AI for Fraud Detection and Prevention in Banking Sector

AI for Fraud Detection and Prevention in Banking Sector

AI for Fraud Detection and Prevention in Banking Sector

The banking and fintech sectors found a new breath of life when their services went online a few decades ago. Currently, the financial world uses the most sophisticated technologies at its front end and back end. But at the same time, fraudulent activities have also scaled new heights with the help of technology. The organizations that fall prey to such activities have their financial security, name, and fame at stake.

The initiatives to detect and prevent fraud must be at least a mile ahead of the perpetrators. Artificial Intelligence and machine learning platforms like DigiXT are the need of the hour to tackle such activities efficiently. Here we discuss the use case of AI and why it is significant in detecting and preventing fraud.

What is fraud and why is it important to detect it?

In financial circles, fraud is often the act of unlawfully acquiring a person’s or organization’s money through deception. It could include phishing or identity theft by hacking and so on. This leads to financial loss or defamation (or both) of the person/ organization. Financial security and reputation amount to the credibility of any individual or company. Therefore, it is very important to detect and prevent fraud.

Challenges in Detecting and Preventing Fraud

There are several challenges in today’s time to detect and prevent fraud.

1.      Big Data

The customer details, records, and history form an immensely large and complicated set of data. It becomes humanly impossible to handle such big data to detect any unusual activities or signs of fraud.

2.      Variety of Sources

Right now, most businesses use multiple channels to collect data and provide services. Social media, Online surveys, mobile, brick-and-mortar, etc. are some of the channels. In this case, where would one put in place detectors or software to handle the data?

3.      Need for manpower and time.

It is inconceivable how much manpower and time would be needed to skim through so much data efficiently.

4.      Ever-evolving technology.

Every day new technology sprouts up for fraudulent activities. Most security features such as passwords are static and can be easily compromised.

5.      Huge cost involved.

To be able to tackle all the above challenges, a huge amount of money will have to be invested and still the detection may not be efficient.

How AI Can Help in Overcoming the Challenges

AI is fast, efficient, and cost-effective in handling fraudulent activities. AI platforms like DigiXT act as one-stop solutions to overcome all the challenges that we mentioned here. And to top it all, it has several other advantages too.

·   It can analyze herculean sets of data relating to transactions and others for fraud detection. For example, DigiXT can employ techniques to detect any anomalies in the data. It can identify disruption in patterns and support decision-making. In fact, AI works better if there is a lot of data available to analyze.

·   The architecture is highly scalable and can adjust to the size and span of data. Platforms like DigiXT can support financial planning by analyzing financial data and supporting activities like budgeting and investing.

·   Time is a crucial element in making financial decisions, especially while making investments. AI has a speed of processing and analyzing data that is beyond the wildest imagination of human brains. Employees can spend less time reviewing data and more on productive work.

·   DigiXT helps in risk mitigation and management as well. The system is equipped to quickly analyze risk. It can provide data based on creditworthiness, making it easier to make financial decisions. Investment portfolios of financial organizations can be made better by understanding the risks and having a better picture of the future.

·   AI is always ahead of the game because it is continuously “learning” to tackle new forms of fraud.

·   It is cost-effective. In comparison to the time and manpower that would be required to keep a check on cyber security, AI is a deal to steal!

Use Case Scenarios with AI in Fraud Detection and Prevention

The best characteristic of AI in fraud detection and prevention is its capability to detect anomalies. A platform like DigiXT can combine with the bank’s data analytics software and indicate a red flag when there is a deviation from normal financial transactions immediately.

Predictive analysis is another method used by AI to determine if a particular client is expected to make a certain transaction. For example, if the geographical location doesn’t align with the purchase history or activities of the customer, DigiXT will be able to predict the possibility of fraud here.

At every stage of the relationship with customers, the bank will be equipped with data relating to their compliance. The bank will be aware in case of any violation of laws such as in money laundering. Or simply at the time of analyzing a client for loan dispersal, there would be sufficient information to understand their financial credibility.

Apart from using AI for fraud detection and prevention, it can be used to help customers make better financial decisions. The customer’s data can be analyzed based on previous interactions, browsing history, etc. Relevant recommendations can be given based on this to enhance the customer’s experience. Even decisions relating to asset management can be made more confidently based on the analysis of the asset’s performance. In case the company or customer wants to invest in trading, decisions can be made based on the analysis of the trading algorithm.

The Future of Fraud Detection and Prevention

The best quality of AI is that it is continuously learning and evolving to tackle any possible threats. It is undeniable that the future of fraud detection and prevention in cyberspace and otherwise, lies with sophisticated technologies like AI. The sooner a financial organization transits into using AI, the more efficient will be its operations and relationship with customers.