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ING
With more than 10 million customers, ING is one of the largest banks in Germany. Its range of services extends from checking accounts and mortgages to consumer loans and securities solutions for both private and business customers.
Each year, ING processes six to seven million documents through its input management system—ranging from forms and emails to scanned documents. Using the AI-based OmnIA platform from Insiders Technologies, the bank increased automation in its incoming mail processing to approximately 80 percent.
Industry
Banking / Financial Services
Product
OmnIA
Volume
6–7 million documents per year
"We were pleasantly surprised by the speed at which the quality metrics improved. At the beginning, we weren’t aware of the full extent of the potential for efficiency and reducing the workload—which makes the improvements in our daily work all the more evident today."
Eyal Azani
Product Owner for Digital Document Processing and Email Handling, ING
Project Overview
What was the
initial situation?
- Millions of documents annually via various channels—mail, email, online banking uploads, and intermediaries
- A system landscape that has evolved over time and is highly fragmented, requiring significant maintenance effort
- Several hundred document classes across dozens of processes and subprocesses
- Even documents received digitally had to be manually reviewed and prepared first
Why the decision
Insiders?
- Comprehensive selection process involving multiple vendors; decision made in favor of OmnIA from Insiders Technologies
- Existing standard features such as automatic splitting and merging of documents
- Efficient training options that business users can utilize without developer expertise
- High degree of standardization combined with flexibility for new requirements
How was the solution implemented?
- Establishing OmnIA as a central, cross-channel platform for all incoming documents
- Automatic detection of document boundaries, splitting, and merging of content
- Classification and management of approximately 400 document classes across two client environments
- Independent training and customization of classification models by business users
How can success
be measured?
- Automation of document creation increased to about 80 percent
- Classification improved to a stable rate of about 80 percent
- Noticeably faster turnaround times and significantly reduced manual post-processing
- Optimized user interface shortens the processing time per document during post-processing
What are the next steps?
- Gradual integration of additional features and further automation, such as for data extraction
- Flexible adaptation to new products and document classes, for example, as part of new account offerings
- Long-term further development of digital document processes based on the OmnIA platform