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DataVisor 2020 Predictions: Friction Is For Fraudsters In 2020

VMblog Predictions 2020 

Industry executives and experts share their predictions for 2020.  Read them in this 12th annual VMblog.com series exclusive.

By Yinglian Xie, CEO and co-founder of DataVisor

Friction Is For Fraudsters In 2020

Enhancing customer experience while mitigating risk through the application of advanced machine learning capabilities will move friction away from good customers and towards fraudsters.

2020 will be the year machine learning fully and finally transforms from luxury to necessity across all industries.

Striking The Right Balance Between Customer Experience and Risk

This transformation will be driven by the collective realization that it is only through the application of advanced machine learning solutions that enterprises can effectively deliver exemplary customer experiences without simultaneously incurring additional risk. Even comparatively traditional and highly regulated businesses will connect the dots between customer experience and risk management, as they fully integrate comprehensive fraud management into their customer acquisition and retention strategies.

The rewards of this transformation will include:

Real-Time Holistic Analysis

Drawing on the power of unsupervised machine learning, businesses will be able to holistically analyze massive volumes of data in real time, without the time-wasting hindrance of historical labels and the ongoing need to retune outdated models.

Accuracy and Speed

Advanced feature engineering capabilities will enable businesses to achieve higher degrees of monitoring and detection accuracy even as they reduce false positives and improve operational efficiency.

Centralized Intelligence

Organizations will evolve from outmoded lake and repository thinking to embracing the centralization of intelligence as they advance their abilities to derive genuinely actionable intelligence from vast troves of unlabeled data.

Adding Friction for Fraudsters

The application of advanced data analysis approaches powered by unsupervised machine learning-specifically, the use of clustering and graphic techniques-will enable businesses to be far more proactive about how they monitor user actions and accounts, and how they engage with their customer bases.

Holistic analysis and early detection will curb the widespread registration of fake accounts, block burgeoning malicious actions and attacks, and flag and neutralize massing bot armies before downstream damage can occur. Simultaneously, the use of these techniques-which represent a move forward from outmoded rules-oriented strategies that result in high false positive rates-will serve to remove friction from the experiences of good customers, and ramp up friction for bad actors by blocking their efforts before they can even mount their attacks, and by making it exponentially more difficult to obfuscate their digital footprints.

Winning With Trust

Organizations that successfully protect their customers-and that consistently demonstrate their commitment to keeping customer data and information safe-are going to make significant competitive gains and see increased growth. As customers across industries and sectors-from marketplaces, e-commerce, and social media, to financial services, healthcare, and insurance-continue to make the connections between trust and safety solutions and their positive experiences, they will, in turn, increasingly give their loyalty to those businesses and platforms that are demonstrably proactive about embracing comprehensive fraud management. In short, gaining and maintaining customer trust will be a key competitive business advantage.

Ultimately, what we will see in 2020 is the positive blurring of lines between customer experience and risk management. Will we see widespread acknowledgment that these are interdependent concepts, and that successful strategies to promote each are mutually beneficial. With the universal adoption of advanced machine learning capabilities, we will see enterprises across sectors successfully striking the right balance between customer service and risk.

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About the Author

Yinglian Xie, CEO and Co-founder

Yinglian Xie 

Yinglian Xie is the CEO and co-founder of DataVisor, and a leading expert in the area of Internet security, privacy, distributed systems and networking. Her work focuses on fighting large-scale attacks to online services; she combines parallel-computing techniques, algorithms for mining large datasets, and security-domain knowledge into research aimed at preventing and combating attacks that range from fraudulent online payments, spamming, service-abuse and user-hijacking attacks to search-result poisoning and malvertising.

Prior to DataVisor, Yinglian was a Senior Researcher at Microsoft Research Silicon Valley where she developed a number of groundbreaking technologies designed to secure Microsoft's consumer-facing web properties.  She worked closely with many product groups at Microsoft to implement a series of new techniques still in production today.  

She has been widely published in top security, networking and systems conferences, serving on many of their committees, and has filed more than 20 patents. Yinglian received her Ph.D. in Computer Science from Carnegie Mellon University.

Published Wednesday, December 11, 2019 7:45 AM by David Marshall
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