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AI for Finance

AI is turning finance from backward-looking reporting into real-time forecasting, control, and research.

Sound familiar?

These are the problems AI can solve for finance businesses this week — not next quarter.

Earnings calls take hours to distill

You listened to a 90-minute call. Now you need to pull out the 5 things that matter for your thesis. Your notes are scattered.

AI extracts key metrics, guidance changes, and management commentary from earnings transcripts — organized by what matters.

Free step-by-step tutorial

Use AI To Summarize Earnings Calls

About 5 minutes. Turns a 90-minute process into a 10-minute review.

Client reports are the same template with new numbers

You update the portfolio numbers in the same Word doc every quarter. The narrative hasn’t changed in 3 quarters. Clients notice.

AI generates personalized portfolio narratives — performance context, allocation rationale, and market commentary specific to each client.

Free step-by-step tutorial

Use AI To Personalize Client Reports

About 10 minutes per client. Gets faster as it learns your style.

Model documentation is always "I’ll do it later"

Your financial model works. You know what the assumptions are. Nobody else does. When you’re out, nobody can use it.

AI reads your model and generates assumption narratives, methodology notes, and a documentation page — so the model outlives your memory.

Free step-by-step tutorial

Use AI To Document Models

About 15 minutes for a full model. Well worth the bus factor reduction.

Get Started in Minutes

Four steps. No consultants. No multi-week rollout.

1

Pick your AI

2

Download it

3

Grab your skills

4

Start working

Start Setup

Detailed Setup Guides

Pick your AI assistant and follow a step-by-step guide built for finance.

Finance AI Skills Toolkit

16 ready-to-use AI skills, prompts, and a knowledge base built specifically for finance. Clone it, point your AI assistant at it, and start getting real work done with Claude or ChatGPT.

16 industry skills Knowledge base~445+ min saved

What’s in this toolkit

13-Week Cash Flow Forecaster~2 hr/forecast cycle

Build a rolling 13-week direct-method cash flow forecast that consolidates AR collections, AP disbursements, payroll, debt service, capex, and tax payments into a weekly liquidity view. Output includes opening-to-closing cash reconciliation, minimum-cash-cushion tracking, variance commentary versus prior forecast, and early warnings for covenant or liquidity stress.

Budget Variance Analyzer~25 min/analysis

Compare actual financial performance against budgeted targets, identify material variances, explain root causes, and recommend corrective actions. Produces narratives suitable for management reporting and board presentations.

Comparable Company Analysis~60 min/comp set

Build a peer-group trading-multiples analysis ("public comps") that frames where a target company trades relative to its cohort on revenue, EBITDA, earnings, and growth-adjusted multiples. Produces a clean comp set, a multiples table with central tendency statistics, and a defensible implied valuation range.

DCF Valuation Builder~90 min/valuation

Produce a defensible discounted cash-flow valuation from a target's historical financials, management guidance, and comparable market inputs. Output includes an explicit free-cash-flow build, WACC derivation, terminal-value treatment, sensitivity grid, and a per-share (or enterprise-value) implied range with commentary on the primary valuation drivers.

Earnings Call Summarizer~20 min/call

Extract key financial metrics, guidance revisions, management commentary themes, and analyst concerns from earnings call transcripts. Produces structured summaries suitable for investment research, portfolio monitoring, or internal briefings.

Financial Model Documenter~20 min/model

Write clear, structured documentation for existing financial models — covering assumptions, methodology, data sources, sensitivities, and limitations. Produces documentation suitable for model audit, team onboarding, investment committee review, or regulatory compliance.

Investment Memo Drafter~45 min/memo

Structure deal notes, research, and financial data into a formatted investment memorandum with a clear thesis, risk assessment, valuation summary, and comparable analysis. Produces memos suitable for investment committee review, partner distribution, or client presentation.

Market Research Brief~30 min/brief

Compile a structured sector or sub-industry brief that sizes the market, maps the competitive landscape, catalogs recent transactions and capital flows, surfaces regulatory and macro catalysts, and synthesizes 3–5 actionable investment or strategic implications. Produces a brief suitable for coverage initiations, deal-sourcing memos, pre-meeting prep, and pitch-book appendices.

Stress-Test Scenario Modeler~30 min/scenario

Model downside financial scenarios — market corrections, revenue shortfalls, interest rate shocks, client attrition — and quantify their impact on portfolios, cash flow, or business performance. Identifies vulnerability points and suggests mitigation strategies.

Advisor Meeting Prep~25 min/meeting

Prepare financial advisors for client and prospect meetings by organizing key data points, generating tailored talking points, anticipating client questions, and creating a structured agenda. Reduces prep time and ensures no critical topics are missed.

Client Portfolio Update~15 min/update

Draft a clear, compliant, client-ready portfolio update that covers period performance, allocation and positioning changes, benchmark context, contributions and withdrawals, and forward outlook. Produces a narrative that an advisor can review, personalize, and send without rewriting it from scratch — with the disclosures and tone required for client-facing wealth-management communications.

Tax-Loss Harvesting Identifier~30 min/account

Scan a client's taxable portfolio for positions trading below cost basis, identify candidate harvest trades that realize losses without triggering wash-sale rules, and propose replacement securities that maintain target exposure. Output includes a ranked harvest list, lot-level tax impact, wash-sale guardrails, and a compliant reinvestment plan.

Regulatory Filing Checker~25 min/filing

Review a draft regulatory filing against the requirements for its specific form, flag missing or inconsistent disclosures, cross-check internal consistency (numbers, dates, counterparties), and produce a reviewer checklist with severity ratings and suggested remediation language. Covers the most common SEC, FINRA, state, and international filings encountered in RIA, broker-dealer, fund, and corporate-finance workflows. Output is decision-support for a compliance officer, CCO, or filing specialist — not a substitute for legal review.

Email Drafter~10 min/use

Turn rough notes into a professional email matching your company's voice and tone.

Meeting Summarizer~10 min/use

Summarize meeting notes into action items, decisions, and follow-ups.

Review Responder~10 min/use

Craft professional responses to online reviews — both positive and negative.

Auto-synced from KRASA-AI/finance-ai-skills. Updated daily.

Free Step-by-Step Tutorials

Each workflow takes minutes, not months. Pick one and start.

1

Use AI To Summarize Earnings Calls

About 5 minutes. Turns a 90-minute process into a 10-minute review.

  1. 1

    Download Claude or ChatGPT and open the Earnings Call Summarizer skill

  2. 2

    Paste the earnings call transcript (most are available on SeekingAlpha or the company’s IR page)

  3. 3

    AI generates a summary: revenue/EPS vs. consensus, guidance changes, key management quotes, risk callouts, and segment highlights

  4. 4

    Review the summary, flag what matters for your coverage, and move to the next name on your list

2

Use AI To Personalize Client Reports

About 10 minutes per client. Gets faster as it learns your style.

  1. 1

    Open the Client Portfolio Update skill

  2. 2

    Input the client’s portfolio: holdings, returns for the period, benchmark comparison, any changes made

  3. 3

    Add context: "Client is 62, conservative growth, worried about inflation, asked about gold last quarter"

  4. 4

    AI generates a narrative that explains performance, addresses their concerns, and frames next steps — specific to them, not boilerplate

3

Use AI To Document Models

About 15 minutes for a full model. Well worth the bus factor reduction.

  1. 1

    Open the Financial Model Documenter skill

  2. 2

    Paste or describe the key tabs: revenue build, cost assumptions, WACC inputs, sensitivity ranges

  3. 3

    AI generates documentation: assumption descriptions, data sources, methodology notes, and a change log template

  4. 4

    Attach as a cover sheet or separate tab — now anyone can understand and update the model

Real-World Use Cases

AI cash forecasting for treasury

Treasury teams are using AI to predict cash positions, compare forecasts to actuals, and surface the drivers behind misses. This replaces one of the most manual recurring finance jobs: reconciling cash views across banks, entities, and planning models.

Tools:

Bank of America CashPro ForecastingGTreasury

Impact:

Bank of America said CashPro Forecasting helped 3,000+ companies save more than 250,000 hours in 2025; results arrive in minutes instead of days.

Source: Bank of America / The Asian Banker coverage, 2025, GTreasury treasury AI article, 2026

Investment research and due diligence compression

Buy-side and corporate development teams are using AI search to scan filings, transcripts, expert calls, broker notes, and news, then jump directly to the relevant paragraph. The job changes from document retrieval to thesis testing.

Tools:

AlphaSense

Impact:

AlphaSense says a $50B AUM fund cut research time by 75% while improving output quality.

Source: AlphaSense case study, 2025

Advisor enablement in wealth management

Wealth teams are using AI copilots to retrieve research faster, summarize complex market moves, and prep client responses during volatile periods. The practical win is more advisor time for client conversations and less time spent hunting for internal content.

Tools:

Morgan Stanley internal advisor AIJPMorgan Coach AI

Impact:

Morgan Stanley said AI could save financial advisors 10-15 hours per week; JPMorgan said AI helped support faster service and expects advisors to expand client loads by 50% within five years.

Source: Reuters, June 2024 and May 2025

Management reporting and commentary drafting

FP&A teams are feeding monthly decks, BU notes, and actual-vs-plan exports into LLMs to produce first-pass variance summaries, executive commentary, and board-pack language. Humans still edit, but the blank page is gone.

Tools:

ChatGPTClaudeMicrosoft Copilot

Impact:

Practitioners in r/FPandA report using ChatGPT to consolidate monthly commentary; EY describes reporting workflows where AI cut manual workload by 60%.

Source: r/FPandA thread 'GPT use cases', 2026, EY FP&A report, 2025

Month-end close acceleration

Finance teams are using AI and workflow automation to handle reconciliations, report prep, and exception spotting so close work shifts from repetitive assembly to review. This is one of the clearest paths to measurable ROI because cycle time is easy to track.

Tools:

RilletDataSnipperChatGPT

Impact:

AidKit cut month-end close from 15 days to 4 days and saved 40-50 hours of manual work monthly.

Source: Rillet customer case study, 2025

Accounts payable and spend control automation

Finance ops teams are using AI to extract invoice data, match receipts, code spend, flag policy violations, and reduce manual follow-up. The immediate benefit is fewer touchpoints per invoice and cleaner close support.

Tools:

RampDataSnipper

Impact:

Ramp says 50,000+ businesses have saved 27.5 million hours; Concur reported more AP teams now spend under 10 hours per week processing invoices than a year earlier.

Source: Ramp G2 profile, 2026, SAP Concur AP automation trends, 2025

Natural-language querying of finance data

Teams are building internal copilots that let users ask plain-English questions like 'show legal expense for Q1 by department' instead of waiting for analyst turnaround. This is becoming the fastest way to widen access without handing everyone raw ERP tables.

Tools:

ChatGPT EnterpriseMicrosoft CopilotCube

Impact:

Gartner says knowledge management is now the most common finance AI use case at 49% among adopters.

Source: Gartner AI in Finance Survey, 2025, r/FPandA thread on custom ChatGPT for financial data, 2025

Scenario planning and rolling forecasts

Finance teams are using AI-assisted planning tools to run multiple scenarios faster, update assumptions in one place, and generate narrative around what changed. That matters most when demand, pricing, or working capital moves faster than a quarterly planning cycle.

Tools:

PigmentPlanfulVena

Impact:

BCG found the strongest finance AI ROI is showing up in risk and forecasting; Pigment users on G2 describe significant time savings from centralized scenario modeling.

Source: BCG finance AI ROI study, 2025, G2 Pigment reviews, 2026

Fraud detection and payment-risk monitoring

Banks and payments teams are using AI to score transactions in real time, spot synthetic identity patterns, and reduce false positives that frustrate customers. This is not experimental anymore; it is core operating infrastructure.

Tools:

FeedzaiMastercard Decision Intelligence

Impact:

Mastercard says AI is helping banks save millions by improving real-time fraud detection and approval decisions; Feedzai says more than half of fraud now involves AI or deepfakes.

Source: Mastercard insights, 2026, Feedzai fraud trends report, 2025

Excel model building and audit support

Practitioners are using AI to write formulas, refactor old models, document logic, and update yearly commission or planning calculators. In audit-heavy environments, AI inside Excel is also speeding up evidence extraction and tying workpapers back to source documents.

Tools:

Claude for ExcelDataSnipper

Impact:

r/FPandA users report rebuilding calculators and formula logic with Claude; DataSnipper says it delivered more than $1.4B in productivity savings across audit and finance workflows in 2025.

Source: r/FPandA 'How I've used Claude for Excel', 2026, G2 DataSnipper profile, 2026

Top AI Tools for Finance

Datarails

FP&A / Reporting

Spreadsheet-native FP&A and reporting platform used by finance teams that do not want to abandon Excel. Practitioners use it for consolidation, budgeting, cash visibility, month-end reporting, and AI-assisted insights without forcing a full workflow rewrite.

Contact for pricing

4.6

Ramp

Spend Management / AP Automation

Finance automation platform for expense management, cards, AP, procurement, and software spend. Finance teams use it to reduce receipt chasing, speed close, and get AI help on coding, policy checks, and vendor spend visibility.

Free plan available; paid tiers available

4.8

AlphaSense

Market Intelligence / Research

AI research platform for investment, strategy, and corporate finance teams. Used to search filings, earnings calls, broker research, expert interviews, and news, then summarize the relevant evidence fast enough to change how diligence actually gets done.

Contact for pricing

4.6

Pigment

Planning / Scenario Modeling

Modern planning platform for finance teams that need live scenario modeling, workforce planning, and cross-functional planning. Best for organizations moving beyond spreadsheet sprawl and wanting AI agents in planning workflows.

Contact for pricing

4.7

Vena

FP&A / Budgeting

Excel-first planning platform used for budgeting, forecasting, financial close, and reporting. A strong fit for finance teams that want structure, workflow, and collaboration while keeping spreadsheet familiarity.

Contact for pricing

4.5

Cube

FP&A / Financial Intelligence

AI-powered financial intelligence platform built around the spreadsheet habits finance teams already have. Useful for planning, reporting, and cross-functional reviews when you need fewer version-control problems and faster forecast cycles.

Starting at $32K annually

4.5

Planful

FP&A / Continuous Planning

Mature FP&A platform used for budgeting, continuous planning, close, and management reporting. Finance teams choose it when they need stronger workflow, data centralization, and enterprise controls than ad hoc spreadsheets can provide.

Contact for pricing

4.3

DataSnipper

Audit / Close Support

Excel-based intelligent automation for audit and finance teams. It is used for document matching, evidence extraction, reconciliation support, and faster workpaper preparation in controlled environments.

Contact for pricing

4.8

Frequently Asked Questions

People Are Searching For

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Recommended Reading

How finance teams are using ChatGPT for monthly commentary in 2026

Datarails vs Cube vs Vena: which AI-friendly FP&A stack fits your team?

What finance leaders should automate before they buy an enterprise AI platform

How to pilot AI in FP&A without breaking controls

7 finance workflows where Claude for Excel is already useful

What treasury teams can automate first with AI cash forecasting

How Ramp changes the close for lean finance teams

What AlphaSense actually replaces in the research workflow

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