Given that 80% of small businesses go under due to cash flow problems, getting this right is crucial<\/em>. And better cash flow = getting to continue doing the work that I love.<\/p>\n To learn more about the tech\u2019s potential, I spoke to several experts across various industries (from finance to ecommerce) to see how they are integrating AI into their forecasting methods and what tips you can learn from their experience.<\/p>\n Table of Contents<\/strong><\/p>\n You probably already know that AI can save you time and money running your business \u2014 but how exactly can it help you better forecast your cash flow?<\/p>\n To answer this, I should first explain what cash flow forecasting is and some common challenges you might face using traditional methods.<\/p>\n <\/a> <\/p>\n Back in time before AI, cash flow forecasting meant gathering data from different systems, updating spreadsheets, and making educated guesses about when customers might pay. It\u2019s manual, time-consuming, and often inaccurate.<\/p>\n Manual forecasting suffered from siloed data, outdated information, calculation errors, and missed seasonal patterns. Teams wasted hours on basic analysis that was outdated before it was complete.<\/p>\n Now, imagine having a system that automatically pulls data from all your sources, learns your customers\u2018 payment patterns, and alerts you to potential cash shortages before they happen. That\u2019s what AI brings to the table.<\/p>\n While traditional forecasting<\/a> might tell you to expect $100,000 in payments next month based on historical averages, AI can tell you things like:<\/p>\n P.S. If you\u2019re looking to brush up on your forecasting skills, I recommend checking out these free courses in HubSpot Academy: Forecasting and Analytics in Sales Hub<\/a> and Hubspot Sales Forecasting.<\/a><\/p>\n <\/a> <\/p>\n Traditional cash flow forecasting can be tedious and error-prone, but AI is solving this problem.<\/p>\n \u201cAI reduces the time spent collecting and entering data, and it can create more accurate forecasts by taking into account unexpected events and current economic conditions, which can be difficult to capture through traditional forecasting,” explains Jim Pendergast<\/a>, General Manager of altLINE<\/a>.<\/p>\n The power of AI lies in its ability to uncover hidden patterns in financial data that might escape human eyes. (And why spend your time poring over detailed spreadsheets if you don\u2019t have<\/em> to?)<\/p>\n Alex Schlesinger<\/a>, Founder and CEO of Active Mutual<\/a>, a final expense insurance business, shares a compelling example. His team noticed that many of their senior clients would receive their Social Security payments on the third Wednesday of each month. \u201cIn the past, we\u2019d roughly estimate that \u2018yeah business might pick up around then.\u2019<\/p>\n \u201cOur model picked up that not only do sales increase two days after Social Security payments, but specifically, they spike between 10 AM and 2 PM on those days,\u201d Schlesinger explained.<\/p>\n \u201cThat kind of accuracy means we can plan everything better \u2014 from marketing budgets to commission payouts,\u201d Schlesinger added. \u201cPlus it’s way cheaper than it used to be.\u201d<\/p>\n Modern businesses generate vast amounts of data across various systems and departments. AI’s ability to synthesize these diverse data streams sets it apart in cash flow forecasting.<\/p>\n Craig J. Lewis<\/a>, Founder and CEO of Gig Wage<\/a>, emphasizes that \u201cAI has introduced predictive algorithms that significantly enhance both the speed and accuracy of cash flow forecasting by processing large datasets in real-time.\u201d<\/p>\n Here are some data sources that can be integrated by AI:<\/p>\n Roy Benesh<\/a>, CTO of eSIMple<\/a>, contrasts this with traditional methods: \u201cWhen we use traditional forecasting, it depends on past data and people’s judgments collected over time, but AI pulls in different data from many sources like supply chain changes and market trends that provide optimized answers now.\u201d<\/p>\n Benesh shared with me examples of what that looks like for two different industries. Take manufacturing as an example. With AI, you can pull in real-time data from supply chains, inventory, and revenue streams to get a clearer financial picture. Retail companies, who rely on maintaining an accurate level of inventory, can also rely on this real-time data to keep updated predictions.<\/p>\n Check out HubSpot\u2019s Forecasting Software.<\/a><\/em><\/strong><\/p>\n <\/a> <\/p>\n Testing out AI doesn\u2019t have to be overwhelming. I\u2018ve talked with several business owners who\u2019ve successfully made the transition, and they all share a common approach: start small, stay focused, and build gradually.<\/p>\n Don’t try to revolutionize your entire financial system overnight. Pick one area \u2014 maybe customer payment predictions \u2014 and start there.<\/p>\n Lewis from Gig Wage recommends you \u201cpinpoint the areas where you think optimization is needed and work with AI in those areas to see how you like the results.\u201d<\/p>\n Begin with one specific project \u27a1\ufe0fset clear success metrics.<\/p>\n Maybe you want to reduce the time spent on forecasting by 50% or improve accuracy by 25%. Having these concrete goals will help you measure progress and build confidence in the system.<\/p>\n AI shouldn’t be something you solely depend on. As Benesh explained to me, \u201cHuman oversight and frequent checks against actual cash flow data are still key to staying accurate.\u201d<\/p>\n \u201cThere’s a myth that this approach \u2018just works\u2019 on its own, but it needs regular attention, especially in unpredictable markets,\u201d he added.<\/p>\n Lewis echoes this advice, \u201cIf the present looks like the past, then AI will do a strong job in minimizing forecasting errors. This is broadly useful because during these periods AI will outperform humans. If there is a significant deviation from the data on which the model is trained, the model will mismanage cash. I think it\u2019s important to know what a computer is good at and what humans are good at so that you mitigate risk to the highest extent possible.\u201d<\/p>\n \u201cTraditional methods, though slower, allow seasoned analysts to apply judgment and context that algorithms alone may miss \u2014 there is still somewhat of a tradeoff,\u201d adds Lewis.<\/p>\n I like thinking of it like having both a GPS and a local guide. The GPS (AI) provides precise, data-driven directions, but the local guide (human expertise) knows about the road construction that started yesterday. You need both for the best results.<\/p>\n Lewis\u2019s last bit of advice? \u201cBe incremental. Pinpoint the areas where you think optimization is needed and work with AI in those areas to see how you like the results. This simplifies the transition and allows people to adapt to the new tools. AI is fundamentally a tool that helps with optimization. I think it would be much harder to implement from the get-go.\u201d<\/p>\n <\/a> <\/p>\n What is it? <\/strong>HighRadius offers a cash flow forecasting software that\u2019s powered by AI and has a 95% forecast accuracy rate. This tool is designed to optimize liquidity management by leveraging AI to provide deep insights into cash inflows and outflows.<\/p>\n Source<\/a><\/em><\/p>\n Key Features<\/strong><\/p>\n Best for<\/strong>: Mid-sized to large enterprises with complex cash flow needs, looking for high accuracy in their cash flow predictions and real-time updates.<\/p>\n What is it?<\/strong> Oracle Cloud Enterprise Performance Management (EPM) Platform is a suite of cloud-based financial software tools that helps businesses manage their planning, budgeting, forecasting, and reporting processes. It integrates with other Oracle financial tools, making it a great option for managing your overall financial performance.<\/p>\n Key Features<\/strong><\/p>\n Best for: <\/strong>Large enterprises that already use Oracle products.<\/p>\n What is it?<\/strong> Kyriba is a cloud-based cash management platform focused on improving cash visibility and liquidity management. Its AI cash flow forecasting feature helps businesses predict and control their cash flow needs.<\/p>\n Key Features<\/strong><\/p>\n Best for: <\/strong>Multinational corporations or businesses with high-volume cash flow activity across multiple currencies and accounts.<\/p>\n What is it? <\/strong>Planful is a financial planning and analysis platform that incorporates AI-based anomaly detection and predictive forecasting to aid cash flow forecasting. I found that the platform is quite easy to use and that it integrates well with other financial tools.<\/p>\n![\"\u2192](\"https:\/\/no-cache.hubspot.com\/cta\/default\/53\/e27057af-294d-4698-af4f-2f3cdb57b71f.png\")
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Why Use AI for Cash Flow Forecasting?<\/h2>\n
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How AI Changes Cash Flow Forecasting: The Old Way vs. The New Way<\/h2>\n
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How AI Can Improve Cash Flow Forecasting<\/h2>\n
AI improves the accuracy and speed of cash flow forecasting.<\/strong><\/h3>\n
AI excels at identifying complex patterns that humans might miss.<\/strong><\/h3>\n
AI integrates multiple data sources for comprehensive forecasting.<\/strong><\/h3>\n
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<\/p>\nImplementation Guide: Tips for Using AI in Cash Flow Forecasting<\/strong><\/h2>\n
1. Start with small pilot projects before scaling.<\/strong><\/h3>\n
2. Maintain human oversight and expertise alongside AI tools.<\/strong><\/h3>\n
3. Blend with traditional methods.<\/strong><\/h3>\n
4. Start small \u2014 and focus on quality over quantity.<\/strong><\/h3>\n
Tools for AI Cash Flow Forecasting<\/h2>\n
1. HighRadius<\/a><\/h3>\n
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2. Oracle Cloud EPM<\/a><\/h3>\n
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3. Kyriba<\/a><\/h3>\n
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4. Planful<\/a><\/h3>\n
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