Kamran Yawar

Leading the development of advanced analytics, AI and machine learning solutions within the Risk consulting practice. Helping embed AI in new offerings to clients with a risk lens attached.

• Managed the delivery of Advanced Analytics and Data Science projects for one of the largest EY global accounts in the oil and gas sector. Collaborated with auditors worldwide to develop advanced analytics approaches, including rules-based and machine learning methods, to drive innovative solutions.

• Led the deployment of multiple machine learning pipelines, with a particular focus on an anomaly detection solution utilizing deep learning algorithms. This solution enabled clients to detect fraudulent activities within their financial transactions. By leveraging Kernel-Shapley, we provided clients with the ability to interpret the characteristics of anomalous data, even when using complex deep learning methods.

• Developed risk scoring models using Random Forest Regressor that helped identify risky entities within our client's businesses. The models incorporated metrics from financial transactions, Internal Audit reports, historical trends and Fraud indexes.

• Led the deployment of financial transformation project, that included big data analytics, controls and risk monitoring and machine learning solutions, success in which helped in establishing a £1M+ future business pipeline.

• Fostered team expertise in data science by designing and implementing a comprehensive learning pathway, enhancing the team's skills and knowledge in machine learning techniques.

Established the data analytics services for the firm's Pakistan branch, empowering the team to provide our clients with data-driven solutions for performance improvement and sharper insights.

• Performed advanced analytics as part of a major environmental restructuring project, overseeing workload assessments, capacity planning, and environmental modelling. Utilised machine learning models to conduct predictive analytics on environmental data.

• Analysed root causes of sales decline, identifying supply chain, distribution, and marketing issues through descriptive analytics.

• Performed K-Means clustering analysis to identify high-risk locations and detect anomalies in training center performance for a government skills development program, enabling the identification of underperforming and potentially fraudulent centers through data-driven insights.

• Conducted thematic analysis, utilizing Tableau and predictive models to optimize sales, order processing, and marketing strategies.

• Supported World Bank by identifying top investment sectors in Pakistan, using advanced statistical techniques to assess FDI and export impacts.

• Demonstrated

Helping improve banks risk profile by deploying Analytics and Advanced AI techniques, specifically for Markets.