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Prevent Fraud with AI

Mike McNamara
Mike McNamara
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According to a recent study, credit card fraud in the United States is expected to reach $12 billion in 2020. Rules-based expert systems currently used to catch fraud have become too easy to beat. In addition to combating fraud, financial services institutions are also challenged to make the right credit decisions, improve risk management, enable fast, insightful trading, and develop personalized services—all while elevating the customer’s experience.



The financial services sector generates a wide variety of data types. Analysis can include transaction history data from banks, smartphone data, real-time structured and unstructured data, a client’s behavior, location, and buying habits, and speech data from banking call centers. The different data types contribute to different aspects of financial services, including credit decisions, risk management, fraud prevention, trading, measures against money laundering, and personalized banking.

To address these challenges, the financial services industry is increasingly relying on artificial intelligence (AI) and machine learning (ML) technologies. With NetApp® ONTAP® AI, banks and other financial institutions can leverage the deep insights gained from AI and ML operations to improve their defenses against fraud and better serve their customers.



ONTAP AI combines NetApp cloud-connected all-flash storage with NVIDIA servers for a high-performance, easily scalable solution that is proven to handle workloads such as credit risk assessment, large trade execution, natural language processing, fraud prevention, and cybersecurity.

AI can be a powerful tool in reducing risk, eliminating fraud, and protecting customer endpoints. To be successful, you need a data management solution that can keep up. ONTAP AI gives you all the performance you need to feed, train, and operate your applications so they can quickly and accurately detect illegal or suspicious financial activity. With data coming in from multiple, disparate sources such as smartphones, call centers, earnings call transcripts, SEC filings, and more, financial institutions must find a way to harness and extract the most value from it as quickly as possible. That requires powerful AI capabilities that reach from the edge to the core to the cloud. NetApp ONTAP AI Reference Architecture for Financial Services Workloads offers guidelines for customers who are using ONTAP AI to build an AI infrastructure for financial sector use cases. The document focuses on addressing the challenges in the training phase.

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Mike McNamara

Mike McNamara

Mike McNamaraは、NetAppの製品およびソリューション マーケティング担当シニア リーダーであり、25年以上にわたってデータ管理とクラウド ストレージ マーケティングに携わってきました。10年以上前にNetAppに入社する前は、Adaptec、Dell EMC、HPEで勤務していました。また、主要なチーム リーダーとして、ファーストパーティのクラウド ストレージ サービスや、業界初のクラウド対応AI/MLソリューション(NetApp)、ユニファイド スケールアウトおよびハイブリッド クラウド ストレージ システムおよびソフトウェア(NetApp)、iSCSIおよびSASストレージ システムおよびソフトウェア(Adaptec)、ファイバチャネル ストレージ システム(EMC CLARiX)の発売を推進しました。過去には、Fibre Channel Industry Associationのマーケティング分野の議長を務めたこともあり、Ethernet Technology Summitの諮問会議や、Ethernet Allianceの現役メンバーとして、業界誌に頻繁に寄稿しているほか、各種イベントにスピーカーとして数多く登壇しています。さらに、FriesenPressより『Scale-Out Storage - The Next Frontier in Enterprise Data Management』というタイトルの書籍を発行しているほか、KaposによりB2B製品マーケティング担当トップ50に選出されたこともあります。Mike McNamaraのすべての投稿を見る

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