Rapid Regulatory Response
VALUE PROPOSITION
- Achieving a major Digital Transformation leap, by utilising ELEMENT’s Knowledge Graph to enrich a detailed network of clients, facilities, and document attributes
- Improving adaptability to regulatory changes and evolving business needs by using low/no code customisation and automating the preparation of management dashboards and reports
- Decreasing labour-intensive tasks by providing a process-centric, AI-embedded application
- Enabling the bank to use a golden source of customer data for cross-functional applications and cross-sale opportunities
Enablement of a leading British bank to mitigate a regulatory change impacting hundreds of thousands of documents, by utilising AI to automate and expedite the review process
BACKGROUND
The bank was required to migrate all IBOR affected facilities that were maturing beyond a given date
A review of hundreds of thousands of documents from multiple business units was required to create a complete picture of the facilities impacted by IBOR
Heavy reliance on on-premise applications and bespoke spreadsheets limited the bank’s ability to identify all affected facilities without extensive manual labour
Fragmentation was compounded by a lack of integration between on-premise systems in multiple jurisdictions, and the absence of workflows, dashboards and data pipes
TARGETS
- Build a unified knowledge base, seamlessly correlating information about clients, related facilities, and document attributes across various internal sources
- Categorise structured and unstructured (text) documents, and determine whether they are IBOR related and whether they mature by a specific date
- Automate workflows to link and match documents to approved facilities and record them in the relevant systems
ADDRESSING THE NEED
- Constructed a comprehensive Knowledge Graph integrating the bank’s core infrastructure — including document repositories, and e-share and core loan systems, to enrich profiles of clients, facilities, and documents, along with their attributes
- Configured a document parsing engine to analyse structured and unstructured documents and automatically identify attributes based on a set of facility dimensions and characteristics, using Natural Language Processing
- Created workflows to assist the bank’s stakeholders in choosing the right remediation process by uncovering patterns in contractual documents and preparing bespoke management dashboards and reports, using AI technologies
Other Use Cases
