Confidential Computing Can Help Solve Your Identity Verification Needs
Digital data sharing has become increasingly commonplace. From store rewards cards to social media signups, every day, we give away pieces of our personal lives to the online world. While all of this data sharing has opened up significant opportunities for consumers and businesses alike, it’s also created a number of security risks.
To better understand the role that data sharing plays in our daily lives, we can look to the data-as-a-service (DaaS) industry. Three interrelated groups dominate this growing sector.
- Data Providers: The organizations that collect, process, and sell data.
- Data Consumers: The organizations that buy personal data.
- Data subjects: The people whose personal data gets collected and sold.
In recent years, a wave of data protection regulations has swept across the developed world. However, this legislation represents just one data security pillar. A comprehensive data management software system is needed to truly protect consumer privacy while granting businesses, such as banks, fintech companies, and other financial institutions, access to the data they need to make informed decisions.
Current Data-Sharing Methods
Currently, a data consumer, such as a bank, would access a customer’s information by conducting an employment verification and identity verification check. Then they would make a soft credit pull and use pricing algorithms to come up with an estimate for a loan product. Before making an official offer, however, they would need to do their due diligence regarding the customer’s ability to repay.
The bank could retrieve this information in one of several different ways.
- Non-Permissioned Data Sources: This includes credit scores taken from one or more of the three major credit rating agencies. You must obtain express written consent from the subject before asking for a hard credit pull.
- Permission Data Sources: You’ll need permission from your customer before you can access their bank, tax, and utility records.
- Publicly Available Information: You can also pull information directly from Google and other search engines.
Lending institutions tend to favor non-permissioned data sources. However, while these give valuable data about a borrower’s attitude toward repayment, it gives little information on key factors influencing their ability to pay.
Fortunately, we can use a combination of the other two data sources to create a much better risk profile. Permissioned data provides concrete proof of a steady income stream and a history of on-time payments.
Data gleaned from search engines can fill in the blank space by providing additional qualitative details. For example, if a potential borrower has spent a considerable amount of time researching home renovations, that represents another data point when making a lending decision.
Advantages of Confidential Computing
Confidential computing allows for sensitive data processing inside a trusted execution environment. This safe space protects data integrity and confidentiality. It also prevents unauthorized users from accessing the data and maintains algorithm integrity. With this technology, you can stop competitors from accessing your data, maintain asset confidentiality and regulatory compliance, and generate additional revenue.
Data consumers like banks, fintech companies, and other financial institutions also benefit from the added convenience, greater data access, and lower costs. Lenders in particular will see a number of generalized and industry-specific gains.
FortifID is an industry leader in the field of confidential computing. We specialize in connecting data consumers to high-quality data sources while ensuring rigorous data privacy measures. Schedule a free demo to learn how you can take advantage of our safe and secure confidential computing technology.