units in parallel, consolidating results into a unified dataset for comparative analysis.

+

Can it extract data for different product lines simultaneously?

Absolutely. The agent processes multiple product lines, segments, and business units in parallel, consolidating results into a unified dataset for comparative analysis.

+

How does this compare to manual data entry?

Manual extraction is slow and error-prone. The agent completes in hours what takes actuaries weeks, with fewer transcription errors and complete source documentation for audit purposes.

+

How does this compare to manual data entry?

Manual extraction is slow and error-prone. The agent completes in hours what takes actuaries weeks, with fewer transcription errors and complete source documentation for audit purposes.

+

How does this compare to manual data entry?

Manual extraction is slow and error-prone. The agent completes in hours what takes actuaries weeks, with fewer transcription errors and complete source documentation for audit purposes.

+

Next steps

Next steps

Still manually extracting actuarial data?

Send us a sample financial statement or claims report. We'll show you how our agent extracts the data you need in hours, not weeks.

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Centerline logo
    Alaris logo

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Centerline logo
    Alaris logo