Technology & Analytics in implementing a risk based approach Banking Compliance Symposium (Sri Lanka) Aug 2016

Necessary Features Analytical Tools Profiling & Peer Analytics Rule Builder Rule Library Profiling & Peer Analytics Analytical Tools Comprehensive Case Management Workflow Management Link Analysis Rule Simulations

Customer Demographics Risk Profiling Customer Risk Categorisation (CRC) is the process of assigning a value to the attributes of a customer of a financial institution, grouping them by and identifying the higher, the neutral (medium) and the lower risk customers. Risk Variables Customer Demographics Product Transaction Risk Categories Geography Customer Type; Length of Relationship; Occupation; Industry Sector; and KYC Compliance Risk Categories Insurance Risk Variables Less than 1 year One to three years Greater than three years Risk Factors Risk Factors1 1 –for illustrative purposes only.

Transaction Monitoring Patterns help in identifying complex activities involving multiple rule breaches over a period of time Aggregating Transactions into Events, Patterns, Alerts and Cases for effective, centralized and customer level monitoring Rules are the basic monitoring algorithms which run as per benchmarks defined All the Events and Alerts triggered for a customer are presented as a single case of consolidated investigation Pattern 1 Alert 1 Alert 2 Alert 3 Pattern 2 Event 1 Event 2 Event 3 Event 4 Event 6 Event 7 Rule 1 Rule 2 Rule 3 Event 5 Case 1 Non-patterned events are also displayed in the case Customers who trip rules will trigger events which are then used for tracing patterns Events of a customer are analyzed to find patterns which are in turn marked as alerts

Workflow Analyst Reviewer Approver Rules Library Assignment Rules - Customer Type - Product Type - Risk - Branch / Zone - Segment - User Defined - In-built - Manual Source Data Alerts & Cases Rules Engine Assignment Engine Forward Forward Analyst Reviewer Approver Re-Assign Re-Assign Comments Documents, Links & Tags Notifications Reminders & Escalations

Rule Builder GUI based Rule builder to assist business, risk and compliance analytical teams to build scenarios for detecting patterns

Peer Groups Dynamic self and peer profiling to establish base-line profiles for customer segments using customer demographic and transaction data.

Analytics Dashboards to manage and prioritize customer alerts.

Customer Level View Data visualizations of customer transactions overlaid with summaries, alerts indicators and key information changes quickly allow analytical teams to hone in on areas of relevant interest

Peer Analytics Comparison of transaction Peer Profiles can indicate customers who can potentially be offered more products/incentives due to use of a particular channel or are high risk and are conducting potentially suspicious activity

Customer Networks

Network Analysis Quick configuration of network depth is an essential feature for analysis Filters on Transaction Types, Channels, Counter Countries, Aggregates and Volumes are key for quickly dispensing on false positives and homing in on the most relevant & crucial items

Simulation Rapid Simulation to better deploy resources and understand business, compliance & risk patterns on historical data is a key component of automated analytics

Simulation Statistical distribution patterns are essential to save time, money and consequently effort on a large scale enterprise analytics & risk management. Such analysis helps teams prioritize and focus efforts on higher risk cases/alerts or patterns

Thank You Questions rahul.jandhyala@jocata.com