Innovation of Customer Experience Value - Data Strategy of Shinsei Bank Group February, 2018 Hiroyuki Torigoe President & CEO Shinsei Financial Co., Ltd.
Creation of Customer Experience Value and Growth with Lake ALSA Lake ALSA will keep pursuing the maximization of customer experiences and their lifetime value (LTV). Lake ALSA Utilization of Digital Technology Operation Credit Rating/ Marketing ・ IVR Collection ・１ to １ Marketing ・ RPA ｘ OCR ｘ AI ・ AI Score ・ Smart-phone LTV (Lifetime Value ・ API Operator ・ Digitalization of transaction Support accumulated ・ UX/UI human expertise ・ ChatBot/API YUI Platform ･ Introduction of ・ Mass Marketing ・ Calling centers Web+Automated Stores credit scores (TV) ・ E-mails/SMS (ACM) ・ Manual credit ・ ACM ratings ・ Web Advertise- ment ・ Convenience Store ATMs ） TV CM+Branches with ・ Manual Credit ・ Branches with ・ TV CM Ratings clerks Clerks 写真を探して張り付ける ・ ATM Essential Depth of Customer Experience 2
“ YUI Platform” to Support Shinsei Bank Group’s A Data Strategy YUI Platform is an analytics platform created by combining an Artificial Intelligence (AI) and the Group-wide Customer Database. YUI Platform is capable of expecting the needs and credit ratings of each customer through AI, allowing us to keep improving our marketing and credit risk assessment capabilities to a higher level. The Group aims to continue upgrading the Platform so that we can always fulfill the true needs of the customers, targeting also the customers outside of the Group in the future. YUI Consumer Finance Customers Platform Shinsei Bank Shinsei Bank Corporate Customers Intricate Credit Individual Transaction- Ratings AI/Analytics Credit based APLUS Platform Showa Leasing Rating Lending Corporate Appropriate Credit Product Recommen- Scores Marketing dation Group Appropriate Scores Customer Shinsei Financial Product APLUS New Database Recommend- Fraudulent Lendings （ Identification, ation to New Scores Anonymization ） … Customers … Data Varieties of Affiliates with Total: Affiliates with Varieties of Inquiries Lending about 10 million Individual Corporate Transaction Method customers Methods Customers Customers AI keeps learning though continuous utilization and acquisition of the new data 3
Innovate Business with Digital Technology and Acquire the New Customers Shinsei Financial will gradually upgrade the credit rating / digital marketing method with AI learning ability, acquiring the young generation with high digital literacy while retaining current customers of the Lake brand. Shinsei Financial, simultaneously, will optimize its operational cost with digital technology, namely, using OCR and RPA. Additional acquisition of C Potential potentially qualified (II) Sophistication in Credit customers Market D (Upgraded AI Scores) Realize cost + Rating/Collection optimization by low- cost operation using Essential digital technology deepening of customer experience Lake Brand with digitally savvy customers (UX/UI) (I) Sophistication in Digital Marketing B 4
Branding and Marketing Concept of Lake ALSA B Shinsei Financial aims to create a brand value which can differentiate itself from competitors, by taking over the sense of safety and convenience of a big brand, Lake, and with advanced technology and customer support. The Value of Lake The New Value to be Created + Sense of safety Agility • • Lake as a big consumer finance On-time service with high-end AI technology brand Linked • Convenience Build a new customer base utilizing the integrated database • (YUI Platform) No ATM handling charge, and no interest for the first 180 days Security • Always behind the customers According to our vision* • *Build a proud “financial service provider for ordinary citizens,” sincerely engaging with customers and offering values needed by society. Enforcement of Multi-Function to Create the Brand Value Card-less withdrawal/repayment service with Seven Bank ATMs. Better response with Web-API, optimization of web members’ site and forms (AB Test, PDCA cycles) ChatBot services with Smart phones/tablets 24h wire transferring services (from Fall, 2018 ） 5
Upgrading the Credit Rating and Collection C-1 Procedures with AI Scorings Expecting better performance through the application of sophisticated hybrid of AI and logit scores to the various financial products of the Group. Expecting higher accuracy of prediction by combining the big data and the AI’s deep learning technology. Expecting better credit scoring performance by utilizing AI analysis of the credit position in fund collection area. Hybrid Credit Ratings Utilizing AI and Logit AI Scoring the Group is Working On AI Scoring Integrate and utilize not only credit and attribute information, High Data but also all structured, “Approve/increase” when Higher non-structured and open data AI finds blue-chip customers, Credit within the Group for scoring regardless of low logit scores Scoring Performance • Maximize the impact of the big data by hiring the high-end Medium “Decline/decrease” when Algorithm mechanical learning models AI finds inappropriate such as deep learning and customers, regardless ensemble learning of the high logit scores Lower Credit • Utilize AI for the credit ratings Low Scoring as well as for the fund collection Area of Performance area, upon evaluation of the Application credit position(as they are two Traditional Logit Scoring sides of the same coin) Low Medium High 6
Digitalization of Human Expertise in Fraudulent Control C-2 Share the expertise of Shinsei Personal Loan’s skilled staffs within the Group by replacing manual credit screening of fraudulent detection with AI. Digitalization of manual credit screening techniques in collection centers are carried out simultaneously. Current Status Future Application Application Toward the higher Scoring Scoring accuracy/credit rating System System support through AI’s learnings of the past manual credit ratings Extract Applications Subject Extract Applications Subject to Manual Credit Scoring to Manual Credit Scoring System System Manual Operations Extraction Tool Manual Credit Scoring Manual Credit Scoring AI Credit Ratings Operations by Operations of Information Experienced Experienced Staffs staffs Collection/ System Decisions of Checking Decisions of Tools Experienced Staffs Experienced Staffs Contract Decline Contract Decline 7
Phases of Robotization with D Robotics Process Automation (RPA) The Group is promoting its robotization by introducing RPA and OCR technologies mainly in back office operations in Shinsei Financial The Group almost completed their preparation processes to implement them in FY2018 We are expecting 50% reduction of workload in the selected 19 operations in FY2018, and will expand its application through modularization going forward. Phase 2-1 Phase 3 Phase 2-2 Design Each Operation/ New Process Introduction Start Utilizing Carry Out Product Selection PoC Consideration April 2018 October - November 2017 December 2017 – March 2018 Period Project Decision Making Check-point Effectivene Calculation Design Each Operation Concept Process of New Trial Support Detailed Designing of Operations （ List of New Operation, ss of Introduction Plan New Operation Flow Chart) Specify Tasks Reflect Share for sampling Characteristics Views The Operation Details of RPA PoC Get Estimates RPA Product Starting-up Program of RPA and Select Operation Tasks Starts Evaluation Comparison Check Tools Axis Set OCR OCR Product Preparation for Utilizing Phase/Adjustment of OCR Evaluation PoC /Selection Support Establishment of Rules for Consideration of Management Policy/ Robotics Management Tools Set Introduction System 8
Disclaimer • The preceding description of Shinsei’s Medium-Term Management Plan contains forward-looking statements regarding the intent, belief and current expectations of our management with respect to our financial condition and future results of operations. These statements reflect our current views with respect to future events that are subject to risks, uncertainties and assumptions. Should one or more of these risks or uncertainties materialize, or should underlying assumptions prove incorrect, our actual results may vary materially from those we currently anticipate. Potential risks include those described in our annual securities report filed with the Kanto Local Finance Bureau, and you are cautioned not to place undue reliance on forward-looking statements. • Unless otherwise noted, the financial data contained in these materials are presented under Japanese GAAP . The Company disclaims any obligation to update or to announce any revision to forward-looking statements to reflect future events or developments. Unless otherwise specified, all the financials are shown on a consolidated basis. • Information concerning financial institutions other than the Company and its subsidiaries are based on publicly available information. • These materials do not constitute an invitation or solicitation of an offer to subscribe for or purchase any securities and neither this document nor anything contained herein shall form the basis for any contract or commitment whatsoever. 9
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