ABDULLAH HUMAYUN SHAFI

Provided analytics solutions to global third-party risk managers and executives to drive decision making and future course of action.

Developed monthly work forecasts using holt-winters forecasting model using time-series data in Python. Model is currently deployed and used to optimize deployment of personnel across global third-party risk management. Model is operating with an accuracy score of 84%.
Developed supplier category classification model using support vector machine models in Python’s SKLearnlibrary. Model is being currently deployed as a quality control tool to assist risk advisors in ensuring category of supplier is correct.
Developed dashboard using Power BI to inform lifecycle of third-party risk management. Modeled and cleaned complex historical data using SQL. Enhanced analytics capabilities by using historical data to evaluate lifecycle. Project led to 3% reduction in onboarding times for suppliers.
Led project to incorporate data from sources outside of TPRM database. Incorporated online incident reporting database, using python ‘Fuzzy Match’ library to clean and join incident reporting supplier data with TPRM supplier data, adding critical data points to holistically evaluate supplier performance.

Partnered with business teams to improve revenue outcomes for BMO using data driven decision making.

Successfully led project to optimize personal line of credit mortgage cross-sell product. Analyzedcustomer segment level delinquency, loss and balances data to improve approval rates by altering automated exclusion criteria. Project implementation led to 105% increase in mortgage cross-sell approval rates.
Collaborated with business and technology teams to overhaul SLOC (Student Line of Credit) product policy. Provided analytical support to business teams by providing originations data and loss forecasts. Attained by-in from senior risk executives for project execution. Project is under implementation and expected to increase acquisition growth by 35% annually and RAR by $8.3 Million over 3 years.
Successfully deployed strategy monitoring self-serve tool using Power-BI. Tool is being used by business and risk teams to monitor portfolio risk metrics.

Implemented solutions to drive firm wide productivity and provided analytics for business optimization

Led development of financial model and feasibility study for flagship strategic initiative for the establishment of an oil condition monitoring laboratory in partnership with Engie-Laborelec.
Led development of forecasting infrastructure at InspecTestleading to consolidation of forecasting data providing a birds-eye view of firm revenue backlog, expected profitability and cashflow requirements.
Presented monthly financial results to company’s board of directors.

Counsello's Team