How to Detect Recurring Payments & Subscriptions via API

Recurring payments are everywhere. From streaming services and cloud storage to gym memberships and meal kits, the average consumer juggles more than a dozen active subscriptions at any given time. For fintech companies, neobanks, and personal finance apps, the ability to detect recurring payments automatically is no longer a nice-to-have -- it is a core feature that users expect. In this tutorial, we will walk through how to identify subscriptions programmatically using an API, build a subscription tracker, and explore the real-world applications that make this capability so valuable.

Why Detecting Recurring Payments Matters

Subscription creep is one of the most common financial blind spots for consumers. Studies consistently show that people underestimate their monthly subscription spending by 2-3x. The numbers paint a stark picture:

• $273/month -- Average American spending on subscriptions
• 84% -- Percentage of consumers who underestimate what they pay
• $133/month -- Average amount wasted on forgotten or unused subscriptions
• 12+ -- Average number of active subscriptions per consumer

For budgeting apps, detecting these charges automatically means users can see exactly where their money goes each month without manually tagging every transaction. For neobanks, it means offering proactive insights like "You have 3 subscriptions you haven't used in 60 days." For expense management platforms, it means separating one-time purchases from recurring obligations to give teams accurate forecasts.

The business case is equally strong. Truebill, which built its entire product around subscription detection and cancellation, was acquired by Rocket Companies for $1.275 billion. That acquisition validated what the market already knew: users will pay for tools that help them manage recurring charges.

Traditional Approaches and Their Limitations

Before AI-powered APIs, developers typically relied on two approaches to detect recurring payments: regex-based pattern matching and frequency analysis. Both have significant drawbacks.

Regex Pattern Matching

The simplest approach involves scanning transaction descriptions for keywords like "subscription," "monthly," "recurring," or known merchant names. You might write rules like: if the description contains "NETFLIX" or "SPOTIFY," flag it as a subscription.

The problem is that bank transaction descriptions are messy. A Netflix charge might appear as "NETFLIX.COM," "NETFLIX INC," "NF*NETFLIX," or "CKO*NETFLIX" depending on the bank, the payment processor, and the country. Maintaining a regex library that covers every merchant across every bank is a losing battle. New services launch daily, and banks frequently change their transaction description formats.

Frequency Analysis

A more sophisticated approach involves analyzing transaction history to find charges that recur at regular intervals. If a $14.99 charge from a similar-looking description appears every 30 days, it is likely a subscription.

This works better, but requires months of historical data before it can identify a subscription. It also struggles with annual charges, irregular billing cycles, price changes, and prorated amounts. A user who just signed up for a new service will not see it flagged until the second or third charge comes through.

How AI-Powered APIs Solve This

Modern transaction enrichment APIs like Easy Enrichment take a fundamentally different approach. Instead of relying on brittle rules or waiting for historical patterns to emerge, AI models analyze the transaction description in context and return structured data that includes subscription classification.

When you send a raw transaction description to the Easy Enrichment API, the response includes an is_subscription boolean field alongside the enriched merchant name, category, logo, and contact information. This works on the very first transaction -- no history required.

// Example API response for a subscription transaction
{
  "original_description": "NFLX DIGITAL 866-579-7172 CA",
  "merchant_name": "Netflix",
  "category": "Entertainment",
  "subcategory": "Video Streaming",
  "is_subscription": true,
  "is_online_only": true,
  "logo_url": "https://logo.clearbit.com/netflix.com",
  "contact_phone": "+1 866-579-7172",
  "contact_email": "help@netflix.com",
  "support_url": "https://help.netflix.com"
}

The API handles all the complexity of merchant identification, description parsing, and subscription classification in a single call. It recognizes thousands of subscription services out of the box, including niche SaaS tools, regional streaming platforms, and services that use third-party billing.

Code Example: Detecting Subscriptions with the API

Here is a complete JavaScript example showing how to enrich a batch of transactions and filter for subscriptions. This uses the Easy Enrichment API with a simple fetch call.

const API_BASE = "https://api.easyenrichment.com";
const API_KEY = "your_api_key_here";

// Enrich a single transaction and check for subscription
async function detectSubscription(description) {
  const response = await fetch(`${API_BASE}/enrich`, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${API_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({ description })
  });

  const data = await response.json();

  return {
    merchant: data.merchant_name,
    category: data.category,
    isSubscription: data.is_subscription,
    logo: data.logo_url,
    contact: {
      phone: data.contact_phone,
      email: data.contact_email,
      supportUrl: data.support_url
    }
  };
}

// Process a batch of transactions
async function findAllSubscriptions(transactions) {
  const results = [];

  for (const tx of transactions) {
    const enriched = await detectSubscription(tx.description);
    if (enriched.isSubscription) {
      results.push({
        ...enriched,
        amount: tx.amount,
        date: tx.date
      });
    }
  }

  return results;
}

// Usage
const transactions = [
  { description: "NFLX DIGITAL 866-579-7172", amount: 15.49, date: "2025-03-01" },
  { description: "AMZN MKTP US*2K7F9X1P0", amount: 47.82, date: "2025-03-02" },
  { description: "SPOTIFY USA", amount: 10.99, date: "2025-03-03" },
  { description: "SHELL OIL 47829", amount: 52.10, date: "2025-03-04" },
  { description: "ADOBE *CREATIVE CLD", amount: 54.99, date: "2025-03-05" }
];

findAllSubscriptions(transactions).then(subs => {
  console.log(`Found ${subs.length} subscriptions`);
  subs.forEach(s => {
    console.log(`  ${s.merchant}: $${s.amount}/mo`);
  });
});

Building a Subscription Tracker

Once you can detect subscriptions, the next step is grouping them by merchant and calculating monthly totals. This gives users a clear picture of their recurring spending.

Grouping by Merchant

Multiple charges from the same service should be grouped together. The enriched merchant name from the API makes this straightforward -- no need to fuzzy-match messy bank descriptions.

function groupByMerchant(subscriptions) {
  const grouped = {};

  for (const sub of subscriptions) {
    const key = sub.merchant;
    if (!grouped[key]) {
      grouped[key] = {
        merchant: sub.merchant,
        category: sub.category,
        logo: sub.logo,
        contact: sub.contact,
        charges: []
      };
    }
    grouped[key].charges.push({
      amount: sub.amount,
      date: new Date(sub.date)
    });
  }

  return Object.values(grouped);
}

// Calculate estimated monthly cost per subscription
function estimateMonthlyCost(charges) {
  if (charges.length < 2) {
    return charges[0].amount;
  }

  const sorted = charges.sort((a, b) => a.date - b.date);
  const daysBetween =
    (sorted[sorted.length - 1].date - sorted[0].date) /
    (1000 * 60 * 60 * 24) /
    (sorted.length - 1);

  const avgAmount =
    charges.reduce((sum, c) => sum + c.amount, 0) / charges.length;

  if (daysBetween <= 35) return avgAmount;          // Monthly
  if (daysBetween <= 95) return avgAmount / 3;       // Quarterly
  if (daysBetween <= 200) return avgAmount / 6;      // Semi-annual
  return avgAmount / 12;                             // Annual
}

// Build the final subscription summary
function buildSubscriptionSummary(subscriptions) {
  const groups = groupByMerchant(subscriptions);

  const summary = groups.map(group => ({
    ...group,
    monthlyEstimate: estimateMonthlyCost(group.charges),
    lastCharged: group.charges.sort((a, b) => b.date - a.date)[0].date
  }));

  const totalMonthly = summary.reduce(
    (sum, s) => sum + s.monthlyEstimate, 0
  );

  return { subscriptions: summary, totalMonthly };
}

With this logic in place, you can display a dashboard showing each subscription with its logo, monthly cost, last charge date, and cancellation contact info -- all derived from a single API.

Real-World Use Cases

Recurring payment detection powers features across many types of financial products. Here are the most common applications.

Personal Finance Apps

Budgeting apps use subscription detection to separate fixed recurring costs from variable spending. This allows users to see their true discretionary budget after subscriptions are accounted for. Many apps also offer subscription cancellation flows, using the contact information returned by the API to connect users directly with the merchant's support team.

Neobanks and Digital Banks

Neobanks use subscription detection to power smart notifications. When a new recurring charge is detected, the bank can alert the user: "It looks like you just subscribed to a new service." They can also flag price increases, detect when a free trial converts to a paid subscription, and warn users about upcoming annual renewals.

Expense Management Platforms

For businesses, identifying which software subscriptions are active across the organization is critical for cost optimization. Expense management tools use recurring charge detection to build a SaaS inventory, flag duplicate subscriptions across teams, and forecast recurring expenses for budget planning.

Lending and Credit Assessment

Lenders use subscription data as part of affordability assessments. Understanding a borrower's fixed monthly obligations -- including subscriptions -- gives a more accurate picture of disposable income than looking at raw transaction totals.

Getting Started

Implementing subscription detection with Easy Enrichment takes minutes, not months. The API handles the heavy lifting of merchant identification, category classification, and subscription flagging. You focus on building the user experience your customers care about.

Start with single transaction enrichment to test the accuracy, then move to batch processing for production workloads. The is_subscription field is included in every response at no extra cost -- it is part of the standard enrichment payload.