Insight On Financial Spreading And Why It Is Needed

Insight On Financial Spreading And Why It Is Needed

Financial spreading is the process used to standardise the presentation of financials and highlight major risks in financial statements. Financial institutions also use it to maintain a record of a customer’s financial information and look for patterns in it. This helps businesses review and analyse credit information, identify credit risks and decide on the next big step for growth of the organisation.

Why is conventional financial spreading unable to cater to current needs?

Companies have historically used manpower for financial spreading. However, maintaining and presenting financial spreads are not easy. It is time-consuming and requires analysis of a significant amount of data to present a forecast. Manual financial spreading may also prove inefficient if the organisation operates on a large scale, as the issue of handling a large dataset could be exacerbated by inconsistency in the language used in the reports generated by the different geographical locations.

AI-powered automated financial spreading

Some outsourcing partners have devised a solution for financial spreading. They propose an automated model for financial spreading that utilises digital image processing and complex algorithms of artificial intelligence (AI), machine learning, deep learning and natural language processing. This automated financial spreading model is able to handle large datasets, necessary for organisations with large-scale operations, and present the final credit information in a structured manner for efficient analysis.

Benefits of automated financial spreading over manual financial spreading

Dealing with large datasets

Manually coordinating and maintaining the financial spreading process for an organisation with large-scale operations is difficult because of the large datasets involved. It also requires significant headcount. An automated financial spreading model can deal with large datasets effectively and generate financial spreading reports that can be analysed easily.

Dealing with multilingual credit statements

The conventional method of financial spreading faces challenges when it comes to a global organisation, as multilingual financial statements need to be incorporated. An AI-powered automated financial spreading model can overcome such challenges well. 

Obtaining precise results

The final output of financial spreading may not be precise when large datasets are handled manually. Just maintaining credit information is not enough; a thorough analysis is required. Finding patterns when working manually with large datasets will be very inefficient, leading to inaccurate results. However, AI-powered automated financial spreading models can find patterns in large datasets efficiently and produce precise and accurate financial spreads along with a detailed analysis of the risk patterns.

Improved decision-making process

Using an AI-powered automated financial spreading model can help you obtain a detailed analysis from different perspectives. A financial spread produced by an AI-powered automated financial spreading model will help separate current liabilities and assets from their non-current counterparts and separate tangible assets from intangible assets. The spread will also show the gross profit earned from different profit-generating activities undertaken by the corporation and help determine ways in which to boost the profit margin, enhancing the decision-making process. 


The conventional method of financial spreading is time-consuming and requires significant headcount. Using an AI-powered automated financial spreading model can help curtail hiring costs. Such models deal easily and significantly faster with large datasets, eliminating the need for human intervention in activities such as error handling, exception handling and validation of spread numbers.

Updating your manual financial spreading process to an AI-powered automated financial spreading model could boost your business by cutting costs of hiring redundant manpower and improving the overall result. Such a model can easily identify origin of risk, calculate risk and give you the credit edge.

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