Appendix
Methodology
Sample Size: 1,520
Ethical Considerations: Participants were provided with an informed consent form outlining the purpose of the study, data collection procedures, and how their data will be used. All collected data were kept confidential and were anonymized.
Data Collection Instrument: A structured online questionnaire was developed using
the survey platform of Zoho Survey. The questionnaire was designed to be user-friendly and accessible across different devices. It included a combination of closed-ended questions (multiple-choice, Likert scale) and open-ended questions to gather both quantitative and qualitative data.
Limitations and Future Research Directions: Self-reported data could be influenced by social desirability bias.
Demographics
Silent Compute
Silence Laboratories’ flagship product for privacy preserving computations over distributed & encrypted datasets
Security and Privacy consistently emerged as the leading areas of concern for existing and prospective Indian fintech users in Silence Laboratories' User Survey Report.
Security is the firm bedrock needed to support the rapid proliferation of a sophisticated data-fuelled digital financial ecosystem. Privacy, which in context of data sharing is often limited to mere one-time obtainment of consent, entails a right to multifaceted control over data sharing. Trust is the foundation of all stakeholder synergy and trust must be rooted in a technically sound, structurally reliable, and secure-by-design security base and be fostered by empowering the data principals with genuine control over their data.
Silent Compute is a tool that facilitates collaboration on data analysis between different organizations while keeping the underlying information entirely private.
It facilitates privacy preserving computations over distributed and encrypted data. This means that the data itself never leaves its native environment and no party is exposed to another's raw data, while usable inferences from the same can flow in a smooth and streamlined manner as agreed by the interacting parties.
Permitting the flow of insights while keeping all raw data secure at its respective sites ensures free utility with guaranteed security. Silent Compute puts the reins of the data back into the hands of the data subjects, empowering them by consolidating their control as exclusive owners of the data while allowing data providers, to act as custodians of data and to earn by harvesting inferences and insights drawn from it.
Silent Compute provides a rock-solid technological substrate for secure cross-institutional data collaboration, protecting customer privacy by preventing exposureof raw data and utilizing distributed analytics to eliminate single-point failures.
Key value proposition offered by Privacy Enhancing Technologies (PETs)
DATA PROVIDER: Monetise your data
Data stays with you, only inferences move
Revenue upside from untapped data
Collaborate without worrying about compliance or competition
DATA SUBJECT: Take control of your data
Transparent & auditable consent mechanisms
Prevention from data misuse and theft
Control over data usage, sharing, deletion or modification
DATA FIDUCIARY: Privacy guarantees for processing data
Computation on encrypted & distributed data - No single point of failure
Navigate privacy compliance with ease
Superior insights into your customer
Use cases of Silent Compute
Open Banking
AML / RegTech
Credit/risk scoring
Telecom data monetisation
Healthcare research
