What is Bank Statement Analysis?

What are your bank statements telling you about your business? 

They’re not just lists of numbers — they’re packed with valuable information about your company’s financial health.

Bank statement analysis helps you uncover this hidden data. It gives you a clear picture of your cash flow, spending patterns, and overall financial health. With this knowledge, you can make better budgeting decisions, spot potential problems early, and keep your business on track financially.

In this blog, we’ll explore what bank statement analysis is, why it matters for your business, and how new technology is making it easier and more effective than ever. 

What is bank statement analysis?  

Sample bank statement with key fields

Bank statement analysis is the process of systematically reviewing and interpreting all entries in a bank statement over a specific period. 

It’s like putting your financial transactions under a microscope better to understand your business’s financial health and activities.

Key aspects of bank statement analysis

Transaction categorization: Classify entries as deposits, withdrawals, transfers, payments, etc.Expense analysis: Review outgoing payments such as vendor payments, payroll, and operational costs.Revenue tracking: Monitor income sources, including customer payments and interest income.Asset and liability changes: Track fluctuations in the company’s assets (cash, investments) and liabilities (loans, credits).Balance verification: Confirm the accuracy of the final balance at the end of the statement period.Pattern recognition: Identify recurring transactions or unusual fraud activities.

This detailed review helps businesses get a clear picture of their financial standing and spot any irregularities early on.

Why is bank statement analysis important? 

Cash flow analysis

Identify regular expenses (e.g., payroll, utilities) and flags unexpected costs.Track steady income streams and highlight irregular earnings.Spot unusual activities that may indicate errors or bank statement fraud.Predict future cash flows and plan for potential overdrafts.

Bank reconciliation

Compare bank statement data with internal records to ensure every transaction is accounted for properly.Detect errors or fraud by catching discrepancies between the bank’s records and your financial documentation.Catch and correct errors before they cause significant financial damage.

Managing future liabilities

Bank statement analysis helps review the balance to ensure sufficient funds are available for upcoming obligations.The insights from bank statement analysis can help avoid unnecessary spending and improve operational efficiency.

Loan and client assessment

To understand the financial reliability of loan applicants and clients and to evaluate loan repayment abilityThe analysis gives you a better picture of the applicant’s liabilities and income streams

Audit and compliance

Support the audit process with detailed transaction historiesEnsure accurate tax filingsMaintain adherence to financial regulations

But let’s face it – going through bank statements line by line is time-consuming and tedious. Traditionally, only trained accountants and auditors performed bank statement analysis, wherein each entry in the bank statement was examined and analyzed. This is practically impossible with today’s scaled-up operations and multiple formats of bank statements. 

That’s where modern AI-powered tools come in. They can quickly analyze your statements, giving you useful insights without the headache of manual number-crunching.

Now, let’s examine how this is done and explore some advanced AI-powered bank statement analysers (BSA).

Spreadsheet-based bank statement analysis

Spreadsheet tools like Microsoft Excel, Google Sheets, or LibreOffice Calc have long been the go-to tools for bank statement analysis. They offer a familiar interface and features that can be used for effective financial management.

The data from the bank statement is imported or manually copy pasted into the spreadsheet templates. Formulae are prebuilt into the spreadsheet to perform calculations, which can then be manually analyzed.

An example of a bank statement template by MS Excel

Pros of using spreadsheets for bank statement analysis

Using spreadsheet templates is a low-cost solution for bank statement analysis. It can be learnt using free online resources and YouTube tutorials – which makes it popular among individual professionals.

They can be used offline and be easily customized to fit specific business needs or accounting practices. Advanced users can create complex calculations and leverage built-in charting tools for better visualization.

Cons of using spreadsheets for bank statement analysis

While spreadsheets offer flexibility, they have many drawbacks for bank statement analysis. Manual data entry is time-consuming and prone to errors, especially as transaction volumes grow. Spreadsheets struggle with scalability, often becoming sluggish with large datasets. They also lack robust security features, potentially exposing sensitive financial data.

Version control can be challenging, particularly in collaborative environments, and spreadsheets offer limited audit trails for tracking changes. While possible, complex financial modeling and advanced analysis are challenging in spreadsheets.

AI-powered bank statement extraction

AI-powered tools are paving the way for financial analysis across all industries.

Bank statement analysis can done by leveraging machine learning (ML) and artificial intelligence (AI) to automate and enhance the extraction and interpretation of financial data. AI-powered tools use advanced OCR to extract data with more than 98% accuracy and come with self-learning and adaptive capabilities.

Pros of using AI-powered bank statement analysis

These tools automate data extraction and categorization and can dramatically reduce manual effort and human error by increasing speed and accuracy. They excel in handling large volumes of data across multiple accounts, making them highly scalable for growing businesses. 

The intelligent categorization capabilities of AI improve over time, providing increasingly accurate insights. These tools can also be easily integrated with all other financial systems using API to act as bank statement analysers. By automating time-consuming tasks, AI tools free up valuable resources, allowing employees to focus on strategic decision-making rather than data processing.

Cons of using AI-powered bank statement analysis

While AI-powered automation tools offer significant advantages, they aren’t without drawbacks. The initial setup and training period of some tools can be time-consuming, and there may be a learning curve for staff, especially for advanced complex integrations.

These tools often require a substantial initial investment and might not be suitable for really small businesses or low-volume bank statement users. While they are highly accurate (98%+ accuracy), AI tools are not perfect and may occasionally misinterpret unusual transactions and require human oversight.

How to set up bank statement extraction and analysis workflow  

Bank statement analysis needs to be spot-on, with no room for errors.

Let’s see how you can use Nanonets, an AI-powered OCR data extraction to make the process easier and more efficient. Note that this can be done for free for up to 500 bank statements:

Open the web application at app.nanonets.com. If you don’t have an account yet, sign up for free and then log in.Navigate to “New workflow” and select “Pre-built bank statement extractor.” If this option isn’t available, you can use the Zero-training extractor instead.Pre-built zero training bank statement extractor by NanonetsUpload/Import all your bank statements —whether they’re PDFs, scanned images, or spreadsheets. Nanonets can handle all file types.  Importing all your bank statements for analysisReview the extracted data and extract more fields if any missed.AI-powered bank statement extractionYou can also customize and add more bank statement fields by editing different labels.Customizing bank statement fields

 

Download/export the data as different file formats (CSV, Excel, Google Sheet, XML).Export bank statements for further analysisWhile the above steps covered the basic steps to set up a bank statement extraction workflow, for more analysis you can also export it to your accounting or ERP software for further processing. All you need to do is setup an integration workflow.

Nanonets comes with 30+ built-in integrations, you can set up any new integration workflow using a bank statement API.Integrations with accounting and ERP softwareYou can also used advanced analytics to get insights into your workflows.Get advanced analytics using Nanonets

Overcoming challenges in bank statement analysis 

Difficulties arise in bank statement analysis primarily due to the inconsistencies in the source data.  

High volume and velocity of data

Traditional methods like manual data entry, spreadsheet-based analysis, and periodic batch processing struggle with the increasing volume and speed of financial transactions and often lead to delays. To address this, implement real-time data processing solutions and use big data analytics tools capable of handling large volumes of transaction data continuously. 

AI-powered data extraction tools can significantly improve this process by automatically processing and categorizing high volumes of transactions in real-time, regardless of the data source or format. 

Diverse statement formats

Banks use different styles and formats for their statements, making standardized data extraction difficult. If you are currently using or planning to adopt a template-based data extraction tool, a library of templates for commonly used bank statement formats can help streamline the process.

In the case of advanced intelligent document processing (IDP) tool such as Nanonets, the AI models automatically adapt to various templates and can help overcome this challenge.

Poor source quality

Poor-quality scans can lead to low accuracy in data extraction. Invest in high-quality scanning equipment for physical statements and use image preprocessing techniques to enhance document quality before extraction. AI algorithms capable of handling low-quality inputs can significantly improve accuracy.

Multiple currencies and international standards

For companies operating across different countries, handling multiple currencies and varying bank types adds another layer of complexity. Financial standards and terminologies can differ from one country to another, making data extraction and harmonization a bit of a challenge.

Use advanced tools that come with built-in currency conversion capabilities and implement a standardized chart of accounts to accommodate international variations. Leverage AI tools that can recognize and categorize transactions across different languages and currencies.

Ensuring data security and compliance

Finally, safeguarding data security and ensuring compliance with regulations like GDPR or HIPAA (in healthcare) is crucial. Financial information is sensitive, and managing compliance can be challenging.

Choose a reputed software solution with robust encryption and compliance certifications.  Implement strict access controls and audit trails for all financial data, and conduct regular staff training on data security best practices.

Industry applications of bank statement analysis

Bank statement analysis is used across many industries, for financial management and decision-making processes. Below are some key examples of how different sectors use this tool:

Financial services

Banks, credit unions, and other lending institutions use bank statement analysis to assess the creditworthiness of loan applicants. By examining transaction histories, they evaluate risks and determine an applicant’s ability to repay loans, guiding loan approval decisions. 

Investment banks also use this analysis to evaluate client companies’ cash flow for valuation purposes and assess financial stability for mergers and acquisitions.

Insurance 

Insurance companies rely on bank statement analysis to assess the financial standing of clients. Underwriters use this data to evaluate risks, ensuring that premiums align with the applicant’s financial profile. This process is also essential for processing claims and monitoring policyholder financial behavior for ongoing risk assessment.

Taxation and accounting

In taxation, bank statement analysis helps verify income, track deductible expenses, and ensure accurate tax filings. Tax experts and accountants cross-check reported earnings with actual transactions to prevent underreporting and detect potential tax fraud. This analysis also facilitates audits and financial investigations when necessary.

Retail and e-commerce

Retailers use bank statement analysis to understand spending patterns and customer preferences. Daily reviews help spot discrepancies and fraud early, while also tracking payments and managing refunds. In both physical stores and e-commerce, this analysis ensures smooth transactions and informs inventory management decisions.

Real estate

In real estate, bank statement analysis checks the financial stability of potential tenants or buyers. Realtors and property managers use this tool to verify the financial capability of clients, ensuring informed decisions. It’s also crucial in mortgage applications to verify income and employment, and in analyzing cash flows for property management.

Hospitality sector

Hotels and restaurants rely on bank statement analysis to manage operational costs and identify patterns in customer spending. These insights inform pricing strategies and marketing decisions, improving overall profitability. The analysis also helps in monitoring and reconciling payments from various booking channels.

Education

Educational institutions use bank statement analysis to manage tuition payments, monitor financial aid, and track expenses. This helps maintain transparency in financial reporting, especially in government and trust-run institutions. It’s also used to monitor the utilization of grants and research funds.

Healthcare

In healthcare, statement analysis is used to manage patient billing and insurance payments. Hospitals and clinics track operational expenses, while pharmaceutical companies monitor cash flow. Health insurance providers use this analysis to understand spending patterns and manage claims payments.

Non-profit organizations

Non-profits use bank statement analysis to ensure proper use of donations and grants. It helps track program-specific expenses and demonstrates financial accountability to donors and regulators. This analysis is crucial for managing cash flow and ensuring sustainable operations.

Government agencies

Government bodies use bank statement analysers to monitor budget utilization across departments and track tax revenue and spending. It helps detect potential fraud or misuse of public funds and manages grant disbursements and usage. This analysis ensures fiscal responsibility and transparency in public finance.

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