“If there were no trust, then no one would take risks. No risks would mean no exploration, no experimentation and no advancement of the society as a whole.” Sinek, Simon. Start with Why: How Great Leaders Inspire Everyone To Take Action. We support risk takers. We ensure these lenders and investors in loans confidently make good credit decisions, competently value and actively manage portfolios independently, and can confidently comply with regulations in an easy and cost-efficient manner. Credit is good, if well understood.
We aim to have access to the best data in the market. We clean it, normalize it and store it in one large database, and have it automatically updated to check data quality. We focus on visualizing data and building complex self-learning models to meet regulatory requirements such as Basel, Solvency II, IFRS 9/CECL and CCAR and EBA stress testing. The model outputs are combined with the data and visualized to support analysis, decision making and seamless regulatory reporting.
We put the risk taker in the centre and the heavy data lifting and complex self-learning models in the background. Our credit risk automation solutions are designed to let the data talk and to avoid expert bias. We automate data validation, analysis, modelling, and reporting on credit portfolios and visualise the outputs for faster, more accurate and more intuitive insight to make better credit decisions focussing on key risk drivers.
We would welcome the opportunity to discuss your requirements and see how we can assist, please email firstname.lastname@example.org or contact him on +31 70 32 60 370.
Open Source Investor Services B.V. (“OSIS”) is a Dutch Fintech company specialized in credit risk and founded in December 2010.
During the recent financial crisis, many market participants from banks to investors, both large and small were unable to quantify the credit risk they had on their balance sheets and thus unable to value their loans and asset backed securities. This led to uncertainty, herding, panic and ultimately the near collapse of the financial system. To date these issues have still not been resolved.
Our motto is “empower people to trust their risk decisions”. We want to make complex credit risk analysis easy to understand for those in the boardrooms of large international lenders, and also for investors in loans thus enabling them to act as do-it-yourself credit rating agencies. We do the heavy data lifting and create complex self-learning models behind the scenes, so our system users can be masters of their own destiny. We enable them to run their own stress scenarios, understand risk, and calculate the value of their loans. We want to contribute to well functioning data rich financial markets.
We distinguish ourselves from our competitors by having access to the best data in the market, and by having relevant domain knowledge in lending, credit portfolio management, loan trading, data pooling and securitization. We operate in a growing market in which, due to changing regulations concerning banks and insurance companies, more than USD 10 trillion in bank assets (mainly loans) in the EU and US will shift between balance sheets. This situation requires new analytical tools for both the sellers and the buyers of these assets.
OSIS develops software, provide SAAS services and consultancy to lenders (banks, insurers and ALP), investors in loans (insurance companies, pension funds and ABS investors) in the EU, Australia and North America.
Jeroen is a co-founder of OSIS. He began his banking career in commercial lending at ING Bank. In 2000 he became head of Credit Portfolio Management at NIBC and in 2007 he continued as head of Securitization at Credit Portfolio Management at BNP Paribas Fortis. In this last role, he was responsible for several post crisis and Basel 2 compliant securitization transactions. Further, he is the founding chairman of Global Credit Data, a global association of banks with the largest loan loss database in the world. He holds a MS in Law from the University of Utrecht, the Netherlands.
Burkhard is a co-founder of OSIS. Previously, he was Managing Director at Bank of America Merrill Lynch responsible for originating and arranging structured credit related capital and funding transactions for financial institutions in Europe. He has been a principal investor in securitization transactions and distressed debt portfolios and has structured a number of first time asset securitizations (e.g. of project finance, aircraft and shipping loans). He holds a PhD in Applied Mathematics and Theoretical Physics from the University of Cambridge, England.
Bernd has 15 years experience in quantitative analysis and financial modelling. He started his professional career at the Deutsche Bundesbank where he worked in banking supervision for two years. Since then he has worked as a quantitative analyst and software developer for the financial industry. He has implemented loan pricing frameworks, economic capital models for ICAAP, and credit risk models for various purposes. In addition, he regularly holds public and in-house credit risk management training courses in Asia and Europe. He holds a PhD in Finance from the University of Vienna.
Xhesika started her professional career at Intesa San Paolo Bank where she worked as an Insight Data Analyst for two years, responsible for designing and implementing predictive statistical models, segmentation analysis, and data analysis. In 2016, she graduated with her master thesis on predicting company earnings, for which she received the Super Quant Internship Award for research excellence granted by Robeco. She holds a M.Sc. degree in Financial Economics from the Erasmus University in Rotterdam, and a BA (Hons.) in Computer Science and Economics from the American University in Bulgaria.
Jiawei started her career in the financial industry as a software developer for stress testing investment portfolios. In 2017 she did a thesis internship with Robeco on measuring government bond value with yield curve modelling, for which she received the Super Quant bonus from Robeco for research excellence. She holds a MSc in Econometrics from Erasmus University Rotterdam.
Michael graduated in 2018 and wrote his thesis on the PD and LGD relationship for US mortgages. He wrote his thesis in combination with part-time employment at Open Source Investor Services and after his graduation Michael became a full-time quantitative analyst at Open Source Investor Services. Michael holds a MSc degree in Quantitative Finance and gained consultancy experience at Zanders while finishing a BSc in Econometrics & Operations Research.
After graduating with a Master’s degree in Quantitative Finance from Erasmus University Rotterdam, Daniel joined Open Source Investor Services as a quantitative analyst. Before starting at Open Source Investor Services, Daniel worked as a research assistant at Erasmus Q-Intelligence and completed an internship at Statistics Netherlands.
Philip graduated in 2018 and holds a Master in Econometrics degree from Erasmus University Rotterdam. Philip completed a graduate internship with the De Nederlandsche Bank, where he worked on a new model for forecasting energy prices. Before transitioning to econometrics, Philip obtained a Bachelor’s (Honours) degree in Liberal Arts and Sciences, focusing on economics and political science.
Stéphane has been active in the field of software development for the last 18 years and has worked as software developer, development team leader and executive manager. He managed teams up to 15 members of PhD candidates and engineers for the development of challenging commercial software and was responsible for an international consortium aiming at building new commercial software. He developed applications to handle securitization data, to easily update and monitor securitized portfolio and generate reports. He also has a lot of experience in collecting user requests, writing software specifications and providing on-site or off-site training and support. Stéphane is a mechanical engineer and holds a PhD in Applied Sciences.