Time is money, and in lending, speedy decisions pay dividends. However, many business finance services struggle to deliver risk-managed loan decisions in a timely manner.
Industry experts agree that one of the main culprits behind slow loan decision-making is data extraction from loan underwriting documents. Manual data extraction fails to accurately capture data from documents due to the repetitive nature of the task.
Even Optical Character Recognition (OCR) - the so-called solution to manual data extraction - is no match for complex document formats. In practice, OCR often requires employee intervention—exacerbating the problem it seeks to solve.
In other words, it’s easy for business finance providers to set KPIs for faster turnaround times but far more difficult to honour them. Several major financiers, such as NatWest, already offer instantaneous decisions on small business loans. Does immediate decision-making represent the future of underwriting?
The rise of IDP (Intelligent Document Processing) in the financial services and banking sectors has ensured that instant, risk-managed decision-making is not only possible, but seamless Automated data extraction solutions offer a sophisticated approach to document processing that’s tailor-made for data-heavy industries such as underwriting.
Moreover, IDP offers a unique capacity to learn from previous errors and, in theory, can offer 100% accuracy in captured data. But first, let’s examine what AI-powered document processing is and how it can benefit business financiers.
Intelligent workflow automation directly extracts the relevant information from scans, PDFs or online text of financial documents such as bank statements. The data is then outputted into a usable format for employees. Correctly configured workflow automation also ensures that the whole process should be instantaneous - or close to instantaneous - with a negligible error rate.
The typical documents used in assessing a customer’s creditworthiness are bank statements, financial statements, and invoices. Most data extraction methodologies struggle with the complex format of financial documents, but AI permits a deeper understanding of the documents.
Initially, an AI data automation model should only require a few training documents. Then, the technology should be able to transfer understanding from previous documents to completely new documents. IDP can therefore process any document with ease.
The alternatives to automated data extraction are extremely costly in the long term. Manual data extraction requires FTEs who are usually overqualified for simple data extraction. Clunky and/or outdated OCR technology also represents a financial drain for many global business financiers.
In contrast, most AI-powered automated underwriting software packages come as a subscription service or a fixed price per page, both of which are less expensive than paying out of pocket for FTEs for manual data extraction. Moreover, compared to OCR, which is expensive to develop and maintain, IDP is the significantly more cost-effective option.
Slow credit analysis is off-putting to customers looking for quick, accessible business financing. Business finance providers who can offer quick decisions on whether to extend credit will win a greater share of the thousands of businesses applying for loans.
High-quality data extraction technology is designed to be easy-to-use, meaning that staff can be onboarded and trained more quickly. Therefore, underwriters will have more time to focus on complex credit evaluation cases and customer service.
If configured correctly, AI-powered underwriting document technology should fit seamlessly into pre-existing company architecture. Once deployed, the complete solution should offer an end-to-end automated workflow solution. For example, the process of using Evolution AI’s IDP technology looks like this:
Aside from uploading the documents and receiving the output, employees aren’t needlessly involved with the data processing. There’s no need to involve the company’s IT team, no need to waste time on manual data processing, no waiting around for data to get captured. It’s all there in one integrated solution: whether it's a bank statement or invoice that you're looking to extract data from.
Moreover, a high-quality piece of technology should be able to keep the complex AI technology concealed behind a user-friendly interface. Or, as one of our clients eloquently phrased it: “Evolution AI makes it incredibly simple to [not] get entangled in the data science that's going on in the background”.
As a rapidly expanding industry, there are multiple AI and RPA-based data automation software options. However, there's one way to distinguish the key players from the rest: the quality of their customer service.
The best AI data extraction companies are the ones that have developed a mature and systematic process for supporting their customers. Document automation can be confusing and unfulfilling if not guided by an experienced customer team.
Evolution AI is proud to offer exceptional customer service, with customers describing us as “heavily invested in our users’ needs”3 and “available practically 20 hours a day, 7 days a week”4. Our customers are supported every step of the way through setting up our technology and making the most of it.
AI-powered data retrieval is a flexible solution that pairs advanced technology with a simple purpose: extracting data from documents such as bank statements, invoices and financial statements. If integrated correctly, it can provide a cost-effective end-to-end solution for data automation.
However, not all IDP solutions are made equal. It’s important to opt for the provider with the most easily implemented technology and the best customer support.
Consequently, we invite you to try Evolution AI’s award-winning technology and highly-commended customer service - contact us today at hello@evolution.ai or book a demo.
