Risk Management: Understanding all risks – from the economic to the political – that could affect our global business, and offering guidance to all parts of the bank.
Job Purpose
• To source and transform data into information as input into effective credit portfolio insights and analytics for allocated PBB products/segments for the credit lifecycle for scored lending (e.g. originations, account management, collections) in line with PBB objectives.
• To automate relevant production reports to improve the reporting, data extraction and information preparation processes.
Key Responsibilities/Accountabilities
Business Requirements
• Sources appropriate data and prepares meaningful and accurate management information (MIS) for allocated portfolios to support Business, Operational, Credit and Finance Reporting.
• Collects and collates the appropriate data for report generation.
• Conducts in-depth analysis of user needs and prepares the appropriate reporting where required (based on urgency and priority)
• Executes all new reporting requirements.
• Provides the necessary big data where required based on business requirements.
Data Transformation and Reporting
• Validates data accuracy by performing standard reconciliation – remediates any data discrepancies or escalates for assistance where required.
• Optimises current reporting processes and provides input into the development of reporting processes to meet timelines.
• Automates relevant production reports to improve the reporting, data extraction and information preparation processes through using appropriate scheduling toolsets.
Reporting and Analytics process
• Extracts, stores, manipulates, processes, analyses and provides information for standardised and bespoke reporting.
• Continuously monitors and tests processes and data to detect errors in order to improve reporting efficiencies.
• Interprets data into information following collation of large sources of disparate data.
• Writes SAS/SQL coding in line with reporting requirements and as far as possible implements automated scheduling.
• Adheres to timelines for new and existing reporting requirements.
• Stays abreast of all changes of how the Customer Decision Engine (CDE) works to qualify and non-qualify customers for lending limits.
Trend Analysis
• Analyses portfolio trends and any changes thereof followed by a detailed investigation to determine the root cause – extracts the relevant account level data as input into portfolio reporting.
• Identifies and highlights data quality issues that affect the accuracy of insights and analytics.
• Keeps up to date with insights and analytics best practice to ensure new and improved designs and products provide improved value to stakeholders.
• Identifies and reports any portfolio risk appetite breaches across the countries.
• Prepares reports on ROE portfolio performance.
• Reconciles all the daily/weekly/monthly reporting outputs and resolves any issues identified (such as operational issues).
Governance
• Adheres to approved toolsets when setting up portfolio management reports.
• Adheres to data governance principles as prescribed by the Enterprise Data Office (EDO).
Knowledge sharing
• Upskills country stakeholders on principles of data extraction, transformation and visualisation.
• Shares knowledge and information on data coding with the Country and Head Office Teams.
• Tracks usage of measurement tools created.
Stakeholder Management
• Proactively communicates the progress of delivery of reporting requirements, where necessary.
• Discusses and negotiates timelines on reporting requirements (as it pertains to data) whilst ensuring regular standardised monthly requirements are still delivered (i.e. data extraction, manipulation and visualisation) and seeks line management approval where required if SLA’s could be breached.
• Manages and resolves escalated queries regarding data anomalies that are detected that impacts accuracy of reporting.
Preferred Qualification and Experience
A degree in business commerce or risk management or degree with a statistical focus e.g. BSc. SQL/SAS/Qlik proficiency is essential.
3-4 years experience in credit data analytics within a personal and business banking environment with specific focus on the credit life cycle. Experience in (preferably credit) data exploitation and business intelligence development and implementation. Experience in the extraction, transformation and visualisation of data using bank approved toolsets e.g. SAS / SQL / Python / Qliksense.
Knowledge/Technical Skills/Expertise
Behavioural Competency
Interpreting Data
Examining Information
Checking Details
Documenting Facts
Team Working
Completing Tasks
Meeting Timescales
Understanding People
Interacting with People
Exploring Possibilities
Producing Outputs
Taking Action
Upholding Standards
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