Omar Aynaou

Recruited within the Personal Insurance Department to supply collection campaigns with an objective set by the CEO: recover €5M in due contributions. Client portfolio with significant debts (provident/health, internal/delegated management), recurring DSN anomalies, manual processes (formal notice, internal control), fraud, absence of a centralized cube for portfolio management and indicators.

Develop contribution/debt recalculation models for collection campaigns

Initiate/develop fraud detection (provident, collective/individual health)

Detect/correct DSN anomalies + optimize internal control/formal notice/quality data

Design data cube + client portfolio management dashboards

Fraud: Initiation of fraud detection work (provident/collective/individual health)

DSN: Algorithms for detecting DSN declaration anomalies

Open data (Insee/Bodacc/Infogreffe): Monitoring of closed companies (liquidation/insolvency) receiving benefits without contributions → termination

Data Cube: Technical/financial/operational indicators (contracts/clients/management/claims/benefits/contributions)

Automation: Formal notices, internal control sampling, client interaction tracking

Data Quality: Alteryx workflows + internal/DSN consistency vs. open data (status/activity code)

Management: Tutoring of an intern + functional management of Data Analyst

Collection models → €5M recovered (CEO objective met)

Collection modeling decision tree

Collection management monitoring (amounts to be collected/collected)

Fraud work: scenario scoring + DSN anomaly algorithms in production

Open data monitoring for closed companies operational

Cube + Power BI dashboards + benefits KPIs (Eckert)

Documentation

Facilitation of steering committees and COMEX meetings

SAS Enterprise Guide, Excel, Power BI, Alteryx, Python.

Within the Inventory Service of the Technical and Financial Department, recurring difficulties in extracting and validating benefit/contribution indicators. Dispersed manual processes, absence of a centralized data cube, obsolete processing limiting risk management. Urgent need for optimization and automation for real-time monitoring.

Complete overhaul of extraction and indicator calculation processes

Design of a unified data cube for benefits/contributions

Optimization of existing tools and proposal of innovative new methods

Creation of dynamic dashboards for risk management

In-depth analysis of existing processes (output flows/indicators)

Overhaul of processes + design of data cube with indicator calculations

Global optimization of inventory service tools/processes

New methods: segmentation of procedure codes by text analysis, automatic/dynamic data backup, alerts for high death benefits, identification of client company hierarchical structure

Calculation of new risk management indicators + documentation of processes/tools

Power BI dashboards (health/provident benefits performance, contributions)

Participation in DSN base design + monitoring of work stoppages + integration of data from delegated managers

Data cube + Power BI dashboards deployed in production

New processes documented + training of the inventory team for complete handover of new processes and for maintenance

Facilitation of scoping workshops and deployment

Impact: Near real-time indicator extraction, improved risk management, estimated 70% productivity gain on monthly extractions

SAS Enterprise Guide, Excel, Power BI.

Support for 15+ Data Analyst trainees (transfer of technical/business skills).

Project scoping, technical coaching (Excel/SQL/R/Python/Tableau/Power BI/Knime), defense evaluations.

+90% success rate for coached cohorts, recognized pedagogical expertise.