Conduct Risk – Frameworks & Analytics

The terrain of Conduct Risk within the Financial Services sector is dynamically shifting. Technological strides are aiding firms in crafting innovative methods and analytics for adeptly detecting and overseeing conduct risk. With heightened scrutiny from supervisory authorities and significant fines imposed on major institutions in recent years, the imperative for effective Conduct Risk Management looms larger than ever. It stands as a pivotal element in a bank's overarching strategy to uphold integrity and safeguard its reputation. New analytical techniques are helping firms gain the upper hand in terms of a proactive approach towards Conduct Risk.

Sia Partners is poised to assist firms in forward-thinking their Conduct Risk strategy, offering expertise in key areas such as:

• An Initial Assessment of your firm’s current Conduct Risk strategy
• Analyse current gaps and their potential impacts, and make recommendations for future enhancements
• Analysis of your data capture elements – e.g. Monitoring systems, Compliance reports, internal/external communication channels etc
• Recent and emerging Analytics Techniques – Natural Language Processing, Machine Learning. Time Series and Network Analysis 

Conduct Risk Analytics

Thanks to new technologies and increasingly advanced data processing, companies are in a position to anticipate and detect conduct risks more effectively. To do this, they need to collect a wide range of data (customer behaviour data, social network data, employee habits, financial data, etc.), coupled with detailed data analysis using a variety of tools (statistical tools, sampling tools, real-time analysis tools, etc).

Key Levers to capture meaningful metrics:

• Metrics Capture – HR applications, GRC platform, Surveillance systems etc
• Analytics – Trends in breaches per Trading Desk/Unit/Region, trends on specific individuals
• Insights – Going further with analysis on certain individuals/desks we can identify gaps in training, lack of understanding, potential cultural issues etc
• Decision Making – Specific insights can aid managers in making key decisions and help proactivity in mitigating conduct elements

Conduct Risk Analytics – Data Capture Elements:

• Activity Logs – Helps identify patterns of behaviour and detect potential misconduct
• Monitoring Systems – Used to proactively identify and mitigate conduct risks, ensuring compliance with policies etc
• Customer Complaints – Helps identify potential conduct risks, improve customer experience and address any grievances
• Compliance Reports – Provides insights into the organisation’s adherence to regulatory requirements
• Performance Data – Helps assess the correlation between conduct risks and financial performance
• Communications – Helps detect potential misconduct, inappropriate language, or breaches of confidentiality
• Social Media – Enables identification of reputational risks, public sentiment, and conduct-related controversies
• Behavioural Data – Helps identify deviations from expected norms and patterns that may indicate conduct risks or unethical behaviour

Illustrative Analytics Techniques

• Statistical Analysis – Study relationships between variables and identify significant trends
• Time Series Analysis – Examine data variations over time to identify trends, cycles or seasonal patterns
• Comparative Analysis – Compare data across different units to identify performance differences, behaviours etc
• Network Analysis – Study relationships and interactions between departments and entities
• Cluster Analysis – Group similar data points into clusters or segments to identify common risk characteristics
• NLP Analysis – Extract information from documents and communications to identify language patterns and sentiments
• Real-Time Data Analysis – Analyse data in real-time to detect and respond promptly to risky behaviours or events
• Predictive Modelling – Build models to anticipate future behaviours or outcomes based on historical data