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Risk Remediation Platform

Wipro’s Risk remediation platform, built on Pega offers customizable UDA remediation for regulated industries, ensuring compliance.

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In highly regulated industries like financial services, insurance, healthcare, compliance risk remains one of the top agenda items for compliance leaders. Significant cases of fraud and mishaps have been reported throughout the industry in recent years, mostly due to spreadsheet-based data processing on User Defined Applications (UDA) applications, which are often not standardized and have limited to no auditable controls. Wipro’s Risk Remediation Platform is built on Pega, one of the industry’s leading AI decisioning and workflow automation solutions and is applicable to both Pega Cloud and On-prem installations. This platform provides a 100% configurable approach to UDA remediation. With the platform in place, highly regulated institutions can rapidly move from manual processes based on email and spreadsheets to an open-architecture-based model that combines the capabilities of Pega with an extract, transform, load (ETL) component using different tools and libraries.

Key Features

  • Flexible Input and output configurations: By integrating directly with upstream and downstream systems, the platform enables data to be sourced without human intervention, ensuring data integrity.
  • Role based access control: Integration with a corporate LDAP ensures role/group-based access to UDAs.
  • Business managed workflow: Each UDA is unique and has its own process flow. A dynamic workflow module allows users to configure the UDA process flow without any development effort.
  • ETL processes: Various file types can be used for input and outputs to match what’s required by upstream systems.
  • Compliance: Ensure adherence to regulatory requirements through standardized components and logic, version control, audit trails, and digital change management workflows.
  • Maker-checker capability: It also enables business determined ‘maker-checker’ capability.


=Wipro Limited

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