Branchless Banking Risk Data Strategy Lead

at Telenor Microfinance Bank Limited
Location Islamabad, Pakistan
Date Posted August 16, 2019
Category Banking & Financial Services
Job Type Full-time
Education Requirement Bachelors/Masters
Career Level Mid Level
Experience 4-5 Years
Base Salary Competitive Salary
Street address Islamabad


            • The Branchless Banking Risk Strategy Lead plays a lead position in Risk’s Strategy function through data analysis and is responsible for overseeing activities of the junior team member ensuring proper execution of duties and alignment with the business’s strategic ambitions. This person is responsible for the creation of new data analysis, customer and fraudster profiling capabilities for the risk function and taking informed decisions following identification of frauds, campaign misuse and fund loss.

              The role proactively works with stakeholders within and outside the Risk function in order to input the appropriate risk parameters for monitoring of customers, fraudsters and trends. The person will design innovative analytic models, utilizing a blend of contemporary and traditional data mining techniques, which he applies to both structured and unstructured data sets.

            • Identifying and monitor key business risks, preventing fraud / campaign abuse scenarios, identifying fund loss and realizing the data needs of the Risk function.
            • It is also the role of this position to build and mentor the Risk function’s analytics talent through role definition, recruitment and development of a team of interpreters that will move the department’s agenda forward as well as guiding reportees through the execution of their duties and encouraging their professional growth.
            • Play a strategic role with continuously improving the risk rule/models to identify and prevent fraud and fund losses and employing the latest in machine learning in the department.
            • Scope, design and implement risk machine-learning models to support the business’s numerous initiatives and programs with a view of achieving overall objectives and targets.
            • Providing analytical support to the Risk Management team in order to prevent fraud, mitigate risk, prevent revenue loss and cut down on operational losses.
            • Identify and monitor the potential risks due to fraud in all areas of the customer lifecycle of our e-wallet and related services.
            • Identify, analyse and escalate any key items regarding fraud or potential fraud and revenue losses.
            • Launch investigation utilising the investigation team and coordinate with them on management reporting.
            • Designing and implementing a fraud risk and fund loss strategy.
            • Working with cross functional teams to design and implement risk and fraud control strategies based on data analysis.
            • Keep updated with developments and trends in fraud and risk and regulatory landscape and advise management on key issues that have the potential to impact the business in particular related to payments, financial services, fintech and e-commerce.
            • Play an analytical role by driving experimental data modelling designs within the business. Run A/B tests in order to evaluate changes in the business’s product/services. Track business’s performance against data analysis model and monitor trends in key business KPIs, providing valuable insights to the risk department for monitoring against strategic ambitions.
            • Draft reports for reporting on departmental performance and presenting recommended models and departmental strategies.
            • Maintain a deep understanding of business’s dynamics. Takes initiative and conducts exploratory data analyses and experimental designs, which will help business to better understand trends and behavior within these markets and settle on the most suitable strategies to drive success and achievements of goals and targets.
            • Analysis of rich user and transaction data to surface patterns, trends, and bugs that help improve fraud policies and processes and contribute to fraud prevention mechanisms.
            • Experience in data mining
            • Understanding of machine-learning and operations research
            • Knowledge of R, SQL or Python; familiarity with Scala, Java or C++ is an asset
            • Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
            • Analytical mind and business acumen
            • Strong math skills (e.g. statistics, algebra)
            • Problem-solving aptitude
            • Excellent communication and presentation skills
            • Exposure to fintech, payments, e-commerce is an advantage
            • Ability to exercise good judgment and mature mindset in approaching complex issues
            • Inquisitive by nature and able to work with data to uncover root causes and identify trends
            • Ability to work in a start-up environment and manage multiple priorities
            • Ability to take initiative in a fast-moving environment
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