Your InfoSec team and predictive analytics can actually be best friends
Your InfoSec team just heard you want to implement predictive analytics and their first response was basically “over my dead body”. They’re imagining customer data flying through the cloud, algorithms running wild, and compliance nightmares that’ll keep legal busy for years.
Deep breath. Your security team is right to be cautious. They’re also probably imagining risks that most enterprise platforms solved years ago (especially if they have SOC II or ISO 27001 like we do).
Security First, Predictions Second
SaaS leaders like Pecan aren’t some grad student’s ML experiment running on borrowed AWS credits. We’re talking enterprise-grade security that would make your InfoSec team smile (or at least stop frowning).
Start with the basics: encryption EVERYWHERE. Data in transit? Encrypted. Data at rest? Encrypted. That random temp file that exists for 3 milliseconds? You guessed it, encrypted. Add in SSO so you’re managing access through your existing identity provider. Layer on role-based permissions so Bob from marketing can see his lead scores but not the financial forecasts.
Every action is audited. Every access is logged. Your compliance team can pull reports showing exactly who looked at what and when. It’s actually more secure than that spreadsheet Jennifer emails around every Monday.
Only Share The Data You Actually Need
The most sensitive data organizations usually have is PII (Personally Identifiable Information). But predictive models don’t need PII at all. Predicting churn? You need behavior patterns, not names. Forecasting demand? Transaction patterns matter, not credit card numbers.
Smart platforms practice data minimization by default. They can work with de-identified or even synthetic data during the security review process. One financial services firm ran their entire pilot on anonymized data. Their security team watched every step, found zero concerns, and green-lit production use in record time.
The Compliance Credentials That Matter
ISO 27001? Check. SOC 2 Type II? Absolutely. GDPR compliant? Of course. HIPAA? When needed. These aren’t just badges on a website. They’re regularly audited commitments that mean your vendor’s security is probably tighter than your own.
Major enterprises, financial institutions, healthcare organizations, they’re all running predictive models on these platforms. Your security concerns are valid, but they’re not unique. And they’ve been solved.
Your Data Stays Yours (Unlike Those Other AI Tools)
Here’s a critical distinction your InfoSec team will love: unlike general-purpose LLMs that might use your inputs to improve their models for everyone, platforms like Pecan keep your proprietary data completely confidential. YOUR data trains YOUR models. Period. It doesn’t become part of some shared intelligence that your competitors might benefit from tomorrow.
Think about it. When you use ChatGPT, you’re explicitly warned not to share sensitive information because it could potentially inform future model training. But with Pecan? Your customer patterns, your pricing strategies, your secret sauce, it all stays locked in your instance. The platform doesn’t learn from your data to help other companies. It doesn’t aggregate insights across clients. Your competitive advantages remain yours alone. One Fortune 500 CISO put it perfectly: “Finally, AI that works for us without working for everyone else too”.
Although it might seem like Pecan is straight out of the future, it’s not!
The Risk of Standing Still
While your team debates security risks, consider this: what’s the security risk of making decisions based on outdated Excel models? What’s the compliance risk of humans making biased decisions without audit trails? What’s the business risk of operating without predictions while your competitors automate everything?
One retailer’s security team spent six months reviewing a platform that their competitor implemented in three weeks. Guess who captured more market share that year?
In a highly regulated space, Coinmama shows how secure, auditable predictive analytics can deliver measurable value. With Pecan powering fraud and chargeback risk predictions, the team reduced manual reviews by two-thirds and saved about 140 hours per month – while prioritizing the riskiest transactions first. That’s tight governance paired with business impact. Read the Coinmama customer story
Your Security Team as Allies
Don’t try to sneak predictive analytics past InfoSec. Bring them in early. Show them the enterprise features. Let them review the architecture. Most importantly, start with a low-risk use case using non-sensitive data. Build trust with small wins.
Your security team wants to protect the business. So do you. Modern predictive platforms let you do both. The real risk isn’t in adopting secure, auditable, enterprise-grade predictive analytics. It’s in clinging to manual processes while everyone else moves forward.
