NEED FOR ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

Transcription

1 Minimize Risk NEED FOR ARTIFICIAL INTELLIGENCE & MACHINE LEARNING Maximize Compliance Akshay Chopra

2 Technology Over the Years Heuristic Approach Decision making based on prior experience and context Rule based Approach Monitoring mechanism based on international standards, regulator recommendations & Internal controls Risk based Approach Alerting mechanism based on multiple dimensions and characteristics Algorithmic Approach Scientific method of generating and working transaction alerts Adaptive Approach Deploying new age tools and visualizations to expedite decision making Optimum State Integrated human intelligence and machine computation

3 Current Landscape Source Data Rules Library Rules Engine - User Defined - In-built - Manual Scoring Alerts & Cases Assignment Rules Assignment Engine - Rule - Customer Type - Product Type - Risk - Branch / Zone - Segment Out of the box, 3 level, scalable to n levels Forward Forward Round Robin Load Balance Central Que Analyst Reviewer Approver Re-Assign Re-Assign Comments Docs, Links & Tags Reminders & Escalations Notifications

4 Case Study 70M+ customer records across 5 business lines and 10 disparate systems spanning branches for a large bank Total transactions over last 6 months 1.8 Billion On Site Deployed Model 511, % 15.6% 79.8% Events / alerts HIGH MEDIUM LOW 172,643 Cases 48 RULES 330 BENCHMARKS 120,293 Customers

5 Case Study Continued.. 172,643 Cases 1,391 STRs or SARs 08 False Positives 171,244 Closed 0.8 % Alert to STR / SAR conversion ratio 1 % Global Average* * Accenture 2017

6 Introducing Artificial Intelligence

7 Success Factors for AI Transformation 01 Use Cases 02 Data Ecosystems 03 Technique & Tools 04 Workflow Integrations 05 Organizational Intent

8 Machine Learning 1. Supervised 2. Unsupervised 3. Re-enforcement

9 What are the possibilities? Ke Jie

10 What are we doing? 1.7% HIGH 4.8% MEDIUM 93.5% LOW Risk Variables Risk Categories 4.6% HIGH Risk Categories Insurance Customer Type; Length of Relationship; Occupation; Industry Sector; and KYC Compliance Customer Demographics 15.6% Risk Variables Geography MEDIUM 79.8% LOW Risk Factors Less than 1 year One to three years Greater than three years Risk Factors 1 Product Transaction

11 What are we doing? continued.. 1,391 STRs or SARs 0.8 % 50 %

12 Success Story Paypal cut its fraud false alerts in half by using an AI monitoring system that can identify benevolent reasons for seemingly bad behavior.

13 Suspicious Transaction Analysis & Reporting Next Generation Transaction Monitoring & Data Visualization

14 Introducing Jocata Former ex-deloitte colleagues in the Forensic & Dispute Services Practice of Deloitte out of New York Several decades of our collective experience channelled into building a sophisticated ecosystem technology (ET)platform that provides an integrated view of business, risk, operations and compliance Founded November member team primarily based in Hyderabad 03 Senior Management 10 Business Analysts Satellite NYC & Pune offices 1 Sales Personnel 3 Product Managers 60 Dev. Engineers Continuous and dedicated investments into R&D has led to the development of our advanced platform. 10 Test Engineers 04 Helper Staff 10 Support Engineers 04 HR & Finance

15 Our Mission Minimize Risk To provide a sophisticated technology framework that goes beyond meeting the complex global requirements for Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations by creating a high-quality, standardized and reusable data asset that can be used to drive business growth Maximize Compliance

16 CLIENTS & PARTNERS Leading global, local financial institutions and trustworthy partners

17 LEADING INNOVATION Jocata selected as one of eight companies in Asia leading innovation in financial technology by a panel of global banks Jocata selected as one of 20 most promising financial technology providers.

18 THANK YOU Strong KYC, AML processes and controls are at the heart of inter-dependencies and linkages within a global organization, offering invaluable client knowledge that can be turned into a data asset