TOBIAS BAER

Consultant • Coach • Scholar
Data Science • Psychology • Risk Management
Author of the book "Algorithmic Bias"

My work

I am a pioneer in data science and the application of analytics and psychology to risk management. I support a small number of Fintechs/start-ups as Senior Advisor and pursue psychological research in cooperation with University of Cambridge. In my advisory work, I focus on Data Science, Risk Management, and Psychology, such as innovative and bespoke risk management solutions that use advanced analytics, Big Data, nontraditional data, qualitative decision systems, debiasing techniques, behavioral segmentation analytics, and psychological insights.


My experience
I am an ex McKinsey Partner with over 25 years of experience in risk management, having served financial institutions on all continents (50+ countries) with a particular focus on credit risk, such as:
  • Advanced analytical models using non-traditional (incl. “Big”) data sources;
  • Qualitative decision systems that apply statistical techniques and proprietary debiasing techniques to human judgment;
  • Collections strategies that tailor the customer engagement approach (e.g., messages and digital channels) using behavioral segmentation analytics and psychological insights
At McKinsey, I was a global leader of Credit Risk Advanced Analytics, building this capability from scratch in our India Knowledge Center starting in 2004 (one of the Firm’s first advanced analytics capabilities ever) and driving its growth to ~30 analysts with global footprint, and have supported numerous start-up lending businesses in emerging markets as well as transformations of large incumbents, achieving break-through business impact (e.g., <2% loss rate for the fastest-growing small business lending start-up; 50% loss reduction and 17% annual growth above the market for already the largest player) through digitalization and exceptional predictive power of highly creative scorecards using innovative data.

I have also taught/coached over 50 LGBT senior executives on transitions into new leadership roles as faculty of McKinsey’s Senior Executive Transition Master Class.

I hold a PhD in Finance (University of Frankfurt), MPhil in Psychology (University of Cambridge), and MA in Economics (University of Wisconsin), and am a member of Wolfson College (University of Cambridge).

Algorithmic Bias

Algorithmic bias can affect us everywhere, from minor trivia such as our social media feeds to critical decisions where bias can wreak havoc with a person's life dream or a company's survival. Sources of algorithmic bias are manifold – some such as biased data and overfitting sit squarely in the domain of data scientists who can take specific steps to counteract them; other sources such as deeply rooted societal biases and the biases of users and data scientists themselves, however, only can be tackled by the business users and government agencies who use algorithms, be it through carefully crafted experiments that generate truly unbiased data or through deliberate tweaks of the decision-making process. 

In my new book "Understand, Manage, and Prevent Algorithmic Bias" I put algorithmic bias in the bigger context of human decision biases, discuss both psychological and statistical sources of bias, and describe in laymen-friendly terms (and dedicated parts of the book) what users and data scientists can do respectively to manage and prevent algorithmic bias. Click here to read more!

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