IDC PlanScape: Augmenting Compliance in Financial Services through Artificial Intelligence

IDC PlanScape: Augmenting Compliance in Financial Services through Artificial Intelligence

This IDC PlanScape provides business and technology leaders in the financial services industry with a strategy for ensuring compliance through the implementation of artificial intelligence (AI) solutions. The study provides a high-level definition of AI, presents compelling reasons for AI implementations, outlines AI deployment phases, identifies key stakeholders, and highlights challenges financial organizations implementing AI must overcome."Financial services organizations have a fertile opportunity to ensure compliance via AI implementations. The need to analyze Big Data and to replace or complement labor-intensive and rules-based legacy systems presents an excellent case for machine learning and natural language programming algorithms to help curb financial crime." — Associate Research Director George Briford, IDC Financial Insights

Please Note: Extended description available upon request.

IDC PlanScape Figure
Executive Summary
Why is AI in Financial Services Compliance Important?
Minimization of the Risk of Business Restrictions and High Fines
Improvement of Process Efficiencies
Potential to Replace Legacy Technology with Models and Algorithms
Provision of Agility to Compliance Supervisors
What is AI in Financial Services Compliance?
Who are the Key Stakeholders?
How Can My Organization Take Advantage of AI TO ENSURE Financial Services Compliance?
Implementation Challenges
Technological Challenges
AI Architecture: Cloud Adoption versus Internal Server Deployment
Organizational and Process Challenges
Demanding Steps: From Model Learning and Engineering to Validation
Partner Selection
Skills and Capabilities ("Buy versus Build")
Regulatory and Legal Challenges
The Key Phases of AI in Compliance Implementation
1) Build the Fundamentals
Develop Basic Skills
Formulate Business Priorities
2) Play and Learn
Select the Variables: Algorithm Learning and Data Modeling
Test the Explainability
3) Apply and Improve
Model Validation
Test the Scalability of the Overall Solution
Advice for Technology Buyers
Related Research

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