Financial reporting with AI: A new era of decision-ready insights

If your team is still wrestling with spreadsheets or using outdated analytics tools for financial reporting, chances are you are missing out on real insights, opportunities, and risks that can cost you big bucks.  

The good news is AI can change this.  

AI in financial reporting can turn around the entire process of financial reporting, surfacing hidden risks, compliance gaps, and even suggesting corrective actions before issues escalate.  

With AI integrated into the reporting process, you can have sharper visibility into your company’s financial health, more clarity on what needs to be done and when, and most importantly, the confidence that every decision you are making is based on deep, intelligent insights.  

This blog will take you through the current challenges of financial reporting and how AI adoption can bring a significant transformation.  

The current challenges in financial reporting 

The process of financial reporting is often challenging, especially when there is manual work involved and frequent inconsistencies in the analysis. Here’s a closer look at some of the key challenges that are often witnessed in financial reporting. 

Hard to believe, but there are still organizations where the process of reporting is done manually using spreadsheets.  From compiling data to validating entries and formatting the reports, the entire cycle can take days or even weeks, leaving little time for teams to go into deep analysis. This also puts significant pressure on the finance teams to meet internal and regulatory deadlines. Besides, there is also a possibility of errors and inaccuracies, and even distorted processes, when doing things manually.  

2. Lack of real-time visibility 

A major problem with traditional financial reporting is that it lacks real-time visibility into the concerned areas of your business. By the time reports are prepared and distributed, data is often outdated. This means the leadership is not equipped with the latest insights to respond swiftly to emerging risks or capitalize on new opportunities.  

For centralized financial analysis, data sources should be well-integrated. The problem arises when your teams have to tap into each source separately to fetch the required data. It’s both time-consuming and exhausting, affecting the entire process of creating reports and conducting analysis. Not to forget the errors that are likely to come up due to the manual system of extracting data. 

4. Data accuracy and quality 

Inadequate data accuracy and quality is another issue that often comes in the way of financial reporting and analysis. Duplicate entries, wrong data, or misclassified transactions – even such small mistakes can have a grave impact on the financial reports, leading to flawed analysis, forecasts, and decisions.  

5. Compliance pressure 

With a traditional financial reporting process where most of the work is done manually, your finance team might miss tracking the changes happening in the regulatory landscape. And failing to comply with changes happening in GAAP, SOX, or SEC requirements can increase the probability of audit failure, penalties, and costly lawsuits.  

Besides there is also IFRS that is followed in 168 jurisdictions across the globe, which requires companies to follow a set of accounting and reporting standards. Non-compliance with such laws can lead to investor distrust and in some cases, legal actions too.  

How is AI reshaping financial reporting 

AI – a global phenomenon is being adopted aggressively by companies across the world.  

The reason is not hard to guess. AI-empowered financial reporting has the prowess to deliver accurate and strategic insights that drive real business value at the speed of light. It can equip you with better predictive power, granular data analysis, and substantially improved accuracy.  

Here’s how AI is giving a facelift to financial reporting:  

1. Automating routine, time-intensive tasks 

Financial reporting encompasses repetitive tasks such as data extraction, categorization, journal entry generation, validation, and reconciliation. Integration of AI with your analytics tools can accelerate and simplify the process, while ensuring minimal human errors.  

By promptly handling such labor-intensive tasks, AI-powered analytics tools free up your finance teams to focus on high-level activities requiring detailed analysis and intelligent decision-making.  

2. Track data as it’s generated 

The best thing about AI is that you don’t need to wait for the end of a month or quarter to check the health of your company’s finances.

AI for financial reporting means you will have instant, real-time insights at your fingertips. You can keep a continuous watch on metrics like cash flow, revenue, and profit and loss, spot emerging risks, act on opportunities as they emerge, and most importantly take course-corrective actions on the fly.  

3. Identify red flags before they spiral 

Another advantage of using AI in financial reporting is that it helps you spot red flags in time, before they blow up into something bigger. Whether it’s unauthorized expenses, unexpected revenue fluctuations, or any fraud risks by suppliers, AI systems can instantly flag suspicious activities that are likely to go unnoticed by the human eye.  

This is mainly because AI systems have the capability to sift through large data sets across systems and decode complex information faster than you can imagine.  

By catching issues early, you can avoid costly errors and take immediate measures to strengthen internal controls.  

4. Powering predictive forecasting 

Conventional forecasting hinges largely on historical data, which can sometimes be irrelevant given today’s volatile environment.  

AI-enabled forecasting models can analyze a broader set of variables, including historical as well as real-time internal data such as operating expenses and cash flow, and external factors like market trends and regulatory shifts.  

This helps provide far more accurate predictions of financial performance, revenue trends, and cash flow patterns, among others. And as a result, you are better positioned to make confident investment and budgeting decisions even in an uncertain climate.  

Read more: How is predictive analytics transforming financial risk mitigation

5. Improving regulatory compliance 

At Hobasa, we believe that the regulatory landscape is constantly changing and keeping track of these developments is extremely crucial to avoid any potential lawsuits or fines. Manually keeping a check of this ever-evolving space is an ordeal, and that’s exactly where AI comes in.  

AI integration into the reporting process ensures that all financial transactions are monitored for compliance with major rules and standards like IFRS and GAAP. AI tools also bring to surface any potential risk of violations, prompting early action on your end. Further, such tools can also examine a large amount of data, giving you a clear picture of any credit or operational risks that you should be prepared for.  

Read more: Managing regulatory compliance: how to stay ahead of legal risks

Using AI for financial reporting: how can your business benefit 

AI is changing the mechanics of financial reporting and how. This inherently time-consuming exercise can be executed seamlessly and with high accuracy, thanks to AI. Here are some of the substantial benefits you can reap by integrating AI into your financial reporting process:  

1. Higher accuracy and lesser errors 

A major benefit of AI in financial reporting is that it helps improve accuracy, especially of routine tasks like data extraction, entry, validation, and reconciliation. Using advanced algorithms, AI significantly reduces the likelihood of errors when working with a large volume of data.  

By identifying anomalies and gaps in the data, these tools can spot irregularities quickly, helping you take corrective actions immediately to address the issues.  

2. Significant time and cost savings 

Financial reporting cycles such as month-end close, quarterly filings, or annual statements can be extremely labor-intensive to produce, consuming a considerable portion of your finance team’s bandwidth.  

By automating most of the routine tasks, AI can lift heavy weights, accelerating the whole process of report generation, while also ensuring your team can focus on more strategic activities requiring deeper analysis, decision-making, and strategy-building.  

This reduces manual intervention to a great extent, saving up on labor costs and letting finance teams work to their full potential. Additionally, with AI tools you can get your reports ready faster than when done manually and get up-to-the-minute insights into your company’s financial well-being.  

3. Stronger fraud detection and risk management 

Potential business fraud and suspicious activities can also be spotted with the help of AI in finance. By analyzing patterns across transactions, vendor behavior, and system logs, AI-powered analytics tools can help you detect red flags in real time. They can bring any abnormal activities such as duplicate payments, inflated invoices, or unauthorized access to the surface, empowering you to be proactive with your actions and prevent any potential damage.  

4. Improved regulatory compliance 

Complying with the changing laws and regulations is a perpetual challenge. AI can simplify this process for you by automatically checking financial transactions for issues related to compliance and intimate you if there are any violations. AI also has the ability to continuously learn from previous violations, keep track of the changing regulations, and spot emerging risks before they turn into real problems.  

5. Deeper financial insights and analysis 

With AI-enabled analytics, you get access to deeper insights into your company’s financial performance. AI’s capability to analyze vast data sets helps in pinpointing slow-moving inventory, unexpected cost surges, cash flow issues, and highlight opportunities where you can invest or save your hard-earned money. The granular, data-rich insights AI-powered reporting offers can be instrumental in making intelligent decisions to help you stay ahead of risks.  

Emerging AI trends in financial reporting

At Hobasa, we believe that as AI technology evolves, its role in financial reporting is only going to get bigger. Some of the key trends to watch out for: 

1. Rise of finance agents 

These AI-powered assistants will stretch the capabilities of AI to a whole new level. They are capable of executing tasks independently with minimal human assistance. They act as full-fledged team members, taking up tasks such as identifying irregularities, reconciling accounts, and generating customized reports, reducing the burden of your finance team to a great extent.  

2. Adopting Gen AI 

GenAI is also being actively embraced by leaders for financial reporting. It’s great at converting raw numbers into clear narratives that are easy to understand and help you make quick decisions. Instead of sending a spreadsheet to stakeholders, GenAI can help you build reports that effectively explain the metrics tracked, trends spotted, and risks detected, enhancing decision-making at every level.  

3. Hyper-personalization 

AI, especially GenAI can help build customized financial reports to match the unique needs of different stakeholders. So, instead of a one-size-fits-all report, you can leverage GenAI to build reports that are specifically relevant for different roles and levels. For example, a CFO might need a high-level report showing cash flow trends and financial ratios. On the other hand, the marketing head might need a report that talks about campaign ROI and revenue contribution.  

Ask the right questions when adopting AI-driven financial reporting 

While AI is incredibly helpful and is redefining financial reporting, it comes with its own set of risks. Before diving headfirst into AI, you must ask yourself the right questions – to ensure you are implementing AI responsibly.  

• Are the data sources feeding the AI tool accurate, secure, and unbiased information?  
• Does the AI system you are using adhere to the regulatory requirements?  
• Do you have any internal governance system in place to keep a check on the AI system?  
• Does your AI system have internal controls for maintaining data security? 
• Do you have any specific teams in place to vet the reports generated by AI?  

These questions will help you come to an answer where you will have a clear understanding of the boxes your AI system should tick before you implement it for financial reporting.  

To sum it up, AI is a game-changer – but only for those who implement it wisely and responsibly.