Quality Team That Adds Value
At Fortis, we have a collegiate environment that celebrates diversity. We are a team-based organisation, and it is essential to our business and to our success that everyone feels trusted and part of the team.
We embrace diversity and inclusion because it is the right thing to do, and we understand that they are vital to our success. Broadening our capabilities by leveraging diverse backgrounds and experiences is how we best serve our clients. As a global organisation, we need a global team of professionals, each bringing their unique perspectives to bear.
Tariq Ateeq
Tariq is a managing partner at Advance Analytica and is responsible for the strategic direction of the firm. He is an IT literate, quantitative risk professional, and qualified accountant with over 25 years’ international experience gained in blue-chip consultancy and financial services organizations.
He is a qualified Chartered Certified Accountant, London and holds an MSc in Information Technology (Southbank University, London) and an MSc in Risk Management/Financial Engineering (Imperial College, London).
Before starting Fortis Auxilium and Advance Analytica, Tariq held senior management roles in assurance functions of international/regional banks. He also has worked as an information technology and risk management consultant, financial/risk modeler, and external auditor in big four and the UK's National Audit Office.
His multi-discipline academic and professional background allows him to effectively manage and execute technically demanding and complex multi-functional international assignments. He has successfully led, developed, and managed multicultural and multidiscipline teams; implemented transformational changes; identified synergies during complex merger transactions; managed relationships with senior stakeholders including executive management and board members; and effectively liaised with international regulators such as the Federal Reserve Bank New York-USA, Federal Reserve Bank of Boston-USA, Financial Conduct Authority (FCA)-UK, Prudential Regulation Authority (PRA)-UK, The Swiss Financial Market Supervisory Authority (FINMA)-Switzerland, Monetary Authority of Singapore (MAS), Hong Kong Monetary Authority (HKMA), Saudi Central Bank (SAMA)-KSA, South African Reserve Bank (SARB), etc., with regards to interpretation of regulatory guidelines, scope of regulatory inspections, factual accuracy of the internal/external observations, remediation work to close regulatory observations, etc., concerning a wide range of areas and functions such as Information security, implementation of new IFRS, valuation control, credit/operational/market risk management practices, finance, risk, and pricing model methodologies, risk sensitivity-based P&L (RSBPL), etc.
Tariq is well-versed in internal audit and risk management practices, including building, validating, and reviewing financial and risk models. He has managed complex FinTech consultancy projects which involved system testing, implementation, and business process analysis.
Examples of some of his financial and risk modeling projects include:
- Designed and developed a VBA based platform which assisted in validating financial models;
- Stress tested models across numerous sectors including structured finance, private equity, securitization, M&A, and corporate restructuring;
- Developed VBA based automated tool which risk assessed businesses and functions of a major global bank and produced risk reports and heat maps;
- Reviewed and validated risk management framework, operational, credit, and market risks, economic capital, hedging, and pricing models at major international banks.
Dr. Matloob Khushi
Dr. Khushi is a Partner at Advance Analytica, leading the integration of advanced artificial intelligence (AI), and big data into medical services.
Dr Khushi holds a B.Sc. Engineering, Master of Computer Science, and PhD from the University of Sydney, Australia (QS world university ranking: 19). A distinguished Fellow of Advance HE UK, Dr. Khushi boasts over 25 years of experience in both industry and academia.
Dr. Khushi is widely recognized as an AI expert and academic. He also holds a position of Associate Professor at Brunel University London, UK, and lectures at other prestigious universities like the University of Sydney, Australia, Southampton University, UK, and Solent University, UK. He developed and headed Australia's top (4th worldwide: QS Ranking) AI/Data Science programmes at The University of Sydney (2017-2021) and also designed and delivered M.Sc. Data Science and AI programme for the University of Suffolk, UK (2021-2022). Dr. Khushi has published over 70 research articles in AI with a citation count exceeding 2100 placing him among the top AI researchers globally. Examples of some of his medical research which he has implemented in Australia are as follows:
- Proprietary algorithm to train machine learning algorithms for skewed datasets [1]
- Proteins localization & quantification tool for expediting cancer drug discovery [2]
- Quantification and identification of region of interest (ROI) from any type of image [3]
- Automatic Identification of Neuroblastoma Cancer [4]
- Predicting High-Risk Prostate Cancer [5]
- Automatic Identification of Corneal Nerve Structures [6]
- Algorithm for generating synthetic data for various domain application [7]
- Automatic Grading Diabetic Retinopathy (DR) Severity [7-8]
- Early stage detection of heart failure [9]
- Large Language Models (LLM) for identification medical named-entity recognition (NER), relation extraction, sentence similarity, document classification, and medical question answering [10]
- LLM for public health sentiment analysis [11]
- Identification of mental health from user sentiment [12]
Cited Publications
- 1. Mukherjee, M. and M. Khushi, SMOTE-ENC: A Novel SMOTE-Based Method to Generate Synthetic Data for Nominal and Continuous Features. Applied System Innovation, 2021. 4(1): p. 18.
- 2. Khushi, M. et al. MatCol: a tool to measure fluorescence signal colocalisation in biological systems. Sci Rep 7, 8879 (2017).
- 3. Khushi, M. et al. Automated classification and characterization of the mitotic spindle following knockdown of a mitosis-related protein. BMC Bioinformatics 18 (Suppl 16), 566 (2017).
- 4. Panta, A., Khushi, M., Naseem, U., Kennedy, P., Catchpoole, D. (2020). Classification of Neuroblastoma Histopathological Images Using Machine Learning. Neural Information Processing. ICONIP 2020.
- 5. Barlow, H.; Mao, S.; Khushi, M. Predicting High-Risk Prostate Cancer Using Machine Learning Methods. Data 2019, 4, 129.
- 6. Mehrgardt, P.; ….; Khushi, M. U-Net Segmented Adjacent Angle Detection (USAAD) for Automatic Analysis of Corneal Nerve Structures. Data 2020, 5, 37.
- 7. Lee, M. Khushi et. al., "Grading Diabetic Retinopathy Severity Using Modern Convolution Neural Networks (CNN)," 2021 IEEE International Conference on Digital Health (ICDH), Chicago, IL, USA, 2021, pp. 19-26.
- 8. U. Naseem, M. Khushi et al. (2020). Diabetic Retinopathy Detection Using Multi-layer Neural Networks and Split Attention with Focal Loss. Neural Information Processing. ICONIP 2020.
- 9. Alom, Z.,… Khushi, M., et. al.. (2022). Early Stage Detection of Heart Failure Using Machine Learning Techniques. Proceedings of the International Conference on Big Data, IoT, and Machine Learning. Lecture Notes on Data Engineering and Communications Technologies, vol 95. Springer, Singapore.
- 10. Naseem, U.,… Khushi, M. et al. Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT. BMC Bioinformatics 23, 144 (2022).
- 11. Naseem U., …Khushi M., Jinman Kim, and Adam Dunn. 2022. Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model. In Proceedings of Association for Computational Linguistics, pages 22–31.
- 12. Naseem U., …Khushi M. 2022. Early Identification of Depression Severity Levels on Reddit Using Ordinal Classification. In Proceedings of the ACM Web Conference 2022 pages 2563–2572.
Ahmet Inci
Ahmet is Partner at Advance Analytica. He is responsible for developing a multi discipline team which provides advisory and quantitative modeling services across multiple geographies. Boasting over 25+ years of experience in leading global banks, he has honed his expertise in building and validating financial, risk, pricing and predictive models. His proficiency is further recognized through his role as a visiting lecturer at Swiss universities including the University of Applied Sciences FHNW, Hochschule für Technik Zürich, and Juventus Technical College. There, he imparts his knowledge on software engineering, software architecture, distributed systems, information systems, data science, and cybersecurity.
Education
He holds a B.Sc. in Computer Science and a Master of Mathematics from ETH Zürich, Switzerland (QS World University Ranking: 9). With a MAS in Banking and Finance, Ahmet boasts over 25 years of experience in various industries including financial, healthcare, mechatronics, and IT, along with extensive teaching experience. Additionally, he holds certificates as a Certified Avaloq Customization Professional, Certified IAM and WAF Engineer, and ISAQB Certified Software Architect and Trainer.
Experience
Ahmet's solid foundation in data science and scientific computing has been applied across multiple industries, including risk management, healthcare, and mechatronics, showcasing his wide-ranging expertise. In risk management, his adept use of machine learning algorithms advances predictive analytics, leading to more nuanced assessments of market and credit risks. Within healthcare, Ahmet has crafted cutting-edge tools that streamline surgical planning for medical professionals. His contributions to mechatronics include the development of a rapid prototyping real-time simulation framework that creates detailed mathematical models for vehicle control mechanisms, underscoring his role in enhancing precision in complex systems.
Examples of some of his projects are as follows:
Projects
- 3D MedView - Transforms CT scans into 3D models, allowing doctors to examine patient data through a 3D viewer for enhanced diagnostic accuracy and surgical planning.
- AutoPark Prototype - Utilizes a rapid prototyping framework to develop a parking assistant tool that automates car parking with precision, streamlining the parking process for drivers.
- RiskAudit Analytics - A comprehensive risk management solution that integrates data-driven approaches with machine learning and statistical tools to optimize risk assessment and auditing processes.
- Leadership in Software Architecture and Digitalization - Spearheaded the pricing and valuation of various financial instruments for multiple European banks, Developed and led the specification and testing of a hedge optimizer for IFRS 32/39 hedge accounting, ensuring accuracy and compliance in financial reporting systems.