Fraud Detection and Prevention in the Fintech Industry
Leaving all other industries behind, the fintech industry has become the leader when it comes to bringing digital transformation. In the past few years, it has seen phenomenal growth in the companies engaged in lending and the emergence of innovative business models such as Peer to Peer (P2P) lending, cryptocurrencies, digital insurances, etc.
The days when people had to stand in long queues are long gone. Now, most of the banks provide online services through ATMs, smart voice assistants, multi-channels like web, mobile, tab, pos machines, smart watches, etc. But with the increase in the number of people turning to online banking services, the number of frauds and online scams for fraudulent transactions are also increasing rapidly.
In the fintech industry, the following fraudulent activities are on the rise:
- Fraudulent payment transactions.
- Forging documents and credit scores to get big loans.
- Make purchases with stolen credit cards, debit cards, passwords, etc.
- Stealing account details via telephonic scams.
- Money Laundering
- Forging account statements for tax and loan benefits.
How to Detect and Prevent Fraud?
Banks and other financial institutions lose a lot of money every year because of fraud. So, fraud detection in fintech industry and prevention becomes essential for identifying and blocking suspicious activities. Let us look at some of the ways of preventing and detecting fraud.
Use Machine learning (ML) and Artificial Intelligence (AI) Algorithms
Machine learning (ML) and Artificial Intelligence (AI) algorithms can be employed for fraud detection and prevention. Multiple variables relating to transactions can be analyzed to check for the possibility of fabricated details in the application form. These variables include:
- Employment history
- Digital identities like phone number and email id
Based on the analysis of the above data and by learning the historical patterns in data, the lending companies can decide whether to proceed with a particular application or not. Companies need to remember that fraudsters also keep on coming up with newer ways to bypass the checks in place. Hence, for any company, making the algorithms they use for fraud detection better by training them on newer methods is essential to stay ahead in the game.
Analyze Bank Statements During KYC
The key to fraud prevention and detection is to detect it right at the stage of origination on a real-time basis. Screening all the customers during onboarding can be the right way to go about it. Most banks and NBFCs ask for bank statements of the potential borrowers at the time of onboarding for analysis. Analyzing the bank statement thoroughly gives a lot of information about the customer’s financial behavior.
Traditionally banks employed their employees to assess a borrower’s income. But it was a tedious process and was prone to human errors. To solve the problem, automated bank statement analyzers, called BSA engines, were employed.
In the bank statements, an automated BSA can analyze circular transactions, cheque returns, frequent cash deposits, and withdrawals, etc., to prevent any fraud.
Check Digital Footprint During Customer Screening
Today almost everyone has a smartphone, and they regularly carry out digital transactions. Banks are now checking the digital footprint of new customers while customer screening.
Use Multiple Authentication Processes
Gone are the days when one had to put in their username and password for verifying their identity. With so many banking channels like physical, online, telephonic, mobile, ATM, POS, etc., it is no more safer just to have a simple user id and password as the authentication technique.
As frauds increase, there is a need for a fraud-proof solution, and digital payment systems provide that solution. They use advanced biometrics and authentication techniques so that a payment cannot be forged and only the genuine account holder can authorize a transaction. One can also use digital wallets to prevent any possible fraud.
Monitor Transactions in Real-time
Monitoring transactions in real-time is the key to fighting this fraud. Machine learning and AI can be effectively used to find the fraudulent patterns in the historical transactional data and apply those learning to current transactions as they are attempted. As the fraud monitoring team labels the fraudulent transactions, the AI algorithms learn to understand how the fraudulent transactions differ from genuine ones. These algorithms can take hundreds of variables related to a transaction, including the amount, location, instrument, etc., to predict the likelihood of a fraudulent transaction. Based on this, preventive action can be taken in real-time, including informing the concerned parties or blocking the transaction entirely in extreme scenarios.
In conclusion, fraud detection and prevention in the fintech industry is a continuous process. The fraudsters will never stop duping people and will keep coming up with newer ways to outsmart the financial institutions, fool fraud detection systems, and bypass them.
So, the Fintech industry and the digital payment companies will also need to keep on evolving. They will have to keep improving their algorithms and make them better at identifying newer methods of fraud on online payments.
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