Tuesday 21 June 2011

Fraud Detection & Prevention

The financial industry is facing the fiercest competition in current time after the economic meltdown. Banks are using all avenues to grow their customer base considering the survival aspect. This has lead to tremendous volume growth in banking accounts applications, credit card applications, and financial transactions.

Obviously, as a consequence, the number of fraudulent applications and transactions is also rapidly growing.

With Digital Transformation new payment channels like prepaid cards, e-payments & now mobile-payments, fresh opportunities for frauds are emerging.

Some of the industry research shows that:
  • Credit card frauds losses are over 8 billion USD per year
  • Insurance policyholders have to pay a higher premium up to 5%
  • Total fraud Losses are estimated at over 30 billion USD per year
Frauds can be classified into various categories as below:
  • Credit/Debit/Charge card fraud
  • Check fraud
  • Internet transaction/wire transfer fraud -
  • Insurance or healthcare or warranty claim fraud – overpayments, false claims
  • Subscription fraud – use of telecom services with false credentials
  • Money laundering
  • Identity theft or account takeover
Analytics approaches to detect & prevent Frauds:
  • Combine historical fraud data with industry knowledge & external market data
  • Create a proof of concept to test the history data to determine fraud cases
  • If historical data is not available then anomaly detection or outlier detection is used
  • Apply the statistical model for fraud detection
  • Models are based on past spending patterns, demographic information
  • Further text mining & link analysis for probable associations to find deeper frauds
  • Increased number of identification of fraud cases
  • Dollar savings from fraud prevention adds to the bottom line
  • Protect the customer base from financial loss or identity theft
  • Improvement in service helps to differentiate in the highly competitive market
How companies are using it:
  • Financial institutions using it to identify frauds in leasing contracts
  • Banks are using it to detect credit card, wire transfers, check frauds
  • Insurers are using it to detect fraudulent claims to save the losses
  • Healthcare provider can optimize the medical loss ratio by detecting claims frauds 
Today with help of Big Data platforms, companies can store all the historical data they have which can help in better fraud detection.

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