Privacy-Preserving Methods for Sharing Financial Risk Exposures
利用密码学成果，开发了无需可信第三方的计算协议，使金融机构能在不泄露专有数据的前提下共享和汇总风险暴露统计量，适用于银行资本比率监控、投资组合审计等场景。
The financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. Using results from cryptography, we develop computationally tractable protocols for sharing and aggregating such risk exposures that protect the privacy of all parties involved, without the need for trusted third parties. Financial institutions can share aggregate statistics such as Herfindahl indexes, variances, and correlations without revealing proprietary data. Potential applications include: privacy-preserving real-time indexes of bank capital and leverage ratios; monitoring delegated portfolio investments; financial audits; and public indexes of proprietary trading strategies.