Explore resources related to insurance analytics.
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Article
Beyond IFRS 17 – what's next?IFRS 17 is not just a new accounting standard. Its fundamental objective is to provide transparency and insight to the insurance business while identifying strengths and areas for improvement. Learn how to keep a long-term vision and achieve broader business value beyond the immediate demands of IFRS 17.
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Customer Story
Improving loss ratios and profitabilityTriad Analytic Solutions helps insurers benefit from advanced analytics.
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Аналитический отчет
Top Strategic IoT Trends and Technologies Through 2023In this report, Gartner examines 10 longer-term IoT technologies and trends that will be important in the 2018 through 2023 time frame.
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Технический документ
Return on Information: The New ROIThis paper explores the techniques and technology available for taking advantage of big data so insurers can price better, expand markets and improve the business of underwriting risk and handling claims.
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Технический документ
Solvency II Compliance and beyond: The essential steps for insurance firmsFor the last 30 years, insurance companies have been bombarded with new and increasingly diverse regulations, all designed to validate that insurers are financially stable. The largest transformation of European insurance legislation to date, Solvency II is meant to protect policyholders and minimize market disruption by setting stronger requirements for capital adequacy, risk management and disclosure. Although it’s a long and difficult journey for many insurance companies, the new guidelines are just the beginning of a new risk management playbook. Learn about the essential steps that insurance companies need to complete to ensure Solvency II compliance – and beyond – with the ability to support enterprise risk management.
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Customer Story
Бразилия борется со страховым мошенничеством с помощью ИИ и аналитики.CNSeg полагается на SAS, чтобы препятствовать мошенникам, и повышает точность оповещения на 67%
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Технический документ
Fighting Insurance Application Fraud Learn about the advantages of using analytics-driven methods for authenticating applicants to reveal customer gaming, agent gaming and potential future claims fraud.
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Технический документ
LDTI Should Spell OpportunityComplying with the Long-Duration Targeted Improvements standard presents major challenges to insurance companies. At the same time, it offers them the opportunity to modernize business processes and information systems.
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Технический документ
Implementing Analytics for Claims Fraud InvestigationA successful analytics solution will radically change life for an insurance company’s special investigative unit, generating higher-quality referrals an average of six times faster.
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Технический документ
Demystifying AnalyticsTo educate and inform insurance companies about how they can move toward becoming an “analytic insurer” – one that embeds analytics into daily operations to make better decisions that reduce costs, improve pricing and more.
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Технический документ
Driving Growth in Insurance With a Big Data ArchitectureThe SAS® and Cloudera Advantage
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Технический документ
LDTI: Finding a solution for today and tomorrowSAS can help insurers address the data and technology complexities of LDTI with a solution that solves the problems of today while looking ahead to obstacles of the future.
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Технический документ
The State of Insurance Fraud TechnologyFor the third consecutive time in six years, insurers report increasing amounts of suspected fraud. Nearly three-quarters of insurers in the 2018 survey say fraud has increased, an 11-point increase since 2014. The expansion in anti-fraud technology does have growth pains, however. Insurers report increased frustration with integrating data into their systems and continuing problems with high levels of false positives.
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Технический документ
Data is KingLearn about the benefits of building an analytical data warehouse based on an insurance-specific data model so insurance companies can gain the most out of their investment in business analytics.
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Customer Story
Advanced analytics can detect and prevent insurance fraud before losses occur | SAS -
Customer Story
Healthier lives for our four-legged friendsAgria uses SAS to provide better care for pets and peace of mind for their owners.
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Технический документ
Effective fraud analytics: 10 steps to detect and prevent insurance fraudInsurers that follow the 10 steps outlined in this paper offer the best chance for detecting both opportunistic and organized fraud.
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Article
Монетизация данных в эпоху цифровой трансформации: роль и задачи ИТЦифровая трансформация стала основной темой обсуждений на недавней 22 ой конференции «ИТ в страховании». Участники сошлись во мнении, что внедрение и применение аналитических технологий для монетизации данных уже стало обязательным условием для качественных преобразований в отрасли.
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Вебинар
Новый всплеск страхового мошенничества после COVID-19Вебинар основан на богатом практическом опыте SAS в области создания Аналитических Антифрод-систем для российских и международных страховых компаний.
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Customer Story
Турецкая страховая компания обнаруживает мошенничество в режиме реального времениAksigorta uses advanced analytics to increase fraud detection rate by 66 percent.
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Customer Story Страховой Дом ВСК выстраивает процессы целевого маркетинга с помощью SASАналитическая CRM-система SAS позволила ВСК автоматизировать и значительно повысить эффективность целевых маркетинговых кампаний.
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Технический документ
Fraudsters love digitalBy incorporating fraud analytics as a first line of defense, insurers can build in safeguards for all of their digital programs. In turn, they can spot emerging fraud rings, emerging fraud trends, and make real-time decisions on claims recovery to reduce leakage.
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Article
Страхование: мошенникам вход воспрещен!Как выявить, что вас обманывают агенты и страхователи, а также распознать первые признаки будущего мошенничества.
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Аналитический отчет
SAS is a Leader in The Forrester Wave™: Enterprise Fraud Management, Q3 2021Due to faster changing patterns in payment and nonpayment fraud, risk modeling has transitioned from an annual or semiannual campaign to a continuous activity that financial institutions cannot ignore.
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E-Book
Four Use Cases Show Real-World Impact of IoT This TDWI e-book explores in detail what IoT means and how different industries are taking advantage of it.
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Технический документ
Using Digital Identity To Unleash Organizational DataCustomer experience focuses on speed and ease of access, lowering friction where possible. However, this approach has the potential to open up an organization to fraudulent attacks.
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Вебинар
Автоматизация процессов урегулирования убытков в автостраховании в новых реалияхКак не потерять клиентов и снизить издержки. Стратегия, проблематика, практика
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Технический документ
Understanding Data Streams in IoTThis paper explains how streaming analytics helps you acquire, understand and use real-time, streaming data to make fact-based, automated decisions – and instantaneously react to new information.
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Article
5 Challenges for IoT in the insurance industryIoT promises to substantially reduce losses in the insurance industry, but adoption is low. That will change when the industry overcomes these five challenges.
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Customer Story Ингосстрах повышает качество портфеля полисов КАСКО с помощью SASВнедрение аналитической платформы SAS помогло страховой компании отладить процессы проверки потенциальных клиентов и оценки рисков.
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Технический документ
Insurers: Are You Ready for IFRS 17?This white paper tells you what to look for in an IFRS 17 solution and explains why insurers should be taking action now to prepare for the new requirements.
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Технический документ
The Art and Science of ReinsuranceThis white paper explains how reinsurers can gain a competitive advantage by turning to technology for catastrophe modeling, data analytics and geospatial information systems (GIS) to better understand the data and their risk exposure.
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Технический документ
Opportunities for Insurers: Operationalizing Analytics As insurers expand the applications of analytics across business functions – underwriting to claims to marketing – they have to master the basics: quality data, business and analytical skills, and focused strategy. To explore what it takes to operationalize analytics in the insurance industry, IIA spoke with Jim Hulett, Insurance Solutions Consultant in the Global Security Intelligence Practice at SAS.
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Технический документ
Advanced Analytics For Dissolving Data SilosThe growing need for data storage has heightened the proliferation of data silos. Readers will learn how organizations can apply machine learning and artificial intelligence to battle fraud, confirm customer identities and build data systems to avoid potential silos.
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Article
IFRS 9 and CECL: The challenges of loss accounting standardsThe loss accounting standards, CECL and IFRS 9, change how credit losses are recognized and reported by financial institutions. Although there are key differences in the standards for CECL (US) and IFRS 9 (international), both require a more forward-looking approach to credit loss estimation.
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Технический документ
The Connected InsurerExplore the opportunities IoT creates, the barriers to its adoption within the insurance industry, and what’s needed to fully exploit the potential of IoT for competitive advantage and growth.
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E-Book
Becoming a data-driven organizationLearn about the three foundations of becoming data-driven – data management, analytics and visualization – and how they can increase profitability, boost performance, raise market share and improve operations.
Blogs: Insurance
Blogs: Insurance
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