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New MIT Paper: Cut Finance Oversight Time by 40%: From Compliance to Budgeting

New MIT Paper: Cut Finance Oversight Time by 40%: From Compliance to Budgeting

Financial leaders today face a difficult balance. On one side is the familiar world of compliance with annual audits, quarterly reports, and reconciliations. On the other is a fast-moving reality of complex supply chains, volatile markets, and rapid capital flows. A recent academic paper highlights the growing tension between these two worlds. Traditional audit and planning processes are no longer enough to keep up.

The Core Challenge: Oversight Is Falling Behind

The paper highlights three major risks for finance teams:

  • Information Overload. The volume of financial and operational data overwhelms review processes. Risks are buried until it is too late.

  • Lagging Oversight. Audits and compliance checks remain backward-looking. Anomalies often appear only after they have distorted results.

  • Systemic Fragility. Complex reporting systems create space for both errors and manipulation. These issues are often uncovered slowly.

For Controllers and FP&A teams, these risks are not academic. They are daily challenges that undermine trust with executives, investors, and regulators. Markets punish uncertainty, and delays in oversight can quickly damage valuation.

Why This Matters for Controllers and FP&A

Controllers must ensure accuracy and compliance. FP&A must guide strategy with forecasts and plans. Both functions face the same obstacle: delayed insight.

  • Deloitte found that 70% of finance leaders rank manual reconciliations as their top time drain.

  • Gartner estimates that finance teams spend up to 40% of their time collecting and validating data instead of analyzing it.

  • Hackett Group benchmarks show that inaccurate or stale forecasts cost companies 6–8% of annual revenue.

Controllers often uncover irregularities after the fact. FP&A teams frequently base forecasts on incomplete data. Together, this widens the gap between compliance and foresight.

A Shift Toward Continuous Oversight

The paper calls for a new model of oversight. Finance must adopt what can be called dynamic assurance. Instead of static point-in-time reviews, oversight must be continuous.

  • Proactive Anomaly Detection. Reduce the time to uncover irregularities from weeks or months to hours or days.

  • Continuous AI-driven Forecasting. Stress-test assumptions quickly. Accenture reports this can cut planning cycles by 30 to 50 percent.

  • Integrated Intelligence. Connect oversight with operational data in real time. McKinsey finds this can increase forecast accuracy by 20 to 25 percent.

This evolution does not replace audits or compliance. It strengthens them with always-on intelligence and gives finance leaders more time to analyze and guide strategy.

Technology’s Role in Closing the Gap

Technology now delivers measurable improvements.

  • For Controllers, machine learning tools can reduce false positives in anomaly detection by up to 60 percent. This frees staff to focus on critical issues.

  • For FP&A, predictive analytics and rolling forecasts can shrink planning cycles from six weeks to two. At the same time, accuracy improves in volatile markets.

The payoff is clear. Faster detection means fewer surprises. More accurate forecasts mean better allocation of resources. Finance teams that move to continuous oversight earn credibility with executives, boards, and investors.


AuditFlow helps Controllers surface anomalies faster and with higher accuracy, turning weeks of review into hours of detection.
BudgetFlow gives FP&A leaders AI-powered forecasting and scenario analysis, cutting planning cycles and improving accuracy. Both tools support the shift the paper calls for. Finance can move beyond compliance and into foresight.


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Corporate Finance Blog

10 Tips for Agile Auditing and Budgeting in 2026

10 Tips for Agile Auditing and Budgeting in 2026

Actionable insights for to modernize Corporate Finance without creating chaos.

Executive Summary

  • Replace annual plans with rolling forecasts and scenario analysis for agility.
  • Centralize budget and audit data for a single source of truth.
  • Automate data integration and reconciliation to eliminate manual risk.
  • Make variance analysis a proactive discipline.
  • Increase awareness of operational drivers without assuming causality.
  • Leverage AI-powered audit coverage for stronger controls and risk detection.
  • Treat budgeting as a living process that adapts continuously to the business.

Dynamic, integrated processes in 2026

As the second half of 2025 progresses, finance leaders are already laying the groundwork for the 2026 budget process. This critical period is the ideal time for CFOs, controllers, and FP&A teams to move beyond outdated methods. The traditional model of static annual plans, disconnected data, and reactive audits is no longer sufficient to navigate market volatility and rising compliance demands.

This guide provides ten actionable tips designed to help you modernize your financial planning. By adopting rolling forecasts, centralizing data, and leveraging AI, you can build a more dynamic, integrated, and strategic budget process for 2026. Put these practices into motion now to reduce manual work, strengthen controls, and sharpen your company’s decision-making for the year ahead.

  1. Adopt Rolling Forecasts for Greater Agility
    Static annual budgets can quickly become outdated. Market changes like inflation shifts, demand surges, or supply disruptions can make them irrelevant. Rolling forecasts allow finance teams to adapt as conditions change. This flexibility improves resource allocation and supports faster, better-informed decisions.

  2. Create a Single Source of Truth (SSoT) for Financial Data
    Budgeting and auditing slow down when data is scattered across systems. Create one environment where actuals, forecasts, and audit results are stored and updated in real time. Connect your ERP, payroll, and GL feeds directly. This eliminates version control problems and ensures all stakeholders work from the same reliable numbers.
  1. Automate Data Collection and Reporting
    Manual data gathering wastes valuable time and increases errors. Direct integration from ERP, payroll, and GL systems into your planning and audit tools improves data accuracy. Real-time reporting allows for faster closes and frees analysts to focus on analysis instead of manual tasks.
  1. Start Simple, Then Expand Budget Reporting
    Too much complexity early in the process can discourage adoption. Begin with clear, high-level dashboards that focus on the most important metrics. Once teams are comfortable, add more detail and advanced reporting. This builds engagement and ensures data is actually used.
  1. Use AI to Handle Low-Impact Line Items, Focus Human Effort on Big Levers
    AI tools can quickly forecast most low-impact line items with accuracy. This saves your team hours of work on numbers that have little effect on results. The freed-up time can then be used to focus on the fewer, high-value items that drive revenue and cost outcomes. This targeted approach improves both speed and strategic impact.
  1. Make Variance Analysis a Weekly Discipline
    Waiting until the end of a quarter to review variances leads to missed opportunities. Weekly variance checks allow quicker interventions and better cost control. Over time, this cadence becomes a habit that strengthens financial discipline.
  1. Analyze External Drivers to Improve Forecast Accuracy
    Results are shaped by external forces such as commodity prices, exchange rates, interest rates, or competitor actions. These drivers should be tested, not assumed, to confirm their actual impact. Tools that merge external data with your financials can reveal which factors truly matter and how strong the link is. This avoids chasing noise and ensures budget and audit changes are based on evidence.

  2. Increase Awareness of Internal Drivers
    Budgets should reflect key internal factors that may influence results, such as labor hours, capacity, or seasonal demand patterns. These should be tested, not assumed, to verify their impact on performance. Linking internal metrics to financial outcomes with the right analytics helps focus attention on what truly drives change and avoid overestimating weak relationships.

  3. Integrate AI into Auditing and Forecasting for Full Coverage
    AI-powered audit tools can analyze all transactions, not just samples. They identify anomalies in real time and strengthen internal controls. On the planning side, AI forecasting instantly adjusts scenarios as new data becomes available. This gives finance leaders more control and faster insight.
  1. Make Budgeting Iterative, Not Annual
    Each budgeting cycle is a chance to improve. Capture lessons about what worked, what caused delays, and which assumptions missed the mark. Use this feedback to refine processes for the next cycle. Treat budgeting as a continuous capability that evolves with the business.

Confidently guide the business forward

The months before budget season are your opportunity to set the tone for the year ahead. By acting now, you can put in place the tools, processes, and habits that will make 2026 planning faster, more accurate, and more strategic. The goal is not just to get through the cycle. It is to turn budgeting and auditing into capabilities that actively guide the business forward.

If your team is looking to improve accuracy, reduce manual work, and surface insights sooner, it may be time to explore solutions that combine forecasting and audit automation in one workflow. The right approach will keep you in control while giving you the speed and confidence you need for the year ahead.

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Corporate Finance Blog

Rethinking Risk in Real Time, How AI Is Transforming Audit Processes

Rethinking Risk in Real Time, How AI Is Transforming Audit Processes

Financial audits look backward. They rely on samples and manual checks. Today, finance teams need real-time visibility and full data coverage. This is where intelligent process automation is changing everything.

AI tools now review every transaction, not just a few. They spot irregularities, compliance issues, and errors as they happen. This allows teams to respond quickly and reduce risk before problems grow.

The Journal of Accountancy reports that firms using audit automation are improving both speed and accuracy. AI helps auditors focus on what matters by flagging unusual patterns. This adds value without replacing people. It simply gives them better tools.

AuditFlow uses machine learning to track financial activity across systems. It catches things like duplicate payments or unusual timing in vendor transactions. Teams can act fast and stay in control.

Accounting, Organizations and Society also notes how audit automation supports stronger internal controls. Every action is logged and traceable. This makes audit prep easier and more transparent.

Audit teams that use automation shift from reaction to prevention. They spend less time digging through data and more time providing value-added services to their clients.

If you want to bring AI into your audit workflow, AuditFlow provides transaction-level analysis and learns from your data. This saves time and improves accuracy.