secure financial analytics

Transforming Finance: Homomorphic Encryption and Privacy in Financial Transactions

Use Cases in the Financial Industry

Secure Financial Analytics


Financial institutions must often analyze vast datasets containing sensitive information, such as customer transactions, without exposing the raw data.


Homomorphic encryption allows for secure financial analytics by enabling computations on encrypted data. Institutions can derive valuable insights without compromising the confidentiality of customer details or transaction histories.

Private Credit Scoring


Credit scoring involves analyzing diverse financial attributes of individuals, but revealing such personal information poses privacy concerns.


Homomorphic encryption ensures that computations related to credit scoring can be performed on encrypted financial data. It preserves the privacy of individuals while allowing financial institutions to assess creditworthiness securely.

Secure Collateral Management


Managing collateral often involves processing sensitive financial information, which must be kept confidential to maintain the integrity of financial systems.


Homomorphic encryption provides a secure way to compute encrypted collateral data. Financial institutions can manage collateral without exposing details to potential adversaries.

Confidential Risk Assessments


Risk assessments in the financial sector require evaluating various factors, including market trends and customer data, but divulging this information can have severe consequences.


Homomorphic encryption facilitates confidential risk assessments by allowing computations on encrypted financial data. It protects the integrity of risk assessment models while keeping sensitive information secure.

Contributions to Privacy in Financial Transactions

Data Confidentiality

Homomorphic encryption ensures that financial transactions and related computations can be performed on encrypted data. The raw data remains confidential even in scenarios where third-party entities are involved in transaction processing.

Privacy-Preserving Analytics

Financial institutions can leverage homomorphic encryption to conduct analytics and generate insights without compromising the privacy of individuals or exposing sensitive financial information.

Secure Multiparty Computation

Homomorphic encryption enables secure multiparty computation, allowing different entities to collaborate on financial transactions or analyses without revealing their proprietary information.

Enhanced Customer Trust

By adopting homomorphic encryption, financial institutions are committed to protecting customer privacy. It fosters trust among clients who are increasingly concerned about the security of their financial data.

Regulatory Compliance

Homomorphic encryption aids financial institutions in complying with data protection regulations. It ensures that sensitive financial information is handled in a privacy-preserving manner, aligning with stringent regulatory requirements.