By Dhruv Verma
The business of loyalty and reward points has undergone a significant transformation in the past few years. From a transactional model, it is now moving to an experiential model. With new-age technology coming in, artificial intelligence is now revolutionizing loyalty programs. Now companies can focus better on increasing customer happiness and retention. But like everything, this too has its cons. Loyalty programs that were simple for customer retention have now become exposed to fraudsters. To protect the integrity of these programs and safeguard both businesses and consumers, artificial intelligence (AI) is emerging as a weapon in the fight against fraud.
The implementation of AI is emerging as a tool to protect such programs and help safeguard businesses and consumers in general.
The Role of AI in Fraud Detection
AI-powered fraud detection and prevention provides a secured solution to the above-explained challenge. AI algorithms analyze significant amounts of data for patterns and anomalies indicative of fraudulent behaviour. Here are some ways in which AI is being implemented to fight loyalty program fraud:
1. Anomaly Detection
Pattern Recognition: AI can identify unusual patterns of activity with strange behaviour, helping find potentially fraudulent activity. With the power of historical data, AI models can drive out subtle deviations that probably escape the human eye of the analysts.
Real-Time Monitoring: Given that analyses of transactions are always going on, suspicious activity will be detected as it is taking place, enabling timely steps to be taken against those actions. This proactive stance of the measure guarantees that potential fraud is detected and mitigated before it can inflict damage.
2. Predictive Analytics:
Risk Scoring: In this, AI can assign risk scores to any kind of transaction or account using past data and predictive modelling. This will ensure a proportional allotment of specialists with the appropriate levels of resources for investigations. This way, resources are only being expended on the most suspicious cases, thereby enhancing the efficacy of the whole regime.
Behavioural Profiling: Based on detailed models of typical user behaviour, AI can detect deviations that may indicate fraud. This makes fraud detection substantially personalized, increasing its accuracy and lowering the number of false positives.
3. Machine Learning Model
Supervised Learning: Learning from labelled datasets helps AI recognize known types of fraud and therefore increases the rate of detecting fraud. This opportunity allows the solution to tune its accuracy, for example, through examples from the past about fraudulent and legitimate activities.
Unsupervised Learning: Through clustering and outlier detection, the AI will be able to reveal patterns, both new and developing ones, in fraud which was indiscernible before. Such a capacity is acutely necessary to be at par with developing fraud techniques.
4. Data Integration
Cross-Channel Analysis: For an all-round view of possible fraud, AI can be fed data from multiple sources, including purchase history, account activity, and social media. This all-encompassing look is expected to lead to more accurate detection results.
Third-Party Data: Allowing the integration of external data, including blacklists and known fraud databases, better helps AI spot fraud. It allows AI to cross-verify and validate suspicious activities effectively.
5. Automated Responses
Immediate Actions: Automated systems can place a temporary hold on all the activities in the account or mark the specific transactions for review without any human intervention, thereby minimizing the time window available to the fraudster. Hence, early action will be taken to prevent possible escalation of fraud.
Alerts and Notifications: Instant alerts to customers and administrators when a suspicious activity is detected to help take timely actions. Such notifications help reduce potential losses and comfort concerned customers with secured accounts.
Benefits of Using AI in Preventing Fraud within Loyalty Programs
The right integration of AI in loyalty programs can boost accuracy in fraud detection significantly, hence bringing down the incidence of false positives to avoid inconveniences faced by customers. This results in more effective fraud prevention and better experiences for the customer. It also ensures low financial loss to the consumer. Fraudulent activities are prevented by business entities only by ensuring that the leakage of money is well maintained, hence an improved bottom line. Effectiveness in fraud prevention results in significant financial savings.
AI can also help in enhanced customer experience wherein customer trust and loyalty are instilled by a securely implemented loyalty programmer. With AI, businesses could meet the requirements of regulations on data privacy and ensure the secure handling of customer information. Observation of such regulations guards the business and most importantly the customers against any allegations.
In conclusion, Artificial Intelligence today is reshaping how we prevent loyalty scheme conmen by offering us a data-based means to identify and stop these acts of deceit. Organisations ought to utilise AI to protect their reward systems, ensure profit safety measures are observed as well as keep consumer faith intact. It is expected that with faster improvements in AI technology, there will soon be a slowdown in any type of fraudulent activity. Thus, it is essential for companies to invest in the right tools and to fight fraud actions so that new threats cannot catch them off guard.
The author is founder and CEO of Thriwe. (Views expressed are the author’s own and not necessarily those of financialexpress.com)