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Fight Fraud Intelligently with AI and ML

Artificial intelligence (AI) and machine learning (ML) are promising technologies that can help fight evolving cyber-threats from IoT devices in this hyper-connected world

artificial intelligence and machine learning

Massive disruptions caused by technological evolution, innovative business models, and changing customer preferences have changed the dynamics of global economy. Everything is now possible through the internet and at a speed that was unfathomable a few decades ago. Increased digitization is accompanied by an explosion in the amount of data being created every single day. Emerging technologies such as Internet of Things (IoT) are also adding to the oceans of data being generated.

Greater Contribution to Economy

According to Cisco, the number of interconnected devices is expected to reach 50 billion devices by 2020. These devices will include connected cars, meters, wearables and consumers electronics. These smart devices have embedded sensors which enable them to communicate amongst each other and with humans, generating humungous amounts of data in the process. All the data captured through these smart devices is stored in cloud-based environments, making it easy for businesses to access and analyze it remotely.

We are also witnessing easy availability of artificial intelligence-powered, voice-driven assistants that allow residents to remotely manage their smart homes. Globally, there is a surge in the adoption of smart homes, equipped with multiple smart devices. Governments around the globe are also investing in smart city projects for better governance through smart lighting, traffic, waste management and data analytics in order to improve the overall quality of its citizens. This has prompted Deloitte to predict that the world’s top 600 smart cities will likely contribute about 60% of the world’s GDP by 2025.

Increased Vulnerability

Greater adoption of IoT, smart devices, and AI-powered intelligent assistants is making life convenient for customers, but it also means that customers face an increased risk of invasion to their privacy. This is due to passive tracking by these always-on, interconnected devices, which keep transmitting data to the businesses. As a result, businesses are in possession of large amounts of sensitive customer data, including personally identifiable details such as social security numbers, residence address, phone numbers and email addresses. This ocean of data is a treasure chest of patterns, insights and correlations that can empower businesses to provide personalized services and products to their customers. Businesses, across sectors, can analyze data to gain real-time insights and fuel business growth.

While all these smart devices are making life simpler for customers, it is opening up greater challenges. For one, cyber criminals operating in the dark web have a greater opportunity to exploit the security loopholes existing in the smart device networks. The giant network of interconnected smart devices and cloud environments provide cybercriminals with a larger attack surface. As a result, there is a greater risk of customer data getting exposed to cybercriminals who can use the freshly breached customer credentials for fraud and to monetize their exploits.

Using AI and ML to Fight Fraud

Striking a balance between using the right tools to generate value out of petabytes of data while preventing fraud is, therefore, a huge challenge that businesses face. Artificial intelligence and machine learning are promising technologies that can help businesses harness large amounts of structured or unstructured data  [Read now – Data lake based Fraud Prevention Solution to help Businesses Gain Competitive Advantage] and correlate subtle patterns that can be used to fuel business growth as well as ward off cyber threats. With insights and patterns revealed using AI and ML-based solutions, businesses can spot anomalous behaviors and arrest fraud early in its track. However, AI and ML are no silver bullet and businesses must always adopt a ‘breach mentality’ assuming an already compromised environment to remain vigilant.

That said, not all businesses have in-house, high-level data analytics capabilities. Therefore, businesses are fast realizing the need for a partner that can help them use data to gain a competitive edge in this data-driven, cognitive business environment, while keeping fraudsters at bay.

Conclusion

PayPal, through its fraud-prevention service Simility, partners with businesses to help leverage the power of artificial intelligence and machine learning to maintain security of customer data without compromising on customer experience. Simility’s Adaptive Decisioning Platform is an omnichannel fraud prevention platform that analyzes large volumes of structured and unstructured data from various sources, unearths anomalous behaviours, and provides businesses with actionable insights to proactively fight fraud.

To learn how Simility’s AI and ML powered solutions can empower your business to fight fraud while ensuring friction-less customer experience, contact us today.

Gurinder Grewal

Gurinder Grewal

Gurinder Grewal is Senior Director, Enterprise Services Architecture and Infrastructure Engineering at PayPal. He is responsible for the architecture of $100MM+ technology portfolio that serves millions of global users, billions of events/day, maintains 105 PB of data. This platform enables ~$500M annual profit savings. He provides technical leadership to the organization of 500+ engineers. He has 20+ years of experience building, scaling very large complex distributed systems at various companies.
Gurinder Grewal

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