Manager - Revenue Assurance and Fraud management

Roles & Responsibilities:

• Perform the RA controls using the revenue assurance tool and identify leakages.
• Analyze relevant data and produce meaningful reports capturing root cause analysis of the issues identified, magnitude of the issue and the recommended solution for the same.
• Regularly monitor the fraud alarms, identify frauds and execute appropriate action to arrest the fraud.
• Create rules in the fraud management system to generate alarms for potential frauds.
• Identify the potential fraud risks and suggest appropriate controls for the same.
• This role will require interactions with most teams internal to Lebara at management and operational level.
• Role holder will also need to coordinate technical support from the external suppliers of Fraud and RA tools.
• The role holder will analyze and propose process improvements wherever necessary to the line manager for management buy in.
• Validate new product implementations as part of the UAT.
• Validate the invoices received from MNOs.
• Perform dispute reconciliation arising from carrier billing settlement and provide appropriate recommendations.
• Perform proactive payment analysis to identify payment frauds and avoid chargeback losses.
• Work in both Revenue Assurance and Fraud Management activities.

Skills & Expertise:

• Extremely strong professional background in Telecom Domain.
• Good working knowledge of revenue assurance processes within a MVNO/MNO business covering Retail, Wholesale and Interconnect revenue and cost streams and functional areas including but not limited to Switch, IN, Mediation, Rating and Billing, Suspense, Top-up and Opt-in and distributor commissions.
• Fraud Management working knowledge is an added advantage. Should be open to learn fraud scenarios/techniques and work in FM activities.
• Excellent data analytics and data manipulation/visualization skills. Experience of using MS SQL desirable as this the primary analytical software used by the wider team.
• Able to manipulate big data, interpret complex results and distil salient information to stakeholders of different levels.