Faisal Rafiq is a seasoned Quantitative Modeller at Data Drill, bringing over 18 years of extensive experience in the banking sector, particularly within the Credit Risk division. His analytical prowess and client-focused approach have made him a pivotal figure in the data and analytics industry....
Faisal Rafiq is a seasoned Quantitative Modeller at Data Drill, bringing over 18 years of extensive experience in the banking sector, particularly within the Credit Risk division. His analytical prowess and client-focused approach have made him a pivotal figure in the data and analytics industry. At Data Drill, Faisal specializes in developing sophisticated predictive models that empower clients to make informed decisions and optimize their strategies.
One of his key projects involves Marketing Mix Modelling (MMM), where he has successfully developed multivariate regression models to assess the impact of various marketing campaigns on sales performance. This initiative not only provided valuable insights into the effectiveness of marketing strategies but also enabled clients to allocate resources more efficiently, maximizing their return on investment.
In addition to MMM, Faisal has made significant contributions to Collections Modelling and Contact Strategy. By creating bespoke models, he has helped large businesses identify high-risk customers, enabling them to implement targeted interventions that reduce the likelihood of missed payments. His expertise in IFRS9 Modelling and customer insight further enhances his ability to deliver tailored solutions that meet the unique needs of each client.
Faisal's skill set is complemented by his proficiency in econometrics, statistical modeling, and predictive analytics, along with a strong command of Visual Basic for Applications (VBA). His commitment to leveraging data-driven insights to drive business success positions him as a trusted advisor in the ever-evolving landscape of finance and analytics. Through his work at Data Drill, Faisal continues to set benchmarks for excellence in quantitative modeling and strategic decision-making.
