Jason Hills, Chief Revenue Officer
The ability to manage a deluge of data has become critical to a company’s success more than ever. With a myriad of ways to put data to work, each dataset can unleash many opportunities for profit and competitive advantage—from product enhancements to game changers to new revenue streams. At the same time, each presents a fair share of challenges to companies for unlocking its potential and extrapolating real value. “The companies who have data assets, the potential sellers, usually lack the resources and the experience to productize data. Unsure of where to start from, the companies, who are interested in selling their data, are faced with regulatory risk, safety, security, or compliance-related issues pertaining to sharing confidential customer data for gleaning insights,” begins Jason Hills, Chief Revenue Officer, ARM Insight.
Governed by a mission to make the data easier for both the companies who are interested in selling and buying the data, Portland-based ARM Insight is a provider of business intelligence solutions, transaction-based analytics, and big data solutions. ARM Insight’s team helps organizations to securely transform raw transaction data from legacy processor platforms into actionable information, which enables companies to make more intelligent business decisions. “We help organizations productize their customer data with confidence by synthesizing and altering it,” says Hills.
To begin with, ARM Insight collects data from organizations, cleanses it, and then transforms it into a format that investors can buy. The company also enhances data to make it easier consume by doing things like identifying merchants and the exact location of a physical store to add value to the processed data. ARM Insight’s proprietary algorithm alters data in such a way that it’s no longer directly attributable to a customer but is still extremely valuable.
We help organizations productize their customer data with confidence by synthesizing and altering it
This Synthetic Data methodology ensures the privacy of sensitive data by creating an “artificial” copy of client data for secure, anonymized, statistically relevant data monetization products. “We also ensure that the data transactions are compliant with all regulation like GDPR and PCI,” adds Hills. He cites an example of how ARM Insight synthesizes credit card data that comes with about 200 fields initially. The team analyzes, identifies, and removes numerous fields that are not important for investors. They then synthesize the fields by slightly altering their values so no one can ever attribute any transaction back to a person. Privacy is never compromised. Hills continues, “We alter the transaction amount in a field by a few pennies, and balance the other transactions in such a way that the investor would still derive accurate insight from individual transactions that have been slightly altered.”
ARM Insight primarily caters to the financial services industry, providing cutting-edge analytics and big data. The company’s role is not just limited to data refinery; they also develop analytics tools with advanced features such as benchmarking. ARM Insight also provides assistance and support services to organizations that have no resources or expertise about productizing their data. What makes the company second-to-none is its ability to deliver new and unique datasets such as processed debit and credit card information that regulated investors cannot directly access.
Today, ARM Insight stands a mile ahead in the industry as a trusted and compliant partner for companies using transactional data. With its proven expertise and experience garnered over the years, ARM Insight is now working with more than 6,000 banks and credit unions, prepaid card companies, and online risk companies to help them better understand and productize their data.
In the long run, ARM Insight focuses on growing and nurturing its current relationships to bring more datasets to the market. “While more companies envision productizing the data, we are solving their data-related privacy, security, and volume concerns to bring more datasets to the market,” concludes Hills.