Client Background
Challenge
The client’s title deed inspection process was largely manual, error-prone, and time consuming. A case documentation typically consisted 50-80 pages including multiple types of documents such as conveyance deeds, property index, general index, and affidavits. The insurer examined around 30,000 such cases per month. The immense quantity and document type complexity led to errors during the inspection process. The insurer wanted to enhance quality and reduce effort and defects in its title deed inspection process.
Solution
Wipro’s Artificial Intelligence platform HOLMES was implemented to make the insurer’s title inspection process efficient. HOLMES utilized Natural Language Processing to go through all documents in the docket and extracted relevant information based on business rules. On the basis of earlier purchase and sale transactions, and rules and extracted data, it got a contextual understanding of the documents and arrived at a ‘Good Starting Point’ (that asserts the title to the property) to begin the examination.
Through Property Index chaining and vesting details, the solution then established a relationship between the granter and the grantee. Based on General Index, it identified potential disputes and risks.
Business Impact
Implementation of Wipro HOLMESTM as a solution for the insurer’s challenges led to improvements in productivity, accuracy and risk identification. HOLMES enhanced its decision quality and reduced due diligence efforts through risk identification during the inspection process.