Daniel Seiler

Within Group Risk responsible for risk methodologies and analytics , including model validation.

Within the Group Treasury Liquidity & Funding Modelling team responsible for strengthening the team's quantitive modelling capacities, establishing improved model development standards and having an important role in the strategic build-out and extension of Liquidity & Funding models.

- Functional management of the Risk Model Validation team (16 employees) o covering around 300 credit, issuer, market, consequential and treasury models of UBS Group and its entities. o acting as contact person towards regulators and internal/external audit. - Responsible SR Letter 11-7 compliant validation of risk models related to Basel III, FINMA LPA, FDIC/FED DFAST/CCAR (covering loss but also balance-sheet and pre-provision net revenue (PPNR) models) as well IFRS 9 Expected Credit Loss provisioning.

- Functional management of the IB Risk Model Validation team consisting of three employees - Participating in the Basel 2.5 project, being responsible for the independent validation of the newly introduced Incremental Risk Charge and Stressed Value at Risk models (including successful audit and regulatory approval process). - Acting as main IB Risk Model Validation contact person towards regulators and internal/external audit, as well as participating in regular meetings with FINMA and PRA.

In Model Validation and Firm-wide Stress teams, among others responsible for the following tasks: - Independent validation of OTC EPE and SFT RepoVaR credit exposure calculation models and Lombard (Securities-Backed-Lending) models - As part of the newly established firm-wide stress testing framework, developed an exposure sensitivity methodology for the traded products credit portfolio (OTC and SFT) and stress modules for IB Take & Hold Credit Exposure and Funding Risk.

- Involved in the field test of the Swiss Solvency Test (SST) that was being developed by the Federal Office of Private Insurance. - Developed and implemented an internal tool to measure the interest sensitive options of Zurich Life Switzerland on a mark-to-market basis (Market-consistent Embedded Value). - From an actuarial side, involved in several tariff revisions (Collective Paid Sick Day Insurance and Mandatory Accident Insurance)

For four months employed part-time (50%) as assistant at the “Institute for Empirical Research in Economics”.

A six week actuarial internship. Involved in the development of a tool to calculate the amortisation pattern for deferrable acquisition costs under US GAAP.

Specialization in Machine Learning and Artificial Intelligence

Diploma of Advanced Studies in Finance (joint programme of Swiss Finanance Institute and University of Bern).

Specialization in Quantitative Finance and Risk Management as well as Asset Management; Master thesis: “Backtesting Multiple-Period Forecasting Models with Application to Credit Exposure Models”

Stochastics, Insurance and Financial Mathematics, Economics; Master thesis: “Modelling Dependent Credit Risks”