- Managing Director
- T: +91 22 5036 5030
- M: +91 98 7183 4301
- 20th Floor, Oberoi Commerz II
- International Business Park, Oberoi Garden City
- off Western Express Highway
- Mumbai, 400063
- T: +91 22 5036 5040
- Bachelor of Commerce, University of Delhi
- Master of Business Administration, Sikkim University
- Software Engineering Diploma, National Institute of Information Technology
- Computer Forensics & Investigations
- Cross-border Litigation
- Litigation Support & Consulting Services
Ankush Lamba specialises in forensic data analytics (FDA) with focus on data integrity, financial data investigations, anti-bribery & anti-corruption (ABAC) investigation, fraud risk assessment (FRA) across industry verticals.
Mr. Lamba's industry expertise spans pharmaceutical, oil and gas, automobiles, retail, toll/construction, e-commerce sector and has demonstrated experience in the domains – procurement to payment (P2P), sales and distribution, travel & expense, arbitration and quality control.
- Led and managed a team for setting up an FDA approach for US FDA & MHRA data integrity review for life sciences companies in India.
- Implemented proactive forensic data monitoring solution in the quality control lab for pharmaceutical company. An automated monitoring solution to support pharma companies in case of GxP issues.
- Led an ABAC review for one of the largest automobile companies involving review of datasets from 28 countries. Set up the approach and created automated algorithm in SQL software to identify fraud patterns and created dashboard reporting for P2P and expense business processes.
- Developed and implemented automated ERP transaction monitoring solution to analyse and identify red flag transactions in financial accounting data in near real-time basis.
- Assisted client (Indian Bank, New Paper & Global Engineering Company) on reviewing and setting up a fraud monitoring system (FMS).
- Assisted a leading law firm in dispute resolution between three joint venture partners and the Union of India. Provided FDA support in computing the cost from three legacy ERP systems spanning over a period of 18 years.