90% faster analysis

AI Pension Liability Analyst Agent

From manual tracking to real-time insights

Delegate pension liability analysis to a specialized AI agent. It tracks funding status by comparing asset performance against actuarial liability tables, identifies funding gaps, and surfaces LDI opportunities, allowing your team to focus on strategic portfolio decisions.

Ideal for

Pension Fund Managers

LDI Specialists

Institutional Investors

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    Brotherhood Mutual logo
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    Paige logo
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See AI Pension Liability Analyst 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
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Mercedes-Benz logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI Pension Liability Analyst 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
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Mercedes-Benz logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI Pension Liability Analyst Agent in action

Play video

Quarterly Funding Status Review

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    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
    Mercedes-Benz logo
    Foobar logo
    ABL logo
    Mercedes-Benz logo
    Mercedes-Benz logo
    Brotherhood Mutual logo
    Mercedes-Benz logo
    Paige logo
    Roche logo
    Mercedes-Benz logo
    Sony logo
    Munch Energie Logo
    Certainty Sofrware logo
    Raft logo
    Bayer Logo
    Mercedes-Benz logo
    Mercedes-Benz logo

See AI Pension Liability Analyst Agent in action

Play video

Time comparison

Time comparison

Traditional way

3-5 days

With V7 Go agents

15-30 minutes

Average time saved

90%

Why V7 Go

Why V7 Go

Automated Funding Status Calculation

Instantly compares asset values against actuarial liability tables to calculate precise funding ratios, eliminating manual spreadsheet errors and delays.

Automated Funding Status Calculation

Instantly compares asset values against actuarial liability tables to calculate precise funding ratios, eliminating manual spreadsheet errors and delays.

Automated Funding Status Calculation

Instantly compares asset values against actuarial liability tables to calculate precise funding ratios, eliminating manual spreadsheet errors and delays.

Automated Funding Status Calculation

Instantly compares asset values against actuarial liability tables to calculate precise funding ratios, eliminating manual spreadsheet errors and delays.

Duration and Convexity Analysis

Identifies duration mismatches between assets and liabilities, surfacing opportunities to optimize your LDI portfolio positioning.

Duration and Convexity Analysis

Identifies duration mismatches between assets and liabilities, surfacing opportunities to optimize your LDI portfolio positioning.

Duration and Convexity Analysis

Identifies duration mismatches between assets and liabilities, surfacing opportunities to optimize your LDI portfolio positioning.

Duration and Convexity Analysis

Identifies duration mismatches between assets and liabilities, surfacing opportunities to optimize your LDI portfolio positioning.

Liability Projection Modeling

Projects future liability growth based on demographic assumptions and discount rate changes, enabling proactive funding strategy adjustments.

Liability Projection Modeling

Projects future liability growth based on demographic assumptions and discount rate changes, enabling proactive funding strategy adjustments.

Liability Projection Modeling

Projects future liability growth based on demographic assumptions and discount rate changes, enabling proactive funding strategy adjustments.

Liability Projection Modeling

Projects future liability growth based on demographic assumptions and discount rate changes, enabling proactive funding strategy adjustments.

Multi-Source Data Integration

Consolidates asset data from custodians, actuarial reports, and internal systems into a unified analysis, reducing reconciliation overhead.

Multi-Source Data Integration

Consolidates asset data from custodians, actuarial reports, and internal systems into a unified analysis, reducing reconciliation overhead.

Multi-Source Data Integration

Consolidates asset data from custodians, actuarial reports, and internal systems into a unified analysis, reducing reconciliation overhead.

Multi-Source Data Integration

Consolidates asset data from custodians, actuarial reports, and internal systems into a unified analysis, reducing reconciliation overhead.

Scenario and Sensitivity Testing

Automatically runs interest rate, inflation, and return scenarios to stress-test your funding position and validate hedging strategies.

Scenario and Sensitivity Testing

Automatically runs interest rate, inflation, and return scenarios to stress-test your funding position and validate hedging strategies.

Scenario and Sensitivity Testing

Automatically runs interest rate, inflation, and return scenarios to stress-test your funding position and validate hedging strategies.

Scenario and Sensitivity Testing

Automatically runs interest rate, inflation, and return scenarios to stress-test your funding position and validate hedging strategies.

Auditable Analysis Trail

Every calculation is traced back to source data with full documentation, creating a defensible record for auditors and regulators.

Auditable Analysis Trail

Every calculation is traced back to source data with full documentation, creating a defensible record for auditors and regulators.

Auditable Analysis Trail

Every calculation is traced back to source data with full documentation, creating a defensible record for auditors and regulators.

Auditable Analysis Trail

Every calculation is traced back to source data with full documentation, creating a defensible record for auditors and regulators.

Analyzes pension funding from multiple data sources

To deliver comprehensive liability-driven investment insights.

Get started

Get started

Logo
Logo
Logo

Import your files

Snowflake

,

Microsoft Excel

,

Tableau

Import your files from whereever they are currently stored

Customer voices

Customer voices

Connect AI to your pension strategy.

Connect AI to your pension strategy.

Join leading institutional investors automating liability analysis.

Join leading institutional investors automating liability analysis.

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

Features

Features

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

Results you can trust.
Trustworthy AI document processing toolkit.

Supporting complex financial data.

From multiple sources.

Pension data comes from diverse sources: custodian statements, actuarial reports, internal spreadsheets, and accounting systems. This agent consolidates all formats into a unified analysis, handling inconsistent data structures and legacy systems seamlessly.

Input types

Multi-source integration

Legacy systems

Complex tables

Real-time feeds

Document types

PDFs

Spreadsheets

Tables

API feeds

Database exports

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex financial data.

From multiple sources.

Pension data comes from diverse sources: custodian statements, actuarial reports, internal spreadsheets, and accounting systems. This agent consolidates all formats into a unified analysis, handling inconsistent data structures and legacy systems seamlessly.

Input types

Multi-source integration

Legacy systems

Complex tables

Real-time feeds

Document types

PDFs

Spreadsheets

Tables

API feeds

Database exports

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex financial data.

From multiple sources.

Pension data comes from diverse sources: custodian statements, actuarial reports, internal spreadsheets, and accounting systems. This agent consolidates all formats into a unified analysis, handling inconsistent data structures and legacy systems seamlessly.

Input types

Multi-source integration

Legacy systems

Complex tables

Real-time feeds

Document types

PDFs

Spreadsheets

Tables

API feeds

Database exports

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Reach 99% accuracy rate

through rigorous financial analysis.

Pension liability calculations demand precision. This agent uses multi-step validation workflows to ensure every funding ratio, liability projection, and duration calculation is accurate and audit-ready, eliminating the risk of costly errors.

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 rigorous financial analysis.

Pension liability calculations demand precision. This agent uses multi-step validation workflows to ensure every funding ratio, liability projection, and duration calculation is accurate and audit-ready, eliminating the risk of costly errors.

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 rigorous financial analysis.

Pension liability calculations demand precision. This agent uses multi-step validation workflows to ensure every funding ratio, liability projection, and duration calculation is accurate and audit-ready, eliminating the risk of costly errors.

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 source data.

Every funding calculation is traced back to its source data with complete documentation. This creates a defensible audit trail that satisfies regulators and auditors while giving your team confidence in every decision.

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 source data.

Every funding calculation is traced back to its source data with complete documentation. This creates a defensible audit trail that satisfies regulators and auditors while giving your team confidence in every decision.

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 source data.

Every funding calculation is traced back to its source data with complete documentation. This creates a defensible audit trail that satisfies regulators and auditors while giving your team confidence in every decision.

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 institutional investors.

Pension data is highly sensitive and subject to strict regulatory oversight. V7 Go processes all fund information within your secure environment, adhering to institutional-grade security standards and data privacy requirements.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for institutional investors.

Pension data is highly sensitive and subject to strict regulatory oversight. V7 Go processes all fund information within your secure environment, adhering to institutional-grade security standards and data privacy requirements.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for institutional investors.

Pension data is highly sensitive and subject to strict regulatory oversight. V7 Go processes all fund information within your secure environment, adhering to institutional-grade security standards and data privacy requirements.

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 Pension Liability Analyst Agent

How does the agent handle different actuarial methodologies?

The agent is configured to work with your specific actuarial assumptions, discount rate methodology, and liability calculation approach. It adapts to PBO, ABO, or custom liability definitions your plan uses.

+

How does the agent handle different actuarial methodologies?

The agent is configured to work with your specific actuarial assumptions, discount rate methodology, and liability calculation approach. It adapts to PBO, ABO, or custom liability definitions your plan uses.

+

How does the agent handle different actuarial methodologies?

The agent is configured to work with your specific actuarial assumptions, discount rate methodology, and liability calculation approach. It adapts to PBO, ABO, or custom liability definitions your plan uses.

+

Can it integrate with our custodian data feeds?

Yes. The agent connects to major custodian platforms and can ingest asset data directly from your existing systems, eliminating manual data entry and ensuring real-time accuracy.

+

Can it integrate with our custodian data feeds?

Yes. The agent connects to major custodian platforms and can ingest asset data directly from your existing systems, eliminating manual data entry and ensuring real-time accuracy.

+

Can it integrate with our custodian data feeds?

Yes. The agent connects to major custodian platforms and can ingest asset data directly from your existing systems, eliminating manual data entry and ensuring real-time accuracy.

+

How frequently can we run funding status updates?

The agent can run analysis daily, weekly, or on any custom schedule. This enables real-time monitoring of funding status and immediate identification of significant market-driven changes.

+

How frequently can we run funding status updates?

The agent can run analysis daily, weekly, or on any custom schedule. This enables real-time monitoring of funding status and immediate identification of significant market-driven changes.

+

How frequently can we run funding status updates?

The agent can run analysis daily, weekly, or on any custom schedule. This enables real-time monitoring of funding status and immediate identification of significant market-driven changes.

+

Does it support multiple plan structures?

Absolutely. The agent handles single-plan analysis, multi-plan consolidation, and cross-plan comparisons, making it suitable for sponsors managing multiple defined benefit plans.

+

Does it support multiple plan structures?

Absolutely. The agent handles single-plan analysis, multi-plan consolidation, and cross-plan comparisons, making it suitable for sponsors managing multiple defined benefit plans.

+

Does it support multiple plan structures?

Absolutely. The agent handles single-plan analysis, multi-plan consolidation, and cross-plan comparisons, making it suitable for sponsors managing multiple defined benefit plans.

+

How does it handle liability assumption changes?

When actuarial assumptions change, you update the agent's configuration with new discount rates, mortality tables, or demographic assumptions. It immediately recalculates funding status using the new parameters.

+

How does it handle liability assumption changes?

When actuarial assumptions change, you update the agent's configuration with new discount rates, mortality tables, or demographic assumptions. It immediately recalculates funding status using the new parameters.

+

How does it handle liability assumption changes?

When actuarial assumptions change, you update the agent's configuration with new discount rates, mortality tables, or demographic assumptions. It immediately recalculates funding status using the new parameters.

+

Is the analysis compliant with accounting standards?

Yes. The agent's calculations align with ASC 715 (pension accounting) and GASB standards, ensuring your analysis is audit-ready and compliant with financial reporting requirements.

+

Is the analysis compliant with accounting standards?

Yes. The agent's calculations align with ASC 715 (pension accounting) and GASB standards, ensuring your analysis is audit-ready and compliant with financial reporting requirements.

+

Is the analysis compliant with accounting standards?

Yes. The agent's calculations align with ASC 715 (pension accounting) and GASB standards, ensuring your analysis is audit-ready and compliant with financial reporting requirements.

+

Next steps

Next steps

Still reconciling pension data manually?

Send us your latest fund data and actuarial assumptions. We'll show you how to get real-time funding status analysis in minutes.

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: