Loans are granted to companies every day. Or not. Of course, a few basic things are decisive for the approval of a loan. It is difficult to recommend a company for a loan if its balance sheet was weak in the past financial year, if its income statement was more loss-making than successful, and if it was therefore in the red. In more positive cases and in order to make a win-win situation a reality for both banks and companies, the automatic extraction of the balance sheet and income statement helps enormously. Learn how this win-win situation is realized with intelligent, AI-based OCR (Optical Character Recognition) in this article.

With a share of over 99%, SMEs in Switzerland form the backbone of the economy to a large extent. In order to be able to operate sustainably, bank financing plays a decisive role for companies in addition to equity capital. So, there are a lot of loans to be granted, which makes this a daily business for banks.

More than 99% of Swiss companies are SMEs – loans are a daily business for banks. So it is not surprising that lending is one of the most common services of a bank.

Balance sheet and income statement as the basis for creditworthiness

Companies often value trust in their bank and a long-term relationship. And a bank has an interest in credit processing being as uncomplicated as possible. In this process, the applying company plays a significant role by disclosing its balance sheet and income statement. The more loans it can grant to creditworthy companies to finance and boost business, the better. Two things are fundamental in a company’s annual financial statements. The balance sheet, which shows the current financial position or cash flow, and the income statement, which reflects the overall performance of the company, whether it made a profit or a loss in the past fiscal year. And why not use the advanced technologies available today to check creditworthiness and speed up processes by an order of magnitude?

Different perspectives of banks and companies

From a bank’s perspective, efficient service includes granting credit as quickly as possible. A seamless review of the creditworthiness of the offending company is more than desirable. The perspective of a company is somewhat different. It always wants to show itself from the best side, which in other words means: to be able to present good balance sheets and profit and loss statements, which increases the rating respectively the credit score, which will enable the faster positive decision ergo uncomplicated credits in the future.

Banks need a quick identification of creditworthiness, companies strive for an impeccable rating – both automated possible with the intelligent, AI-based OCR.

Solutions in the form of intelligent, AI-based OCR

What remains identical is the solution. To achieve the points raised, intelligent, AI-based OCR is used. Considering the bank or the company’s perspective, it looks as follows:

  • Bank: banks use OCR software to automatically check the company’s balance sheets and income statements when a loan request is made. OCR automatically extracts all relevant data from the balance sheets and income statements. In a very short time, the bank now knows whether the company is creditworthy or not. Furthermore, based on the data extracted by OCR, it can accurately classify the terms and interest rates of the loan
  • Businesses: Intelligent OCR helps businesses to be able to present an impeccable rating. OCR continuously extracts key values to trigger new valuations and look at how well (or how poorly) the company is performing

Accordingly, intelligent, AI-based OCR is ideally suited for both banks and companies in connection with balance sheets and income statements to drive process optimization in an automated and efficient manner.

The integration of intelligent OCR is not only a plus for banks and companies, but can also be used for company expansions or trade sales.

Automated enterprise scanning

Intelligent OCR software can also be best used for company expansions or trade sales. Data of any companies can be extracted automatically, companies scanned. This helps to see what kind of companies are suitable, which ones are more suitable for acquiring, which ones are less suitable.