Automate data entry and information gathering
Speed on-boarding and periodic review using intelligent automation to pre-populate information from multiple sources and extract concepts from data sources and negative news, minimizing manual tasks, analyst subjectivity and the potential for data entry errors.
Gain on-going insights from internal and external data
Verify company information and uncover hidden relationships by linking previously unconnected data both within the institution as well as from external sources, during the on-boarding process as well as when customer and counterparty details change.
Speed investigation, review and reporting
Extract concepts from unstructured data such as negative news, presenting analysts with a prioritized list of relevant articles as well as the related entities and high-risk keywords to quickly understand context, and automate dossier generation for standardized recording for future.
Modernize your approach without an overhaul
Take advantage of Watson capabilities like AI, machine learning, natural language processing and intelligent automation by augmenting existing systems instead of replacing them, creating a faster time to value. In addition, deploy quickly based on your institution’s needs as a Software-as-a-Service (SaaS) or on-premise implementation.
A platform built for change
IBM Financial Crimes Insight runs on IBM Cloud Pak for Data, providing financial institutions an advanced data science tool kit to build and govern models as well as a flexible, containerized deployment architecture. IBM Cloud Pak for Data manages the entire AI lifecycle, from preparing data for AI use to model creation, deployment and governance. In addition, Red Hat OpenShift offers the ability to deploy Financial Crimes Insight anywhere, as well as access management and audit capabilities.
Your partner for success
To maximize the impact and success of Financial Crimes Insight, we offer a full range of additional services, from base implementations to complete platform and process transformation. These include: - Architectural Design & Data Integration - Data Governance Organizational & Process Transformation - Model Development & Model Governance