Powered by Kim et al. (2024) Research
Based on peer-reviewed research from the University of Chicago, MKBrain achieves 60% accuracy in predicting earnings direction—outperforming human analysts at 53%. The secret? Analyzing financial statements without knowing the company identity.
MKBrain analyzes without knowing company identity, eliminating confirmation bias
Step-by-step reasoning visible and explorable, not a black box
See where MKBrain is confident vs uncertain across different aspects
Identifies similar historical situations and their outcomes
MKBrain analyzes financial statements without knowing the company identity, forcing pure analytical reasoning without bias.
Methodology based on: Kim, A.G., Muhn, M., & Nikolaev, V.V. (2024). "Financial Statement Analysis with Large Language Models." University of Chicago Booth School of Business.