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시사점"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"}},":itemsOrder":["blog_hero"],":type":"snowflake-site/components/container"},"responsivegrid_content":{"columnClassNames":{"blog_text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-897c5b1a73","text":"\u003Cp\u003E올 가을, 금융 서비스 업계 수천 명의 리더가 Money 20/20 연례 컨퍼런스 참석하여 결제, 규정 준수, 사기 감소, 재무 및 트랜잭션 등과 관련된 동향을 논의했습니다. ‘인간과 기계’이라는 주제가 중점적으로 논의되었지만 AI 외에 실시간 데이터 분석, 보안 및 고객 전략 등 돈의 미래와 관련된 다른 인사이트도 많았습니다. \u003C/p\u003E\n\u003Cp\u003ESnowflake 전문가와 파트너 몇 명과 함께 이번 행사에서 얻은 시사점과 사용 사례의 추세, 그리고 2024년 이후의 은행 및 결제 분야의 발전에서 주목해야 할 부분에 대해 얘기 나눠봤습니다. \u003C/p\u003E\n\u003Ch2\u003E데이터 및 AI 아키텍처 관련 \u003C/h2\u003E\n\u003Cp\u003E“하이퍼 개인화 및 사기 방지와 같은 AI/ML 사용 사례에 집중하기 전에 데이터와 데이터 아키텍처가 전 세계 현지 규제 기관의 요구 사항과 표준을 충족하는 방식으로 조직되고 구조화되어야 합니다. 이러한 요구 사항은 클라우드 인프라 서비스를 활용하여 충족할 수 있습니다. 결제 커뮤니티는 개방형 파일 형식과 개방형 테이블 형식을 이해하고 GPU를 활용하는 최신 클라우드 기술이 향후 새로운 데이터와 데이터 처리 혁신에 어떤 힘을 불어넣을지에 대해 알고 있어야 합니다.” - \u003Ci\u003EPaul Chang, 결제 네트워크 부문 책임자, AWS\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E“데이터 웨어하우스는 지금 많은 힘을 얻고 있으며, Snowflake는 이러한 추세의 최전선에 있습니다. 복잡성 [및] 비용 절감, 제로 카피 데이터 액세스 지원(데이터 거버넌스 중앙 집중화하는 데 이상적임)과 같은 모든 이점을 고려하면 이는 놀라운 일이 아닙니다. 많은 사람들은 이러한 이점이 고객 경험에도 반영되는 방법에 대해 궁금해했습니다. 고객 참여 솔루션에 제로 카피 데이터 액세스를 제공하는 동종 최고의 기술 스택을 통해 마케터는 마케팅 워크플로우를 간소화하고 독립적으로 세분화 또는 이벤트로 인한 경험을 생성할 수 있습니다. 이 모든 것이 효율적이고 확장 가능하며 안전합니다.” -\u003Ci\u003EErin Banka, 산업 마케팅 부문 이사, Braze\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E\"핀테크 스타트업이 확장 또는 실패하는 속도는 AI의 발전에 따라 가속화하고 있습니다. 초기 단계에서 데이터 전략과 다른 엔터프라이즈 애플리케이션과의 협업을 고려하는 것이 더욱 중요해졌습니다. VC와 기업 모두 성장과 ROI 실현으로 가는 짧은 경로에 초점을 맞추면서 투자에 대한 규율을 강화하고 있습니다. 스타트업과 엔터프라이즈 모두의 경우, 배포를 고려 중인 데이터 인프라와 데이터 소스는 명확한 가치 경로를 갖추고 비용 효율적인 규모를 확보할 수 있어야 합니다.” —\u003Ci\u003ESam Shapiro-Kline, 제품 마케팅 부문 이사, TransUnion TruAudience Marketing Solutions\u003C/i\u003E\u003C/p\u003E\n\u003Ch2\u003E생태계도 중요\u003C/h2\u003E\n\u003Cp\u003E“판매자를 포함하여 생태계 전반에서 더 많은 협업 관계를 촉진할 수 있는 기회가 보입니다. 현재는 니즈에 대한 공동의 이해와 일반적인 데이터 협업 부재로 인해 협업에 상당히 방해가 됩니다. 아이덴티 식별과 같은 미디어 및 마케팅 산업에서 흔히 사용되는 몇 가지 기법은 금융 서비스 기업에서 새로운 사용 사례와 새로운 수익원을 가속화할 수 있습니다.” —\u003Ci\u003EPrabhath Nanisetty, 리테일 데이터 및 큐 커머스 부문 리드, Snowflake\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E“금융 서비스 산업의 데이터 리더는 상호운용성 데이터 연결성을 우선시해야 합니다. 금융 생태계가 점점 더 상호 연결되면서 기관은 플랫폼 전반과 서드 파티 파트너와 데이터를 공유하는 동시에 높은 수준의 개인정보 보호 및 규정 준수 기준을 유지하면서 확장할 수 있는 안전한 방법이 필요합니다. 상호운용성은 즉각적이고 원활한 트랜잭션을 위해 고객의 기대에 부합하는 일관된 크로스 채널 경험을 제공하는 데 필수적입니다.” —\u003Ci\u003E리차드 윈스턴, 글로벌 금융 서비스 리더, Slalom\u003C/i\u003E\u003C/p\u003E\n\u003Ch2\u003EAI ROI가 최우선 과제\u003C/h2\u003E\n\u003Cp\u003E“AI가 Money 20/20의 대화를 주도했습니다. 올해 많은 조직이 개념 증명(PoC)에서 실제 AI 구현으로 전환했음이 분명합니다. 하지만 AI는 입증된 ROI 없이 비용이 많이 들고 리소스 집약적일 수 있으므로 어떤 사용 사례가 금융 서비스와 가장 관련성이 높은지에 대해 많은 논의가 이뤄지고 있습니다. 최고 수준에서 두 가지 주제는 분명했습니다. 즉, 효율성을 높이는 동시에 비용을 절감하는 내부 AI 사용 사례와 사용자 경험을 개선하는 상업용 AI 사용 사례입니다. 내부적으로 은행은 데이터 계보 및 데이터 품질 제어를 포함하여 데이터 관리 부담을 줄이기 위해 AI를 사용하거나 콜센터 등에서 비즈니스 인텔리전스를 사용하여 효율성을 높이고 있습니다. 상업적 측면에서는 보안 서비스, 사기 감지 및 위험 분석과 관련된 AI 사용 사례를 들어봤습니다. 이 모두의 공통점은 무엇일까요? “고객이 자연어를 활용하여 은행 데이터에 대한 인사이트와 분석을 얻을 수 있도록 지원합니다.” —\u003Ci\u003EJames McGeehan, 금융 및 결제 부문 책임자, Snowflake\u003C/i\u003E\u003C/p\u003E\n\u003Ch2\u003E새로운 기술을 통해 새로운 기회를 탐색할 가치\u003C/h2\u003E\n\u003Cp\u003E“저렴한 실시간 국경 간 결제 솔루션으로 나타나면서, AI와 디지털 통화(중앙은행 디지털 통화 및 스테이블코인)의 교차점에 대한 관심이 모아지면서 전통적인 금융과 최신 디지털 플랫폼을 연결하는 디지털 통화로의 강력한 전환이 강조되었습니다. 또 다른 핵심 주제는 임베디드 금융의 역할로서, 브랜드는 마찰이 없는 맞춤형 경험을 제공하기 위해 금융 서비스를 자신들의 생태계에 직접 통합하는 방법을 점점 더 많이 모색하고 있었습니다.\u003C/p\u003E\n\u003Cp\u003E가장 영향력이 있으나 아직 논의되지 않은 영역 중 하나는 시스템이 결제를 자동화할 뿐만 아니라 최소한의 인간 개입으로 계정 및 금융 프로세스를 관리하는 자율적인 금융의 잠재력입니다. 자율 금융은 단순히 자동화를 넘어 개인과 기업이 금융과 상호 작용하는 방식을 혁신할 수 있는 잠재력을 가지고 있으며, 이는 사용자 요구를 예측하는 고도로 개인화되고 동적인 접근 방식을 제공합니다. 그러나 이러한 변화는 사용자의 신뢰를 촉진하고 규제 일치를 보장하기 위해 사이버 보안, 개인정보 보호 및 규정 준수 분야의 새로운 표준이 필요합니다.” —\u003Ci\u003E리차드 윈스턴\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E또한, 전문가들은 대화에서 언급된 특정 사용 사례에 주목했습니다. 아래에서, 주목해야 할 세 가지 주요 동향을 살펴봅니다.\u003C/p\u003E\n\u003Ch3\u003E관심 사용 사례 1: 고객 360 및 마케팅 분석\u003C/h3\u003E\n\u003Cp\u003E“금융 서비스 산업은 메시징 경험에서 개인화를 개선하고자 합니다. 이상적으로는 이러한 경험을 강화하기 위해 최소 규모의 고객 데이터를 사용하여 개인화를 극대화합니다. 이 우선순위는 수년 전부터 중요한 주제였지만,마테크 스택의 한계로 인해 기대에 못 미치고 있어, 점점 더 시급하고 중요해지고 있습니다. 이에 따라 데이터 리더들은 마테크 스택의 한계가 고객 경험에 미치는 영향뿐만 아니라 데이터 거버넌스 관점에서 위험을 초래하는 것에 대해서도 서서히 받아들이고 있습니다.  따라서 데이터 리더들은 더 원활하고 안전한 데이터 액세스, 활성화 및 배포를 가능케 하는 동종 최고의 접근 방식에 우선순위를 두고 있습니다.” —\u003Ci\u003EErin Bankaitis\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E“금융 서비스 데이터 리더들은 마케팅을 위한 확장된 데이터 세트에 대한 액세스를 확대하고자 합니다. 이들은 데이터 세트가 마케팅 부서 외부 팀과 마케팅 부서 전반에 걸쳐 여러 사용 사례에 가치를 제공할 수 있는 진정한 자산인지에 대해 점점 더 깊이 생각하고 있습니다. 리더들은 통합 아이덴티 식별을 사용하는 등 마케팅 기술 전반에 걸쳐 데이터를 연결하는 접근 방식이 필요합니다.” —\u003Ci\u003ESam Shapiro-Kline\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E“리테일 업체와 CG는 광고뿐 아니라 혁신을 촉진하고 새로운 제품과 서비스를 개발하기 위해 고객에 대해 지속적으로 자세히 알아보고자 합니다. 은행, 투자 또는 대출 등 금융 서비스 산업 내에서 고객이 어떻게 활동하는지 더 잘 이해하면 다양한 소비자 그룹의 목표, 동인 및 장벽을 더 잘 이해할 수 있습니다. 이는 도시의 식품 사막화를 해소하거나 브랜드를 다른 가격 계층으로 확장하는 것에 대한 새로운 아이디어를 불러일으킬 수 있습니다.” —\u003Ci\u003EPrabhath Nanisetty\u003C/i\u003E\u003C/p\u003E\n\u003Ch3\u003E관심 사용 사례 2: 재무 서비스\u003C/h3\u003E\n\u003Cp\u003E“수많은 시스템과 플랫폼에 걸쳐 있는 방대한 데이터 양으로 인해, 재무 서비스 사용 사례는 AI를 통한 변환의 핵심 사례입니다. 현금 흐름 Forecasting 및 조정을 간소화하고 사기 감지를 지원하는 등 유동성 및 자본 분석에 AI를 도입하는 기능으로 산업 내 승자와 낙오자가 가려질 것입니다. AI는 기업 재무 담당자가 데이터 경험을 혁신하고 그 힘을 민주화하여 ERP 및 기타 회계 시스템을 자연어로 조사할 수 있도록 지원합니다.” —\u003Ci\u003EJames McGeehan\u003C/i\u003E\u003C/p\u003E\n\u003Ch3\u003E관심 사용 사례 3: 사기 감지 \u003C/h3\u003E\n\u003Cp\u003E“반복적으로 등장한 또 다른 주제는 결제 시스템 참가자들이 인식하고 있는 범산업 차원의 강력한 사기 데이터 및 인프라 공유의 시급성입니다. AI와 에이전틱 AI 기술이 발전함에 따라 기회와 함께 도전 과제가 발생하고 있습니다. 이 두 기술은 더 효율적이고 안전한 결제 역량 강화를 약속하지만 동시에 악의적인 행위자는 AI를 점점 더 정교한 방식으로 활용하여 더 감지하기 어려운 형태의 트랜잭션 사기를 창출하고 있습니다. \u003C/p\u003E\n\u003Cp\u003E이러한 기술 진화는 집단적 방어의 중요성을 강조합니다. 광범위한 참가자 네트워크에 걸쳐 사기나 비정상적인 트랜잭션에 대한 인사이트를 통합하여 산업은 AI 기반 위협에 대한 회복탄력성을 강화할 수 있습니다. 그러한 협업 데이터 공유는 더 강화된 생태계를 창출할 것입니다. 많은 사람들의 집단적 인텔리전스는 단일 기관이나 소규모 그룹만으로는 구현할 수 있는 것보다 훨씬 강력한 방어선을 제공합니다.” \u003Ci\u003E—Richard Winston\u003C/i\u003E\u003C/p\u003E\n\u003Cp\u003E\u003Cbr\u003E\n금융 서비스 미래에 대해 자세히 알고 싶으신가요? \u003Ca href=\"https://www.snowflake.com/webinars/thought-leadership/2025-financial-services-data-ai-predictions/?utm_cta=website-blog-money-2020-2024-takeaways-wb\" target=\"_blank\"\u003E2025 금융 서비스 AI 및 데이터 예측 웨비나\u003C/a\u003E에 등록하거나\u003Ca href=\"https://www.snowflake.com/ai-blueprint-financial-services-enterprise-ai/?utm_cta=website-blog-money-2020-2024-takeaways-ebk\" target=\"_blank\"\u003E \"AI 금융 서비스 블루프린트: 엔터프라이즈 AI로 거듭나기 위한 방법\u003C/a\u003E”을 사본으로 받아보세요.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnClassNames":{"premium_content_bann":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{"premium_content_bann":{"id":"premium-content-banner-89c56dd252","contentEyebrow":"Webinar","contentHeadline":"2025 Financial Services AI & Data Predictions","contentDescription":"Join a panel of financial services data, tech and AI experts as they discuss how data and enterprise AI will transform both workflows and business strategy.","showImage":true,"image":{"id":"image","lazyEnabled":true,"alt":"Photo illustration of digital numbers and a performance bar chart overlaid on a skyscraper 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