According to data available from the Reserve Bank of India , the fourth quarter ended March 2023 itself witnessed payment frauds of over Rs 800 crore under the new format of fraud reporting.

These findings should be concerning for bank managers across the country. While the amount may not seem significant as compared to the volume of transactions, it reveals vulnerabilities in banks’ anti-fraud mechanisms.

Caption: Number of bank fraud cases across India from FY 2009 - 2022

Source

Increased adoption of digital payments and digitalisation of the financial ecosystem has led to the rise of identity theft and cybercrime .

In this piece, we’ve put together a guide on the common types of frauds and how banks can detect and combat them effectively.

What is Banking Fraud Detection?

Banking fraud detection refers to financial institutions' strategies, techniques and systems to identify and prevent illicit activities that may lead to financial losses.

Vast amounts of data from various sources, such as transaction records, customer profiles, and external databases are analysed to identify patterns, anomalies, and behaviours inconsistent with typical banking activity.

These irregularities could indicate potential fraud. Once potential fraud is identified, the bank can take steps to investigate and prevent further fraudulent activity.

Types of Banking Fraud

Banking fraud undermines consumer confidence in banking institutions. Some of the most common types of fraud are:

1. Identity theft

Fraudsters impersonate individuals to gain access to their banking accounts and carry out unauthorised transactions. They trick customers into revealing their personal and banking information through a process called phishing, wherein they pretend to be a trusted entity and solicit sensitive information. 

2. Credit card fraud

Scammers gain access to a customer's credit card information and make unauthorised transactions. It may happen through skimming, online hacking or physical theft.

3. Loan fraud

Individuals or organisations provide false information when applying for loans, intending to default once the loan is disbursed.

4. Cheque fraud

Scammers forge, alter, or create counterfeit cheques to make fraudulent deposits or withdrawals.

5. Online and mobile banking fraud

Fraudsters hack into online bank accounts of customers or use malware to steal sensitive information.

6. Wire transfer fraud

Fraudsters trick bank employees into transferring money from the bank to a fraudulent account. 

Deloitte found that data theft, cybercrime, third-party fraud, bribery and corruption and fake documentation have been the most common types of banking fraud between 2019 and 2021.  

Challenges in Banking Fraud Detection and Prevention

The need to balance security with a smooth customer experience is a blocker in banking fraud detection and prevention. The major challenges are:

1. Sophisticated fraud schemes

Fraudsters are good at adapting to existing security measures and developing new methods to exploit vulnerabilities. 

Banks need to be one step ahead at all times. They must take stock of existing security measures and improve on them regularly, perform periodic employee training to ensure awareness of the latest types of security risks, and keep a close watch on emerging trends in banking fraud. 

2. Growth of digital banking channels

Online and mobile platforms have opened up multiple vulnerabilities for fraudsters to exploit. Cybercriminals employ sophisticated techniques, such as malware, phishing, and hacking, to steal sensitive banking information and impersonate customers.

In FY 2021-22, card or internet-based transactions were the leading type of fraud in terms of the number of transactions, whereas advances-related fraud were the highest in terms of the quantum of money involved. 

Thus, banks must implement advanced cybersecurity measures and machine learning algorithms for threat detection and prevention. 

3. Balancing security measures with customer experience

Financial institutions have to master a tricky balancing act: maintaining robust security while ensuring a seamless customer experience.

Excessive security protocols, such as multiple authentication steps, might deter fraudsters but could also frustrate genuine customers, leading to poor user experience and potential customer loss. 

4. Compliance 

The banking sector is heavily regulated to deter and detect fraud. Complying with the guidelines can be complex and time-consuming. It involves regular audits, ongoing employee training, and potential restructuring of business practices. 

Non-compliance attracts penalties, damage to the bank's reputation and loss of customer trust.

5. Money laundering

Money laundering, a process where illicitly-obtained money is ‘ appear legal, is a complex form of banking fraud.

Banks have systems in place to detect suspicious activities that could indicate money laundering. These systems study customer behaviour and transaction patterns and have robust customer due diligence procedures. 

However, the advanced techniques used by money launderers make detection incredibly challenging and require constant updates of preventive mechanisms. 

7. Streamlining customer onboarding 

The customer onboarding process is a critical point where security must be stringent to prevent fraud, but it's also a stage where a good impression matters.

A lengthy or complicated onboarding process can deter potential customers. 

Thus, banks need to create a secure yet straightforward and efficient onboarding process. This involves carefully checking the credibility of new customers without making the process overly cumbersome.

8. Preventing credential theft

Credential theft, where fraudsters steal customer login information, is a significant source of banking fraud. 

Preventing this type of fraud means educating customers about secure practices, such as not sharing passwords and implementing security measures like automatic logout and account lock after several failed login attempts. 

Despite these efforts, controlling the external environment, where customers may fall prey to phishing scams, is a challenge for banks.

5 Ways to Detect Fraud in Banking 

Here are five ways that banks can detect and prevent fraud:

1. Implementing robust internal controls

Internal controls play a crucial role in fraud detection in banking. They encompass a set of rules, policies, and procedures to detect and prevent fraudulent activities.

This could include dual controls for critical operations, regular audits, segregation of duties to ensure that no single individual controls all parts of a financial transaction, and rigorous vetting procedures for new staff.

Strict adherence to internal controls can help identify suspicious activities and nip them in the bud before they snowball into full-blown fraud.

2. Empowering customers with knowledge and tools

Given the right knowledge and tools, customers can be the first line of defence against banking fraud. Banks should conduct regular educational campaigns on common fraud tactics, security best practices and ways to detect fraud.

A KPMG survey found that customers are key to preventing and detecting fraudulent activity on their accounts.

Banks can provide customers with the tools to monitor their accounts, set transaction limits, receive immediate alerts for unusual activity, and report suspicious transactions.

3. Vigilant transaction monitoring

Banks need to constantly monitor transaction patterns to identify anomalies that may indicate fraudulent activities. Suspicious behaviours can include extensive transactions, multiple transactions in a short period, transactions from a new device or location, or frequent password changes.

Banks can quickly investigate suspicious activities and mitigate potential losses by implementing systems that monitor these patterns and generate alerts for potential fraud. With DeviceConnect , lenders can analyse transaction data in real time, facilitating faster identification and response to potential fraud.

4. Leveraging real-time data enrichment tools

Real-time data enrichment tools gather and analyse data from multiple sources instantly to give banks a more comprehensive view of each transaction. This allows banks to assess the risk of fraud more accurately.

For instance, if a customer who usually transacts in small amounts suddenly makes a large transaction, a product such as DeviceConnect can flag it for review. Such tools can also correlate data from different sources to identify complex fraud patterns that might otherwise go unnoticed.

DeviceConnect transcends standard monitoring capabilities by offering seamless, real-time surveillance of transactions and account activity. This enables banks to promptly identify and address any unusual or suspicious behaviour, such as sudden large transactions from a typically small-scale customer.

It also offers automated data collection and integration, vastly simplifying the process of gathering and interpreting large amounts of financial data. This ensures that banks can identify complex patterns and anomalies that could indicate fraudulent activity, further enhancing their fraud detection capabilities.

5. Harnessing the power of machine learning and artificial intelligence

Machine learning (ML) and artificial intelligence (AI) are transforming the fraud detection landscape. As they continue to be deployed more widely in banking, we're seeing positive impacts on fraud rates. 

As an example, fraud cases involving amounts over Rs 100 crores in the banking sector showed a significant decline, with incidents totaling Rs 41,000 crores in 2021-22 compared to Rs 1.05 lakh crore in the preceding year. The number of fraud cases in both private and public sector banks dropped to 118 in FY22 from 265 in 2020-21, according to The Hindu .

This achievement was due in part to the implementation of advanced technologies, including ML algorithms. In 2021-22, the Reserve Bank of India (RBI) assessed the effectiveness of its Early Warning System (EWS) framework in select banks using ML algorithms. This allowed the RBI to enhance its system's efficiency and better detect patterns indicative of fraud, and respond more swiftly to suspicious activities.

ML algorithms have the unique capability to adapt to evolving fraud tactics, making them indispensable in identifying new and emerging types of fraud. AI, on the other hand, can mimic human intelligence to detect fraud by identifying anomalies in data, patterns of transactions, and subtle changes in customer behaviour.

Even in high-profile cases such as the State Bank of India (SBI) fraud totaling Rs 22,842 crore or the Rs 34,615 crore case involving Dewan Housing Finance Ltd (DHFL), these tools offer powerful ways to recognize and prevent fraudulent activities.

Banking Fraud Detection Checklist: Key Strategies and Technologies

Here are some of the key strategies and technologies used by banks to detect banking fraud:

1. Behaviour analytics

Behaviour analytics involves analysing how users interact with banking systems to detect unusual or suspicious behaviour. It considers factors like transaction patterns, activity time,  and location to identify potential fraud.

For example, if a customer who typically uses their account in New York suddenly starts making transactions in Moscow, that's a red flag that would trigger a review.

2. Device fingerprinting

Device fingerprinting is a method of tracking devices for the purpose of fraud detection. It collects data about a device, such as the IP address, device type, operating system, and browser type, to create a unique fingerprint’.

If the same device is used for fraudulent activities, it can be flagged for review. This method is especially effective at identifying repeat offenders and preventing account takeovers.

3. Real-time transaction monitoring

FinBox’s in-device risk engine, DeviceConnect, is designed to enhance real-time transaction monitoring. This tool integrates with your existing systems to provide instant data enrichment. By capturing and analysing data from multiple sources, it can give you a more comprehensive view of each transaction and assess the risk of fraud more accurately.

Adapting to the Future of Banking Fraud Detection

Banks need to stay ahead of fraudsters by developing innovative solutions that can adapt quickly to changing trends.

Here's what banks can do:

1. Adopt emerging technologies

Technologies such as AI and ML are changing the game by enabling the analysis of large data sets at an unprecedented scale and speed.

AI can identify patterns and anomalies in data that may suggest fraudulent activity, whereas ML allows systems to learn and adapt to new tactics used by fraudsters continually. 

2. Continuous improvement and staying up-to-date

Banks must invest in regular staff training, system upgrades and stay updated on emerging trends in fraud tactics in order to ensure that its systems are equipped to counter evolving threats.

3. Collaboration between banks, businesses and customers

Fraud detection should be seen as a shared responsibility between banks, businesses and customers. 

Banks can play a pivotal role by encouraging collaboration. This includes sharing information about emerging threats and effective preventative measures with other financial institutions and regulatory bodies. 

Banks should also regularly communicate with their customers, providing them with tools and education to help them guard against fraud.

Wrapping Up

Timely detection of fraudulent activities helps lenders mitigate losses, protect reputation and ensure compliance with ever-evolving regulatory frameworks. With increasing consumer expectations and tightening regulatory requirements, businesses cannot afford to ignore fraud detection and prevention strategies. 

With DeviceConnect , you can effectively monitor your entire network for fraudulent activities in real time. The solution offers out-of-the-box features such as geolocation, device interaction analytics, and behavioural analysis to identify and prevent fraud.

Schedule a free demo and learn how DeviceConnect can help you build a robust fraud detection and prevention system that is scalable, flexible, and customisable to meet your business needs.