About Tobias

Tobias coleads our work in credit-risk advanced analytics and is a member of our Behavioral Insights group. He has pioneered much of our proprietary research in credit-risk analytics, including advanced-analytics engines using (through machine-learning, traditional, and hybrid approaches) big data and other nontraditional data, the development of unique approaches for qualitative rating systems, and the debiasing of risk-management decisions. He also focuses on low-default modeling, loss-given-default estimation, and revenue and income prediction.

In 2004, Tobias helped launch our Risk Advanced Analytics Center of Competence in India, which today has more than 30 analysts and modeling experts.

Aside from risk analytics, the primary focus of Tobias’s work is underwriting, portfolio risk modeling, and strategy design for collections and workout using psychological levers and behavioral analytics. His experience also extends to the application of predictive modeling in other industries, including insurance (for example, commercial insurance underwriting and claims predictions), government services, law enforcement, and telecommunications.

Based in Taipei, Tobias serves clients across the globe. Among other recent projects, he has:

  • developed both quantitative and qualitative rating systems for a large North American bank, including low-default and specialized-lending portfolios
  • worked with a major Taiwanese bank to transform its risk-management function, including developing new rating models and credit tools, estimating Basel II exposure and loss parameters, and designing new credit-risk processes and management reports
  • helped a Brazilian bank assess the level of commodity risk embedded in its credit portfolio, and then created a set of tools to mitigate exposure
  • helped a Southeast Asian microlending organization develop credit-assessment processes and tools
  • conducted a broad enterprise-risk-management diagnostic for one of the world’s leading emerging-market banks
  • designed innovative motor-insurance pricing models for a digital start-up that compensated for gaps in the company’s loss experience by leveraging comprehensive metadata on insured risks, such as car-engineering data.

Tobias speaks English, German, and basic Italian, Portuguese, French, Mandarin, and Korean.

Published work

Behavioral insights and innovative treatments in collections,McKinsey on Risk, March 2018

Controlling machine-learning algorithms and their biases,McKinsey on Risk, November 2017

The business logic in debiasing,McKinsey on Risk, May 2017

Lending responsibly: New credit-risk models for the unbanked,” McKinsey & Company, February 2012

The use of economic capital in performance management for banks,” McKinsey Working Papers on Risk, Number 24, January 2011 (PDF–404 KB)

The National Credit Bureau: A key enabler of financial infrastructure and lending in developing economies,” McKinsey Working Papers on Risk, Number 14, December 2009 (PDF–529 KB)

Best practices for estimating credit economic capital,” McKinsey Working Papers on Risk, Number 11, April 2009 (PDF–185 KB)

Past experience

Dresdner Bank
Various credit-related roles


University of Frankfurt
PhD, finance

University of Cambridge
MPhil, psychology

University of Wisconsin, Milwaukee
MA, economics

University of Giessen
BA equivalent, business and economics