4 ways in which financial institutions are leveraging RPA for fraud detection

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RPA in Fraud Detection
The Banking and Financial Services sector is heavily reliant on standard processes and systems. The BFSI sector is also one that is highly susceptible to fraud and fraudulent behavior. Especially in the wake of COVID-19 and new digital initiatives, there has been a rise in incidents of fraud and the threat is only looking large. As per a Deloitte India survey, the key reasons leading to the rising cases of fraud include the large-scale remote work models, increasing customers leveraging non-branch banking channels, and the ineffective use of forensic analytics tools to find and mitigate potential frauds or threats. The solution lies with leveraging RPA in Fraud Detection that can reduce the overheads associated with traditional fraud prevention processes and get faster, more accurate results.

Failure of traditional models of fraud detection

A majority of banks and financial institutions use rules-based systems with manual evaluation for identifying fraud. These methods worked well in the past but with fraudsters and cyber criminals becoming more sophisticated, the older methods for identifying and mitigating risks are simply not fast enough.

Over the years, fraud patterns have transformed and evolved faster than the rules-based processes. This has led to multiple issues. For instance, false positives or undetected incidents as a result of the high volume of banking data. This is where robotics process automation comes to the rescue.

 

The Banking and Financial Services sector is heavily reliant on standard processes and systems. The BFSI sector is also one that is highly susceptible to fraud and fraudulent behavior. Especially in the wake of COVID-19 and new digital initiatives, there has been a rise in incidents of fraud and the threat is only looking large. As per a Deloitte India survey, the key reasons leading to the rising cases of fraud include the large-scale remote work models, increasing customers leveraging non-branch banking channels, and the ineffective use of forensic analytics tools to find and mitigate potential frauds or threats. The solution lies with leveraging RPA in Fraud Detection that can reduce the overheads associated with traditional fraud prevention processes and get faster, more accurate results.

Implementation of RPA in fraud detection

RPA solutions are ideal for use cases that need to analyse vast reams of data quickly and then apply rules-based actions to it. RPA is then ideal for the automated, repetitive and rules-based financial macros of fraud detection.

Not only is this solution cheaper and faster, it is more efficient as it gets rid of the manual errors and enables the workforce to focus on less tedious and more creative work.

Here’s how implementing RPA can help in fraud identification and mitigation:

1. Reassessing current processes

Banks and financial organisations can program RPA bots to review current and historical financial transactions to find anomalies and atypical patterns that can indicate illegal or fraudulent activities. This also helps at the broader business level because implementing RPA will require the financial institution to study, document, assess the current processes, leading to deeper insights and identifying high-risk areas.

2. Elimination of human errors

By strategically incorporating RPA into the business processes, banks and financial institutions can significantly reduce the human interaction and chances of manual errors. Employers can instead focus on other important tasks, eliminating the chance of clerical errors.

3. Improved trade monitoring

With a rise in financial crimes and money laundering, many companies and government agencies seek the help of intelligent automation to fight financial terrorism. RPA bots, when integrated with other automation technologies, can process each and every transaction for potential fraud and flag high-value transactions as appropriate. RPA’s capability lies in sifting unstructured data and the bots can identify risks much faster than a manual process.

4. Automated threat detection

Monitoring thousands of web pages or reams of application data would be a huge task for any fraud detection team. However, this task would be much simpler, faster, and easier for a bot.

Two of the common use cases where RPA solutions can be leveraged to implement automated threat detection include:

● Copyright infringement

RPA bots prevent copyright infringement by quickly scanning through suspected websites for your confidential or copyrighted information such as patents, trade secrets etc.

● Pricing information

In order to boost sales and steal your customers, many websites or companies may sell your products at lower price points that are impossible to match. One thing that RPA bots do well and quickly is to collect and aggregate pricing information to see whether your offerings are being sold online illegally or set at lower price points.

Why should RPA be used for fraud mitigation?

Fraud impacts various organizations in multiple ways. When an RPA solution is integrated into a well-structured process, the human element can be minimized, leading to faster processes, fewer errors, and improved customer experiences. A survey of 164 Financial Executive International members shows that RPA is underutilized to prevent and detect fraud. The survey highlights some benefits that companies hoped to achieve through RPA. These included reducing employee time on low-value-added tasks, mitigating human errors, and reducing costs.

Benefits of using RPA for fraud detection

Implementing fraud detection bot, banks and financial institutions can see a noticeable difference in the ROI of this automated labour. For instance, time spent in processing requests can be reduced to 50% and exception rate can be slashed to zero. Some of the other benefits include enhanced service-level agreements, reducing hours of manual labour to minutes of automated work, elimination of human involvement in bulk processing etc.

Final thoughts

RPATech’s customized financial bot solutions don’t just help your organisation to save on costs or work faster, it helps you to work smarter. By adopting RPA, you join the league of several other industries and create a competitive advantage. If you want to understand how RPA adoption creates a win-win situation for both your employees and customers, get in touch with us for a consultation.