Financial Crime Investigation
Accelerate the Underwriting process with better faster analysis of unstructured data
For: Financial Regulators
Matching names of people and organizations from disparate information sources across multilingual data from across the globe is a daunting challenge. Agolo Entity Analytics lets you identify and link names to ensure financial crimes don't go undetected.
With the increasing complexity of financial transaction, traditional methods of detection prove to be inadequate. Identifying names of individuals and organizations across various languages, document types, and formats requires more advanced techniques than traditional methods offer.
Agolo provides an AI-based, self-learning system for extracting entities and transforming them into real-world Identities eliminating users from needing to have specific knowledge of who or what they are looking for. The AI system processes content the same way an experienced Analyst does, by comparing names and looking at contextual information to resolve that entity mentioned to an Identity.
For: Professional Underwriters
The exhaustive task of sifting through disparate structured, semi-structured, and unstructred data sources can slow down underwriting processes — but with Agolo, ensure lightning-fast, informed underwriting decisions every time.
Underwriting demands precision. Every decision is based on myriad data points, often scattered across various sources. An underwriter's efficiency hinges on how quickly and accurately they can access and interpret this data.
Accelearte the underwriting process without stretching your team, all while reducing risk. Agolo transforms unstructured text into a searchable, identity-centric knowledge base that can augment structured and semi-structured data sources across your organization. The outcome? A unified data hub that equips underwriters with all the information they need at their fingertips. Accelerated processes, minimized risks, and enhanced decision-making efficiency become the new standard.