Traditional financial statement analysis methods are increasingly becoming obsolete. They primarily rely on basic tools such as the Profit and Loss Account and Balance Sheet, failing to deliver comprehensive insights into a company’s financial health.
Furthermore, the heavy dependence on historical data can lead to outdated conclusions and predictions that do not reflect current market conditions.
As a result, businesses risk making uninformed decisions based on incomplete or irrelevant data.
Nevertheless, the integration of advanced tools like artificial intelligence (AI), machine learning (ML), cloud-based solutions, etc., for financial statement analysis is changing the landscape. These tools are helping leaders derive more insights and make accurate decisions.
A report by PwC reveals that businesses using advanced analytics outperform their competitors by 6% in profitability and 5% in productivity.
In this article, we will explore the transformative role of advanced financial statement analysis tools.
Advanced Financial Statement Analysis: An Outline
Advanced financial statement analysis tools are sophisticated applications and methods that gather, analyse and interpret vast amounts of financial data from balance sheets, income statements, cash flows, etc.
A survey by Deloitte revealed that 70% of finance professionals believe that advanced analytics will play a critical role in the finance function’s ability to support strategic decision-making.
These tools employ the latest technologies to gain insightful knowledge and bridge the information gap to make wise business decisions. It also significantly improves operational efficiency and risk management.
Now, let us explore these technologies and tools one by one.
Modern Financial Statement Analysis Tools and Technologies for Lenders
A survey by PwC found that companies using advanced analytics and AI for risk management experienced a 23% reduction in annual losses from risks.
Let’s understand the key technological tools and technologies re-defining financial statement analysis:
1. Robotic Process Automation
RPA automates repetitive tasks like extracting financial statement data and generating reports. It reduces the chance of human error while accelerating workflows. Furthermore, it frees up analysts to focus more on strategic tasks.
As of now, The BFSI (Banking, Financial Services and Insurance) sector accounts for 36.81% of the revenue share of the global RPA market.
Also, according to Gartner Research, 80% of finance leaders have already implemented or are planning to implement RPA.
2. Artificial Intelligence-driven Predictive Tools
Natural language processing (NLP) can extract qualitative insights from textual data within financial statements like audit notes, management discussions, etc.
The data extracted from financial statements are used to forecast future outcomes. It allows lenders to make informed decisions, detect fraud, measure credit risks, etc.
Moreover, the analysis of unstructured data via AI and ML can identify trends and sentiments that would otherwise go unnoticed by the traditional approach.
According to a survey by EY, 50% of finance leaders believe that AI will have a significant impact on the way finance drives data-driven insight.
For instance, Precisa’s Bank Statement Analysis tool extracts relevant data from multiple bank statements, classifies and categorises them, and generates insightful reports. This saves time by 5X and improves productivity by 8X.
- The Credit Report Analysis tool analyses the client’s repayment history, credit utilisation, defaults, and so on to give a holistic 360-degree view of credit behaviour.
- The GSTR Analysis tool tracks real-time data from verified government sources. It enables lenders to predict revenue trends, discrepancies in claims, etc., and integrate this into credit scoring models.
Lenders can use the information to tailor product recommendations to clients.
3. Integrated Multi-Source Analysis
The traditional analysis often relies on siloed data and fails to capture the comprehensive financial picture.
In contrast, modern tools can aggregate and analyse the data from banks, mutual funds, insurance, etc., in a secure and consent-based manner. It also eliminates the need to submit physical documents, enabling faster loan approvals.
For example, the Account Aggregator framework by Precisa helps in this integration for quick and foolproof credit decisions within minutes.
4. Cloud-based Financial Dashboards
These tools can also collect, analyse, and visualise data in real time to understand the current state of the client’s financial standing. It allows lenders to quickly assess frauds and suspicious activities and have early warnings to take preventive actions and better portfolio management.
Additionally, cloud integration facilitates remote accessibility, allowing for data access anytime, anywhere. Precisa leverages cloud technology for its applications, which enables faster lending decisions.
5. Blockchain for Financial Data Transparency
Blockchain, by offering a decentralised and tamper-proof ledger, ensures data is stored securely and transaction records are accurate and verifiable.
For lenders, it will ensure they have access to trustworthy information while making decisions.
Combining blockchain with Precisa’s Bank Statement analysis and Credit Report Analysis will ultimately lead to more accurate risk assessment and fairer lending practices.
Financial Statement Analysis: Overcoming Implementation Challenges
Despite these benefits, there are several challenges in the adoption of financial statement analysis tools:
1. Data Quality
A Gartner research study has found that organisations experience an average annual loss of $15 million due to poor data quality.
Unstructured and inconsistent data are prevalent, especially in small and marginal sectors. Ensuring the reliability and accuracy of inputs remains a consistent pain point.
2. Initial Heavy Investment in Technology
The significant costs associated with installing technology infrastructure and maintenance can limit the adoption of advanced tools for small players.
However, using a cloud-based solution can solve this worry.
3. Skilled Personnel
In India, this skill gap is particularly pronounced. NASSCOM mentions approximately 50% of the skills needed in the BFSI sector by 2027 are currently non-existent.
4. Evolving Compliance Issues
The regulatory environment undergoes frequent updates, and aligning advanced financial tools with these changes is a complex but urgent task.
Key Takeaway
As India moves towards a Digital Economy, embracing advanced financial statement analysis tools is crucial for lenders seeking a competitive edge.
Precisa’s suite of tools, including the GSTR Analysis, Account Aggregator, and Bank Statement Analysis, will provide real-time analysis to identify growth opportunities, efficiently manage risks, make informed decisions, and promote innovation in the ever-changing financial world.
These cloud-based tools use advanced data validation techniques designed with regulatory compliance in mind.
The best part? Taking the first step with Precisa is entirely free!
Sign up now to get started.
Mumbai