Leveraging SQL pattern matching for fraud detection in insurance claims

25 Sep 2023

In the world of insurance, fraud detection is a critical aspect of protecting the industry and ensuring that genuine claims are processed correctly. With the advancement of technology, businesses now have access to sophisticated tools and techniques to help identify fraudulent activities. One such technique is SQL pattern matching, which can be leveraged to analyze insurance claims data and detect potential fraud.

What is SQL Pattern Matching?

SQL pattern matching, introduced in Oracle Database 12c, is a powerful feature that allows developers to perform pattern matching within the database. Using SQL language constructs, you can search for regular expression patterns in text and extract relevant information based on those patterns. This functionality enables complex search and analysis operations that were previously difficult to achieve with SQL alone.

How Can SQL Pattern Matching be Applied to Fraud Detection?

When it comes to insurance claims, patterns can reveal potential instances of fraud. SQL pattern matching can be applied in various scenarios:

Identifying Duplicate Claims: Fraudsters often submit multiple claims for the same incident to different insurance companies. By employing SQL pattern matching, you can search for patterns indicative of duplicate claims, such as similar claim descriptions, claim amounts, or policyholder information.

SELECT claim_id, claim_description, claim_amount
FROM insurance_claims
MATCH_RECOGNIZE (
  PARTITION BY claim_description
  ORDER BY claim_id
  MEASURES
    A.claim_id AS claim_id1,
    B.claim_id AS claim_id2,
    A.claim_description AS claim_description,
    A.claim_amount AS claim_amount
  PATTERN (A B)
  DEFINE B AS B.claim_id <> A.claim_id
);

Detecting Anomalous Behavior: Fraudulent claims often exhibit unusual patterns or behavior. By analyzing historical claims data using SQL pattern matching, you can identify patterns that deviate significantly from the norm. For example, if a policyholder suddenly submits multiple high-value claims within a short period, it may indicate potential fraud.

SELECT policyholder_id, claim_amount, claim_date
FROM insurance_claims
MATCH_RECOGNIZE (
  PARTITION BY policyholder_id
  ORDER BY claim_date
  MEASURES
    A.policyholder_id AS policyholder_id,
    A.claim_amount AS claim_amount,
    A.claim_date AS claim_date
  PATTERN (A+)
  DEFINE A AS A.claim_amount > 5000
);

Discovering Frivolous Claims: Frivolous claims refer to those lacking evidence or veracity intentionally. SQL pattern matching can be used to identify patterns where claims share similar characteristics or contain common keywords associated with fraudulent or frivolous claims.
```
SELECT claim_id, claim_description
FROM insurance_claims
WHERE REGEXP_LIKE(claim_description, 'fraud|fake|frivolous', 'i');
```

Conclusion

Utilizing SQL pattern matching for fraud detection in insurance claims offers insurers a powerful tool to identify and combat fraudulent activities. By leveraging the pattern recognition capabilities within the database, businesses gain an edge in analyzing large volumes of claims data efficiently and effectively. With the ability to detect duplicate claims, anomalous behavior, and frivolous claims, insurers can minimize losses, protect legitimate claimants, and uphold the integrity of the insurance industry.

#fraudDetection #SQLPatternMatching