Transform your business data into valuable insights

In the modern business landscape, where data reigns supreme, companies are on a continuous quest to leverage AI's transformative power. From uncovering hidden patterns to optimizing workflows and enhancing decision-making, AI offers a versatile toolkit for every step of the data journey. By understanding AI's diverse capabilities and their practical applications in various business scenarios, organizations can fully harness the potential of this game-changing technology.

Figure 1: The four general categories of generative AI use cases.

AI is revolutionizing creativity and productivity by generating innovative content, code, and human-like language. For example, Oracle's Select AI empowers users to effortlessly create SQL syntax from natural language queries. Meanwhile, Natural Language Generation (NLG) enables automated report creation, personalized content like customized sales emails, and conversational AI interfaces that simplify access to complex corporate systems.

By harnessing AI's generative prowess, businesses can streamline workflows, elevate personalization, and unlock new levels of efficiency. A prime example is the integration of generative AI with Retrieval-Augmented Generation (RAG), which transforms corporate search. Instead of manually combing through endless files, employees can use natural language queries to instantly retrieve and generate precise answers, as illustrated in the following gif.

Grow Your Revenue Faster with AI for Finance

AI is demonstrating that it is far more than a trendy technology. It is one of those rare breakthroughs, akin to the internet and cloud computing, with the potential to transform the business landscape. For CFOs and their teams, this advancement has arrived at a most opportune moment.

A constant challenge for finance leaders is to grow revenue while expanding margins. Achieving this necessitates running businesses more efficiently and utilizing technologies like AI to identify growth opportunities and uncover inefficiencies.

Looking ahead to the future of finance, Hiperdist envisions a significant transformation in the finance function. Although AI is unlikely to completely replace finance team members, it is expected to become an integral part of their daily activities.

1. Financial Forecasting and Planning
   AI is revolutionizing the financial forecasting and planning process through predictive analytics, which employs data, statistical algorithms, and machine learning to forecast future outcomes by analyzing historical data and current trends.
   
   Using predictive analytics, finance teams can project future cash flows using both historical company data and industry-wide data. Unlike traditional financial forecasts that require manual adjustments when circumstances change, AI-driven forecasts can recalibrate based on new data, ensuring forecasts and plans remain accurate and relevant. Generative AI can also automatically generate contextual commentary to explain forecasts and highlight key factors driving the predictions.
   
   
2. Regulatory Compliance
   With the increasing complexity of regulatory compliance worldwide, the cost and resource burden of regulatory reporting has surged in recent years. Organizations allocate significant time and resources to meet these requirements. AI can alleviate some of this workload by automating compliance monitoring, audit trail management, and regulatory report creation.
   
   Natural language processing (NLP) is particularly valuable in regulatory compliance. NLP, a branch of AI, enables computers to understand and generate human language. It can swiftly parse large amounts of textual data, transforming raw text or speech into meaningful insights. NLP can analyze lengthy documents, contracts, policies, and other text sources to extract critical information, identify pertinent changes, and highlight potential compliance risks. Additionally, NLP can enhance document management by automatically classifying documents based on predetermined criteria.
   
   
3. Cash Flow Optimization
   Effective cash flow management is a top priority for CFOs and their teams, and AI is proving to be an invaluable tool in this area. Due to the vast amounts of data involved, most finance professionals require more than a day to build a consolidated view of their cash and liquidity, and even then, forecasts can contain errors and become quickly outdated.
   
   By leveraging predictive analytics and machine learning, companies can automatically compile data from all relevant sources—both historical and current—to continuously predict future cash flows. With faster and more accurate cash flow forecasting, companies can make proactive decisions to maintain healthy liquidity levels. For example, if there is excess cash, they can take advantage of early payment discounts with suppliers or identify opportunities for reinvestment in the business. When cash is tight, they can reassess loan positions or trigger foreign exchange transfers between subsidiaries. Finance teams might also use AI to optimize working capital by applying the right early payment incentives to select suppliers based on market conditions, payment history, and other factors.
   
   

4. Expense Management
   Expense management can quickly become a source of frustration. For employees, adhering to expense policy rules by manually collecting receipts, filling out forms, and submitting expense reports is arduous and prone to errors. Finance teams also struggle to manually review every expense to ensure compliance. AI offers a powerful solution to streamline expense management and reduce its complexity.

   For instance, optical character recognition (OCR)—a form of AI that scans handwritten, printed, or image text, extracts relevant information, and digitizes it—can assist with receipt processing and expense entry. OCR scans uploaded receipts and invoices, automatically populating expense report fields such as merchant name, date, and total amount.

   AI's role in expense management goes beyond OCR. Companies can use AI to automate approval workflows, flagging only those expenses that need the finance team's review based on predetermined rules, and fostering a "manage-by-exception" culture. AI-enabled expense assistants are also becoming more common, helping employees by automatically categorizing expenses, populating and filing the required documentation, and providing guidance on the company's compliance policy.

   
   
5. Task Automation
   One of the most common and impactful capabilities of AI is task automation. AI can automate numerous manual, time-consuming finance processes that previously inundated finance teams, including:
   
   Data Entry: Extracting and inputting relevant information from statements, invoices, receipts, and other financial documents into a company’s system.
   Invoice Capture and Processing: Scanning, reading, and digitizing paper invoices.
   Matching and Verification: Automatically comparing and matching invoices against corresponding purchase orders and delivery receipts.
   Payment Execution: Facilitating the payment process, including scheduling payments to optimize cash flow, selecting the preferred payment method, and executing payments automatically or with minimal human intervention.
   Reconciliation: Carrying out automated reconciliation processing by matching payment transactions with bank statements to verify that amounts and beneficiaries align.
   Account Code Combination Defaulting: Predicting and automatically defaulting segment values of the account code combination on non-PO accounts payable invoice lines.
   Financial Close Processes: Intelligent process automation (IPA) orchestrates the financial close, monitors task status across multiple systems, recommends new rules for ongoing automation, automatically initiates close processes as dependent tasks are completed, and updates the close calendar.
   The advanced automation of high-volume, repetitive, and mundane manual tasks brings numerous benefits, including time and cost savings, decreased errors, and higher employee satisfaction as finance staff can focus on more strategic, value-added tasks.
   
   
6. Financial reporting and analysis
   AI can automate and enhance various aspects of the financial reporting and analysis process. Initially, it can extract relevant financial information from multiple data sources. It then cleans and processes this data by identifying errors, inconsistencies, or missing values and notifying finance staff of areas needing attention.
   
   AI can subsequently use the cleaned data to generate financial statements, such as income statements, balance sheets, and cash flow statements, transforming the data into reports that highlight key performance indicators (KPIs), trends, and observations. It also assists with regulatory reporting by filling out necessary forms with data provided by the finance team for review and confirmation.
   
   Generative AI (GenAI) can produce narrative reports, providing context by combining financial statements and data with explanations. GenAI can even prepare first drafts of 10-Qs and 10-Ks, including footnotes and management discussion and analysis (MD&A).

Concluding thoughts

What can your business do now to prepare for increasing AI use over time? First, aggressively automate your processes to reduce transactional work. Second, train your staff so they have the skills to effectively interact with AI tools, building analytical capabilities that capitalize on the technology. Giving finance staff an increased understanding of AI will also be critical in ensuring the proper security, controls, and appropriate use of the technology.

Ready to harness the power of AI to revolutionize your financial operations, drive revenue growth, and make informed, data-driven decisions? Don't get left behind in this era of AI-powered finance.

Contact Hiperdist today to explore our cutting-edge storage solutions and discover how we can help you unlock the full potential of your financial data.

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