Finance groups are under constant pressure to close the books faster, forecast with greater accuracy, and provide insights that guide strategic decisions. At the same time, they are often weighed down by manual processes, complex reconciliations, and scattered data. Artificial intelligence offers a way to reduce that burden by automating routine work, improving accuracy, and freeing finance professionals to focus on higher value activities.

Automating the Close Process

One of the most time consuming tasks for finance teams is the month end or quarter end close. Gathering numbers from multiple systems, reconciling accounts, and ensuring accuracy can take weeks. AI can streamline this process by pulling data automatically from ERP systems, flagging anomalies for review, and preparing reconciliations. Instead of spending long hours on manual checks, finance professionals can review exceptions and finalize reports in a fraction of the time.

Improving Forecasting and Scenario Planning

Traditional forecasting often relies on static models or spreadsheets that are updated periodically. AI can analyze historical financial data along with external indicators such as market trends or customer behavior to create dynamic forecasts. These models adapt as new data arrives, producing more accurate projections. Finance teams can also run scenarios quickly, such as testing the impact of a sales slowdown or a change in supply chain costs, and deliver valuable insights to leadership.

Streamlining Expense Management

Expense data often comes from different sources and requires hours of classification and review. AI can automatically categorize expenses, detect unusual transactions, and prepare summaries for reporting. This reduces errors, supports compliance, and makes audits easier. For staff, it removes one of the more repetitive aspects of finance work and ensures information is ready for analysis more quickly.

Enhancing Reporting and Analysis

Management and board reporting can take significant effort each month. AI can assemble data from multiple systems, generate draft dashboards, and even create written summaries that highlight key variances. Finance leaders can then refine and add context, saving hours of manual compilation. This turns reporting from a data gathering exercise into a strategic communication tool.

Supporting Compliance and Risk Management

AI can also support compliance functions by monitoring transactions against established rules, flagging potential issues for review, and maintaining an audit trail. For companies operating in regulated industries, this reduces the risk of oversight and gives compliance teams a powerful tool to stay ahead of requirements.

A Practical Example

At New Clarity, we have seen these opportunities firsthand. One example is the creation of a custom Model Context Protocol server built for a fractional CFO. The system connected to an LLM and automated the transfer of data between spreadsheets. By intelligently mapping fields and reducing manual work, it saved hours each week and eliminated a source of recurring errors. This project illustrates how even highly specific finance workflows can benefit from carefully designed AI solutions.

“The enhancement built directly into Claude desktop is used to manipulate our spreadsheets to build financial models from P&L statements and other documents. This has saved me countless hours of time I would have otherwise spent doing manual entry, so now I can now allocate that time to more valuable work.”

– Rob K, Fractional CFO

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Why New Clarity

Optimizing finance teams is not about chasing every new tool. It is about focusing on the tasks that consume the most time and carry the highest risk of error. At New Clarity, we work with companies to identify those areas, design AI solutions that directly address them, and provide support to ensure adoption. The result is a finance function that operates more efficiently, delivers better insights, and has the capacity to focus on strategic priorities.

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