{"id":2084,"date":"2025-02-24T10:08:16","date_gmt":"2025-02-24T10:08:16","guid":{"rendered":"https:\/\/bixpert.hu\/blog\/why-use-artificial-intelligence-in-finance-too\/"},"modified":"2025-02-24T10:24:07","modified_gmt":"2025-02-24T10:24:07","slug":"why-use-ai-in-finance-too","status":"publish","type":"post","link":"https:\/\/bixpert.hu\/en\/blog\/why-use-ai-in-finance-too\/","title":{"rendered":"Why use artificial intelligence in finance (too)?"},"content":{"rendered":"\n

Finance teams are under pressure to become more efficient and incorporate more detailed data into financial planning. But they face constraints such as the time it takes to prepare data, the limitations of spreadsheets, and the lack of automation. <\/p>\n\n

AI can streamline massive amounts of data to reveal details that were previously unavailable. It can provide financial planning and analysis (FP&A) teams with insights they didn’t have before, and help them proactively manage the business, ultimately giving them greater confidence and accountability in the business. <\/p>\n\n

How can AI help?<\/strong><\/h3>\n\n

Once finance leaders are ready to invest in AI, what\u2019s the most profitable place to start?<\/p>\n\n

Revenue forecasting<\/strong><\/h4>\n\n

AI adds depth and accuracy to forecast predictions while accelerating the pace at which FP&A professionals can edit and update forecasts based on data changes.<\/p>\n\n

AI can improve the finance organization’s data by combining financial and CRM data with field and business unit insights. This allows finance to collaborate with the business to create a more accurate plan. With AI, finance can perform statistical analysis on internal historical data and connect to key factors that could impact the forecast. <\/p>\n\n

Customer churn predictions<\/strong><\/h4>\n\n

AI analyzes vast amounts of historical data, including external and operational factors, to cluster customers and understand which drivers impact customer churn the most.<\/p>\n\n

AI can analyze historical data to cluster customers and understand which factors have the greatest impact on customer churn, while also incorporating third-party data (e.g., customer service interactions and escalations, common topics addressed, changes in company revenue) to identify trends. With these predictions as a starting point, finance organizations can provide insights to customer-facing teams in time to implement mitigation strategies for at-risk customers or promote best practices learned from the most loyal customers. <\/p>\n\n

Cashflow forecasting<\/strong><\/h4>\n\n

AI can analyze and clean large datasets and surface information to indicate which drivers are likely to have the greatest impact on cashflow.<\/p>\n\n

AI can analyze and cleanse large data sets to surface information such as customers who don’t pay on time, special payment terms, and customer mix. With data like this at their fingertips, the FP&A function is fully equipped to confidently advise on capital expenditures, investments, or expansion plans. The team will be able to predict with greater accuracy scenarios such as how many customers will pay late, early, on time, etc., providing confidence in decision making. <\/p>\n\n

Workforce planning<\/strong><\/h4>\n\n

AI can review data on employee characteristics and correlate those plans with upcoming projects to help finance professionals identify potential gaps in staffing or training.<\/p>\n\n

AI can synthesize large data sets on skills, attrition rates, or certifications, and connect these plans with upcoming projects. AI can help identify gaps for finance professionals to review and recommend hiring and training actions to ensure the organization is well-prepared. Even if finance has provided this guidance in the past, AI ensures that it will be deeper and more accurate. <\/p>\n\n

Summary<\/strong><\/h3>\n\n

Management demands greater speed and accuracy in forecasting and reporting. Historically, it has been difficult to process data and derive insights at the scale and speed at which markets change. <\/p>\n\n

AI removes conscious and unconscious bias from analysis and can accelerate the summarization of complex data and present options for humans to exercise judgment and make more informed decisions. Actionable AI solutions improve collaboration across the organization and free up analyst time for higher value activities. <\/p>\n\n

AI is at the heart of the Jedox platform, making finance teams smarter in all aspects of planning and performance management. Contact<\/a> us to explore the power of Jedox and its AI solutions! <\/p>\n\n

(source: https:\/\/www.jedox.com\/en\/resources\/ebook-ai-in-fpa\/<\/em><\/a>)<\/p>\n","protected":false},"excerpt":{"rendered":"

Finance teams are under pressure to become more efficient and incorporate more detailed data into financial planning. But they face constraints such as the time it takes to prepare data, the limitations of spreadsheets, and the lack of automation. AI can streamline massive amounts of data to reveal details that were previously unavailable. It can […]<\/p>\n","protected":false},"author":25,"featured_media":2082,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[4],"tags":[],"class_list":["post-2084","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"acf":[],"yoast_head":"\nWhy use artificial intelligence in finance (too)? - Bixpert | Munk\u00e1ra fogjuk adatait<\/title>\n<meta name=\"description\" content=\"In the coming years, artificial intelligence will transform finance teams by making them more strategic. With AI, FP&A teams may be able to spend most of their time generating insights instead of preparing data. 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