Industry Focus : Information Technology and ITES
The Issue : Manual cross reference of authenticity in KYC documents.
The Solution : A Machine Learning BOT that can detect anomalies in documents.
The Summary : Our customer from the IT industry required to to optimize their KYC process. Before we started, this process involved manual verification of uploaded documents for clarity, authenticity and accuracy while the person responsible for this workflow also had to fill in details on a separate form. This process of verification and data entry was resource intensive and left a lot of room for error. Each verification could take anywhere from Two minutes to Fifteen Minutes based on the document type and required over 20 executives to process.
The Result : SIFT stepped in to understand the entire 10 point workflow which was dotted with lots of manual overheads and approval processes. We trained a machine learning BOT to understand a sample size of acceptable KYC documents, using this trained BOT, we were able to process KYC documents directly to the final stage without any human intervention. The small percentage of documents which were unreadable were automated by another flow requesting for reupload from the user. Using SIFT’s automation approach, we were able to help our client downsize the ineffective and slow 20 member team to a sleek efficient 2 member team that handles only escalations now. The customer had a budget surplus of 83% within 6 months of this solution being operational, in that department.