More than ever, the customer is king. The requirements and expectations are sky high and organizations in the financial sector are also looking for ways to distinguish themselves in various areas. This is difficult, because products and services are rarely unique and the price differences are minimal. Organizations that successfully differentiate themselves usually win with a smooth customer experience. At ProcessMaker IDP, we therefore have enriched our platform so financial institutions can use AI technology to optimize one of the first experiences customers have with them. Before doing business with consumers or companies, financial institutions are required to go through processes to identify and verify the customer. The documents and financial documents that are provided for this are usually complex, unstructured data that must be processed manually. This leads to long processing times and often delays in the process. Automation is pretty much the only option to make a difference here. ProcessMaker IDP has succeeded in this by applying Intelligent Document Processing (IDP). From the recently introduced version 2.1 of our platform, we offer the possibility to remove the bottleneck of manual customer onboarding. To do this, unstructured documents based on machine learning models are combined with logic and patterns and converted into structured customer data. How does Intelligent Document Processing work? Documents can be submitted for processing via API links or ProcessMaker IDP can retrieve documents from various sources including file shares, and email. Image preprocessing optimizes images from scanned documents for OCR processing. For instance optimizing resolution, contrast or straightening text lines. With optical text recognition, ProcessMaker IDP converts the scanned documents into editable text. Subsequently, the documents are classified by document type and it is checked whether the information is complete. The relevant data is extracted from the documents and automatically validated. For extraction we can use either pre-trained machine learning models, regular expressions or a combination of both. A special approach is required to extract data from tables, this is called table extraction. Our solution also takes into account the requirements of the GDPR by automatically anonymizing the personal data as part of the processing. By applying this technology, documents can be processed at least 50 percent faster and with fewer errors, while also saving costs. For employees who carry out the customer onboarding tasks, automation means they can focus on the more complex matters so their job becomes more challenging and more focused on providing service. This allows the organization to distinguish itself even more. Considering that is unstructured, you can also imagine that accelerating customer onboarding with IDP is just the tip of the iceberg of what we can do with our platform. For example contract management, automating invoice processing or complete electronic mailrooms and digitally handling insurance claims. All these processes involve a lot of documents and manual actions. Huge efficiency gains can also be made in these areas.
