Finance & Banking Teams Solution

Protect Financial Data When Using AI Tools

Finance teams can use ChatGPT to analyse transactions, identify patterns, and generate insights without exposing account numbers, customer financial information, or sensitive data.

The Finance Team's Challenge

A financial analyst needs AI help identifying patterns in transaction data, summarising customer account activity, or detecting anomalies. The export contains account numbers, customer names, transaction amounts, BSB/routing numbers, and reference details.

The Risk: Data Exposure

  • Account Numbers Exposed: Banking details uploaded to AI tools
  • Customer Financial Identifiers Leaked: Customer names and financial identifiers accessible to third parties
  • Transaction History Compromised: Transaction history and payment patterns exposed
  • Banking Details Accessible: BSB/routing numbers and reference codes at risk
  • Regulatory Violations: Serious regulatory violations and compliance breaches

The Fix: Redactli

  • Local Processing: Data is anonymized in your browser before it hits the network.
  • Smart Replacement: Sensitive values become readable tokens like "[EMAIL_1]" for context preservation.
  • Instant Processing: Millisecond-speed encryption with zero server latency.

How It Works

1

Export Financial Data

Download transaction or account data as CSV

2

Anonymize Identifiers

Transform account numbers and customer info

3

Upload to AI

Get pattern analysis safely with ChatGPT

4

Get Insights

Identify patterns without exposing data

5

Maintain Compliance

Analysis with regulatory protection

Comprehensive Data Protection

Automatically detect and protect all types of sensitive information.

Account Numbers

Real account numbers → "Account_x5y9z3w1"

Customer Names

Account holders encrypted to "Name_a3b7c9d2"

Transaction References

Payment references encrypted, patterns preserved

BSB/Routing Numbers

Banking identifiers encrypted with tokenized format

Success Story

The Challenge

Financial controller has 12 months of transaction data (15,000 records) and needs to identify spending patterns, detect anomalies, and prepare executive summary for board presentation—but can't manually analyse thousands of transactions.

The Solution

  • Export transaction data with account numbers, customer names, amounts, dates, and categories
  • Upload to Redactli and anonymize Account Number, Customer Name, and Reference columns
  • Ask ChatGPT: "Analyse transaction patterns. Identify top spending categories, flag accounts with unusual activity, calculate monthly trends, and create executive summary with key insights"
  • Receive comprehensive analysis with anonymized account identifiers, trend charts, anomaly alerts, and executive summary
  • Present insights to board with confidence—no customer data was exposed to AI tools

The Outcome

Finance team gets sophisticated analysis in hours instead of weeks. Regulatory compliance maintained throughout. Board receives actionable insights backed by comprehensive data analysis.

Ready to Protect Financial Data?

Join finance teams using Redactli to safely leverage AI for transaction analysis without compromising customer privacy or compliance. Start free today.

    Protect Financial Data When Using AI Tools | Redactli | Redactli