Data Analytics

How to Use Financial Analytics to Detect Fraud

Teresa Wingfield

September 14, 2023

Fraud detection using financial analytics

According to the Association of Certified Fraud Examiners, organizations lose 5% of their revenue to fraud each year. It’s no wonder that financial analytics for fraud detection is in such high demand given this alarming statistic. Fortunately, financial analytics can play a crucial role in helping businesses detect and prevent fraud by analyzing various patterns, discrepancies, and anomalies in financial data and flagging suspicious activities.

The list of use cases for fraud detection leveraging financial analytics seems to be endless, but here’s a breakdown by industry (banking and finance, healthcare, insurance, retail, and telecommunications) of some of the most common examples.

Banking and Finance

  • Credit Card Fraud: Flags credit card transactions that fall outside the scope of normal activity such as multiple transactions to one card in a short period of time, multiple rush orders to the same address, or an unusually high charge card amount.
  • Money Laundering: Analyzes transactions and the flow of funds across different accounts to identify suspicious activities such as structuring transactions to avoid reporting thresholds, layering funds through multiple accounts, or using complex transaction networks to obfuscate the source of funds.
  • Insider Trading: Identifies abnormal trading volumes, unusual price movements, and correlations between trading activities and significant corporate events.
  • Identity Theft: Flags accounts with unusual behavior such as sudden changes in spending patterns or unexpected transactions in new locations that may indicate that someone is illegally using another person’s data or account.


  • Fraudulent Claims: Identifies claims with excessive or unnecessary procedures, and services that are inconsistent with a patient’s medical history.
  • Fraudulent Billing: Spots unusual coding patterns, phantom billing, upcoding, unbundling, and disproportionate billing compared to peers.
  • Collusion: Analyzes claims and payment data to detect a high number of patient visits to different providers or patients who may be helping providers charge for tests they do not need.


  • Application Fraud: Spots false information, fictitious beneficiaries, and agents opening and canceling policies to make quotas and bonuses.
  • Fraudulent Claims: Detects frequent or excessive claims, inflated claims, staged accidents, duplicate claims, and inconsistent information across claims.


  • Credit Card Fraud: Flags credit card transactions that fall outside the scope of normal activity, such as changes in the frequency of orders, higher orders than the average use transaction, changes to a shipping address, bulk orders for the same item, and unmatched or suspicious IP addresses.
  • Refund Fraud: Analyzes data such as the frequency and timing of returns, products returned and their value, and return reasons to discover potential fraud.


  • Revenue Reporting Fraud: Examines billing data, contract terms, and revenue streams to identify discrepancies, such as unbilled services, underbilling, or revenue leakage that are likely to be due to fraudulent activities.
  • Subscriber Fraud: Analyzes subscriber behavior patterns and financial transactions to detect unusual account activities, such as frequent Subscriber Identity Module (SIM) card changes, abnormal roaming behavior, or suspicious calling patterns.

How Actian Can Help

Fraud is increasing both in frequency and amount. With so much at stake, businesses need to either adopt or ramp up their financial analytics to control fraud. Actian can assist you with a new project or help scale your existing analytics deployment. We are a trusted advisor with over 50 years of experience helping customers manage the world’s most critical data.

Actian makes financial data easy. We deliver cloud and on-premises data solutions that simplify how people connect, manage, and analyze data. We transform business by enabling customers to make confident, data-driven decisions that accelerate their organization’s growth. Our data platform integrates seamlessly, performs reliably, and delivers at industry-leading speeds.

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About Teresa Wingfield

Teresa Wingfield is Director of Product Marketing at Actian where she is responsible for communicating the unique value that the Actian Data Platform delivers, including proven data integration, data management and data analytics. She brings a 20-year track record of increasing revenue and awareness for analytics, security, and cloud solutions. Prior to Actian, Teresa managed product marketing at industry-leading companies such as Cisco, McAfee, and VMware.