Automated Spreading: How AI Revolutionizes Data Analysis in Lending

Automated Spreading, meaning capturing and spreading financial statements and calculating financial ratios for credit risk assessment are key processes in commercial lending. The predictive quality for credit risk rises and falls with the quality of data on the financial background of clients. How the use of artificial intelligence enables much faster and better analysis of financial data, knows Saikat Gupta. He is Vice President at our analytics partner Evalueserve India and an expert in Automated Financial Spreading and presents a revolutionary new approach to data preparation. This turns the previously laborious process of manual capturing of financial statements into a fast and lean process.

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The New Efficiency Potential of AI for Lending

In a business expert talk about automated spreading, risk rating and credit decisioning, Sakai Gupta elaborates in detail on the status and the main trends of digitalization in the banking world. Around the globe, financial institutions are massively investing in technology to evolve their traditional lending business into a digital one. Fintechs are setting the pace, with traditional houses following suit. According to market research, the digital lending economy is expected to grow by around twelve percent annually from $453 billion to $795 billion between 2024 and 2029.

Lenders looking to capitalise on this impressive growth need to automate their processes to meet the needs of their customers and compete in a dynamic market. Here, it is important to identify those sub-processes where automations pays off. Furthermore, it is important to use the right technologies – among other things: Machine Learning.

The use of machine learning (ML) will play an important role in the future.

“Banks have been using machine learning models for decades. But the focus has been more on data classification projects and process automations, sometimes also on identifying data trends,” says Saikat Gupta. The new high-performance capabilites of modern AI models offer the potential to digitlaize the actual core business, i.e., the financial service itself and increase efficiency. Saikat reports: “Now, we are seeing that ML is increasingly being integrated into the underwriting processes across the entire credit value chain.”

Why is that? With the emergence of new technologies such as generative AI, a dataset can be analyzed in a much broader sense, revealing significantly more complex correlations. Saikat Gupta gives an example of what this enables banks to do: “You can query five-year-old data to understand what the most important upcoming trends in an industry will be.”

This provides a much more extensive basis for making decisions about lending.


The Importance of Ongoing Financial Analysis

The analysis of the borrower’s financial situation is not confined to the initial credit granting process.

The spreading of financial statements and the rating are crucial for ongoing credit risk management, with annual reviews being a standard practice in many financial institutions. Regularly updating the financial data of clients ensures that banks can detect changes in the financial health of borrowers promptly. This proactive approach helps in mitigating risks and making informed decisions regarding existing credit lines.

During the annual review, financial statements are re-evaluated to monitor performance against initial projections and to identify any potential red flags. Automated spreading significantly enhances the efficiency and accuracy of these reviews, allowing credit analysts to focus on in-depth analysis rather than data entry.

This requires that credit analysis teams can access a carefully compiled data foundation about the clients anytime and quickly. Whether this is ensured depends on the process quality of financial spreading.

Expert Business Talk I On-Demand

How to effectively automate financial spreading, risk rating and credit decisioning by leveraging AI and integrated SaaS solutions.

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Financial spreading

The Challenges of Financial Spreading in the Credit Granting Process

Financial spreading is an essential part of the credit granting process. It means transferring the data from annual financial statements, or other financial documents of clients into the bank’s financial spreading applications. And this must be done in such a way that the correct information is mapped to the corresponding field in the financial spreading template. Only then do they provide a meaningful picture and can be usefully processed further – not least for a well-founded credit decision.

“The larger the customer base, the more challenging the manual processing and accurate evaluation of financial data becomes,” says Saikat Gupta. In the expert talk, he goes into detail on the core problems that arise from this. Only a few aspects are mentioned here as examples.

As expected, manual data extraction is time-consuming and can take 35 to 120 minutes per dataset. Moreover, it is prone to errors. According to Gupta, eight to ten incorrect entries in 100 data points are not uncommon. Especially in peak seasonal times, it is difficult to maintain consistent data quality when there are high workloads yet processing deadlines must be met. This drives up the costs for later quality assurance.

It is not surprising, then, that interest in automating this process is growing. “Banks desire nothing more than to manage the costly financial spreading more efficiently. And rightly so. Because this is a case for automation with high ROI potential,” says Saikat Gupta.

What is Automated Spreading?

Automated Spreading replaces the manual capturing of financial statement data with AI. The credit analysts upload the e.g., PDF files via a interface or a web application.

Subsequently, AI-trained text recognition algorithms identify the relevant data points and add them to the correct place in the database of the financial spreading software used by the bank. The foundation of specialized software for automated spreading is much more powerful than conventional options for OCR (optical character recognition). It not only makes the text of a paper document digitally searchable but, unlike OCR technology, also captures contextual relationships.

“Automating this is attractive from the banks’ perspective but not trivial from an IT standpoint,” emphasizes Saikat Gupta. “In practice, the credit clientele submits their financial reports in all sorts of document formats, as a scanned PDF, in Excel, Word, sometimes as a low-quality image file, sometimes as a protected file, and so on.” Moreover, the financial accounting standards used may differ, and for banks with an international clientele, this also applies to the languages in which the documents are written.

Software for automated spreading must therefore be able to read in and standardize output from very heterogeneous source material. An indispensable part of this is a so-called template-based approach. It allows the captured data to be displayed in different target templates at the appropriate place. These vary, for example, depending on the legal form of the company, but also over time as internal bank and legal guidelines change. Even then, the assignment should still be correct.

Good solutions prepare the data as precisely and quickly as possible. At the same time, they always present how they calculated the evaluations and which bank guidelines were the basis in a comprehensible, traceable, and transparent manner.

The Benefits of Automated Spreading for Credit Decisions

Evalueserve meets all these requirements for automating financial spreading with a solution called Spreadsmart. It can be seamlessly integrated into ACTICO’s cloud-based Credit Risk Platform. This allows the captured data to be optimally interwoven with the entire digital credit granting process. “Banks that have automated their financial spreading in this way report a time saving of up to 80 percent and data accuracy of up to 99 percent,” Saikat Gupta concludes.

The integration of Spreadsmart with the Credit Risk Platform offers extensive benefits beyond automating data collection. ACTICO’s solution contains fully configurable templates for financial data, which accelerates further processing in the credit granting process. This makes it easy to create reports that are either provided to credit analysis teams as a basis for evaluation – or result in fully automated decisions upon request. Because the Business Rule Engine integrated into the Credit Risk Platform allows banks to also design the actual credit granting based on adjustable business rules as an automatic process.

Because ACTICO and Evalueserve pursue a cloud-based approach, the solution can be easily integrated into the bank’s existing IT landscape and with external data sources via interfaces. In this way, banks realize a modern digital workflow from data entry through creditworthiness analysis to the decision on credit granting. Additionally, the results of financial spreading are seemingly available for the calculation of internal bank rating procedures, which must also be included. This article explains in more detail the opportunities for automating other sub-processes.


Automated Financial spreading has so far been a costly, time-consuming, and error-prone process that slows down and makes the entire credit granting process more expensive. The new performance capability of machine analysis methods allows this process to be automated, thus making the entire digital lending business significantly more efficient.

AI-supported solutions for automated spreading extract data more precisely and faster than a traditional manual process allows. Advanced algorithms can establish meaningful relationships between financial metrics and insert the required data precisely into target templates – even if the source documents were written based on different legal forms, accounting standards, and business languages. This enables seamless further processing in subsequent sub-processes such as the analysis of creditworthiness and the actual credit granting.

Automated spreading is easy to implement in banks’ IT systems thanks to the cloud-based solutions from ACTICO and Evalueserve. With ACTICO’s Credit Risk Platform, financial institutions can flexibly and scalably digitize individual parts or the entire workflow of their credit risk management, adaptable to their requirements. It can be easily expanded with individual components like Spreadsmart from Evalueserve.

With automatically captured and processed financial data, banks lay the foundation for modern digital lending that reduces operating costs with a high degree of automation, minimizes default risk with precise financial analyses, and offers an attractive customer experience with short processing times for a digital target group.

Moreover, the capability to perform annual reviews and ongoing financial analyses ensures that banks can maintain up-to-date financial insights into their clients financial situation, enabling them to manage credit risk effectively over the entire lifecycle of a loan. This continuous monitoring is vital for maintaining a robust and proactive credit risk management strategy.

Interested in delving deeper into the topic of commercial lending?
Take a look at our expert talk on financial spreading:

Expert Business Talk I On-Demand

How to effectively automate financial spreading, risk rating and credit decisioning by leveraging AI and integrated SaaS solutions.

Watch the expert talk now

Financial spreading

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