Financial Industry AI: Presenting Implementable Technologies, Business Application Methods, and Success Cases
Enterprise Machine Learning Platform 'SAS Viya' Supporting Enterprise-wide Analytics Lifecycle and Technical Support

SAS Korea held a financial seminar today at the Westin Josun Seoul Hotel, addressing approximately 180 key financial industry stakeholders. The company presented strategies for building an optimal enterprise machine learning platform and leveraging analytical synergies across the entire organization.

The financial industry has recently been leading AI-related trends by implementing machine learning across various fields including loan assessment, fraud prevention, and customer service. According to global market research firm IDC, the financial industry spent 1.5 billion dollars (approximately 1.7 trillion won) on cognitive and artificial intelligence systems in 2016 alone, making the largest investments in the AI sector alongside the retail industry.

However, behind high expectations for artificial intelligence and rapid adoption, several challenges have emerged due to lack of realistic implementation approaches and enterprise-wide objectives, resulting in systems being limited to specific domains or delayed progress. In response, SAS held this seminar to present implementable AI technologies, business application methods, and success cases that financial companies are considering.



The event presented methods for efficiently improving business through machine learning platforms. The seminar covered ▲misconceptions and truths about artificial intelligence and machine learning ▲enterprise machine learning analysis environments and application fields ▲platforms for enterprise machine learning ▲artificial intelligence implementation cases from leading global financial companies. Additionally, various successful data analytics cases utilizing SAS solutions were shared, including credit rating and fraudulent data utilization in e-commerce enterprises, customer social media data utilization in banks, and machine learning-based analytical models incorporating auto-tuning capabilities.

SAS Viya, the enterprise machine learning-based analytics platform introduced at the event, is a cloud-based open platform that supports various levels of analytical technology for machine learning. Business analysts, data scientists, and software developers can utilize the SAS Viya platform to derive insights from big data and create analytical assets to solve business challenges. SAS Viya supports common APIs and various programming languages, implementing interactive exploration and reporting, statistics, data mining, machine learning, streaming data analytics, forecasting, optimization, and econometrics.

SAS was recently selected as a 'Leader' in the 'Predictive Analytics and Machine Learning Solutions' category in Forrester Research's Q1 2017 report. Additionally, it was selected as the 'only Leader' in the 'Enterprise Insight Platform Suites' category in Forrester's Q4 2016 report, receiving praise for SAS Viya's provision of modern and simplified architecture.

Lee Jin-kwon, Senior Executive of SAS Korea, stated: "As financial services utilizing artificial intelligence and machine learning continue to expand, financial institutions must build an enterprise machine learning platform applicable across the entire organization rather than one limited to specific domains to successfully apply these technologies to business. SAS will support financial companies in achieving service innovation through data analysis in the age of artificial intelligence by providing methods to apply machine learning algorithms to existing analytical systems and analytical models suitable for financial business."