Bent Dalager

Bent Dalager
Equity Partner, NewTech and Financial Services Nordic, KPMGBent Dalager works in the capacity of Equity Partner, NewTech and Financial Services Nordic at KPMG. Bent is also a board member on IT-Branchen and Red Barnet - Save the Children Denmark. He has also served as Managing Director for Financial Services Nordic at Accenture.
News mentions
Man and machine form the perfect pair when it comes to fighting payment fraud, according to a new whitepaper from European payments solution firm, Nets and multi-national professional services provider, KPMG. Fighting Fraud with a Model of Models explains how utilizing human expertise in combination with artificial intelligence (AI) and machine learning (ML) technologies can significantly increase the accuracy of fraud prevention services. Fighting Fraud with a Model of Models Fighting Fraud with a Model of Models explores the theoretical approach behind Nets Fraud Ensemble, an AI-powered anti-fraud engine developed in collaboration with KPMG, which can reduce fraudulent transactions by up to 40% on top of existing AI fraud prevention measures, for the benefits of banks, merchants and cardholders, as well as society in general. Sune Gabelgård, Head of Digital Fraud, Intelligence & Research, Nets, commented, “It’s time for financial institutions to stop playing catch-up with fraudsters and, instead, get ahead of the curve." "The business of fraud prevention has become increasingly convoluted, with the mass adoption of e-commerce, increases in cross-border payments, and the growing popularity of new digital payment methods all adding new layers of complexity”. Financial fraud detection and prevention Machine learning can not only find these, it can analyse and act on them too and prevent fraudulent transactions" Sune adds, “Humans cannot tackle these challenges alone. Until now, the use of true machine learning to fight payment card fraud has been limited. We need it now. There are patterns in the data which are hugely valuable in the fight against fraud, but that are too complex for the human brain to identify. Machine learning can not only find these, it can analyze and act on them too and prevent fraudulent transactions.” Bent Dalager, Nordic Head of NewTech and Financial Services, KPMG, stated, “We have applied an innovative machine learning approach utilizing several machine models in unison. This approach has a clear advantage and generates the most accurate fraud screening. When applied, this next level of fraud monitoring and prevention means banks and merchants can take a big step forward. Not only does it combat crime, it also improves the customer experience and dramatically reduces financial losses.” Nets Fraud Ensemble The ‘brain’ of Nets Fraud Ensemble consists of multiple models working together to analyze each individual transaction within ten milliseconds – the time frame in which a transaction can be safely blocked. The solution learns from the results of its analysis and adjusts accordingly, meaning the longer that it is operational the more fraudulent transactions are blocked, and the fewer false positives are granted. Fighting Fraud with a Model of Models is available to download free of charge from the Nets website. The European fraud landscape With the total annual value of fraudulent transactions across Europe hitting €1.8 billion, the need to step up fraud prevention has never been greater. Card not present fraud now represents almost 80% of the total volume of fraudulent card transactions across Europe. UK banks and card companies prevented £1.66 billion in unauthorized fraud in 2018 alone. This represents incidents that were detected and prevented by firms and is equivalent to £2 in every £3 of attempted fraud being stopped.
Nets, renowned company in the European payments industry, has collaborated with multinational professional services provider, KPMG, to develop Nets Fraud Ensemble, a next-generation fraud monitoring and prevention solution. As the total annual value of fraudulent transactions across Europe hits €1.8 billion, the need to step up fraud prevention, particularly in card not present (CNP) transactions, has never been greater. Reducing transaction fraud is an increasingly convoluted and nuanced business, however, as factors such as the mass adoption of e-commerce, increasing cross-border payments, and the growing popularity of new digital payment methods combine to add new layers of complexity. Nets Fraud Ensemble AI-enabled anti-fraud solution Nets Fraud Ensemble is an AI-powered anti-fraud engine that assists fraud prevention teams Nets Fraud Ensemble is an AI-powered anti-fraud engine that assists fraud prevention teams to navigate this ever-changing landscape in real time. By deploying true machine learning (i.e. a system that identifies emerging fraud indicators as well as established patterns), it represents a significant step forward from the rules-based models that are currently in use across the international banking industry. Sune Gabelgård, Head of Digital Fraud, Intelligence & Research, Nets, said “Although initiatives such as 3D-Secure have done much to make it more secure for people to shop online across Europe, the industry still faces challenges. Many issuing banks have focused on fraud prevention through consumer education, but the industry must also tackle the problem where it starts and where it is orchestrated by organized criminal enterprises: on the internet.” Fraud monitoring and prevention “Nets has significant and proven capabilities in fraud monitoring and prevention, and has been utilizing AI in this area for several years. Nets Fraud Ensemble takes this to the next level. It brings security and value to issuers, merchants and cardholders by blocking fraudulent card-present and card-not-present transactions in real time, creating a real societal benefit by keeping illegally obtained funds out of the hands of criminals. We look forward to our continued collaboration with KPMG to stay ahead of the curve and prevent fraud throughout the value chain.” The ‘brain’ of Nets Fraud Ensemble consists of multiple models working together to analyze each individual transaction within ten milliseconds – the time frame in which a transaction can be safely blocked. Artificial Intelligence solution Nets Fraud Ensemble also decreases operating costs and chargebacks for a better cardholder experienceThe solution learns from the results of its analysis and adjusts accordingly, meaning the longer that it is operational the more fraudulent transactions are blocked, and the fewer false positives are granted. In initial pilot programs, it reduced fraudulent payments by 25% within weeks and up to 40% in the long-term. The benefits to issuers extend beyond achieving significant reductions in fraud. Nets Fraud Ensemble also decreases operating costs and chargebacks, creating an improved cardholder experience. Furthermore, to balance accuracy with customer convenience, issuers can implement customized decision thresholds to minimize false declines. Preventing financial fraud Bent Dalager, Nordic Head of NewTech and Financial Services, KPMG, adds “In terms of tangible reduction of fraudulent transactions, Nets Fraud Ensemble is surpassing all other products currently available. The development of Fraud Ensemble and its state-of-the-art algorithms is the result of Nets’ and KPMG's combined innovation capabilities, AI experience and fraud monitoring and prevention expertise. It's a big step forward in the use of AI to fight fraud."
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