See the original story in Japanese.

Mitsubishi UFJ Financial Group (MUFG), a bank holding company with its core commercial banking subsidiary The Bank of Tokyo-Mitsubishi UFJ, last month held the Demo Day for MUFG Digital Accelerator 3rd batch in Tokyo.

Six teams that passed the selection had participated in the program and been working on improvements in order to brush up for their services, upon receiving support from mentors over a four-month period starting April of 2018 based on the co-working space The Garage in Nihonbashi-Kabutocho, Tokyo.

In the Demo Day, the teams’ four-month results were showcased to MUFG Group staffers, Venture Capital and media for the first time, to be examined based on four evaluation items: degree of innovation, user benefit, business potential and synergy with MUFG. The highly evaluated teams were given support grants and supplemental awards.

The judges for the Demo Day were as follows:

• Hironori Kamezawa (Chief Digital Transformation Officer, MUFG)
• Souichi Kariyazono (Managing Partner, Globis Capital Partners)
• Muneki Handa (CEO, Mitsubishi UFJ Capital)
• Yoshiaki Murakami (Executive Research Director, Mitsubishi Research Institute)

In addition, all six teams were given PR Times award (free use right of the press release distribution service PR Times for one years) as a supplemental prize.

See also:

• Mitsubishi UFJ showcases five prominent startups from its first FinTech accelerator batch

Top-award winner / AWS Award winner: Lendy by Credit Engine

• Mentor: Yasuhiro Yoshizawa (Inclusion Japan), Kotaro Sasamoto (Dentsu Ventures)
• Grand Prix supplemental prize: Business support grant 2 million yen
• AWS Award supplemental prize: Amazon Echo

Credit Engine provides a small-lot loan service Lendy as short-term emergency funds or operation funds targeting SMEs (small and medium-sized enterprises) / sole proprietors. Through cooperation with external web services and utilization of machine learning, its own risk evaluation system and quick application receiving / credit screening became available, so that the firm focuses on needs for funding which cannot be covered by conventional banks and financial organizations.

Credit Engine also developed a platform allowing external financial organizations to provide online lending service. This platform is specialized for online lending and enables bank users to reduce a burden of operation work in various introduction patterns according to their existing financing works flexibly.

Credit Engine revealed that it conducts PoC (proof of concept) at the MUFG-affiliated money lending company Acom and is expected to acquire new customers. Credit Engines will cooperate with MUFG Bank, and it is the first client of the platform.

See also:

• Japan’s Credit Engine closes $970K seed round for data-driven small business loans

Runner-up: MDR

• Mentor: Kengo Ito (D4V), Akira Kurabayashi (Draper Nexus)
• Supplemental prize: business support grant 500,000 yen

Quantum computers to perform high level computation is classified roughly into special-purpose machine and general-purpose machine. MDR exhibits a Python-based SDK (software development kit) supporting special-purpose machine free of charge, allowing anyone to experience quantum computing easily.  Through the participation in this acceleration program, the MDR team commented that it became possible to assess the influence on operations of banks / investment banks / investment trusts and to determine the area in present operations that quantum computing can or cannot be introduced.

In addition, MDR developed an OS for special-purpose quantum computer that allows easy development of quantum computing app without specialized knowledge. To deal with problems that cannot be solved by special-purpose quantum computer, MDR concluded an agreement with MUFG Bank on joint development of general-purpose computer. The firm plans to develop OS for general-purpose computer and aims to establish an environment where special-purpose / general-purpose quantum computing can be easily introduced into every operation of the financial industry.

Runner-up: Remitis by Restar

• Mentor: Shinji Asada (Salesforce Ventures) and Jun Nakajima (Archetype)
• Supplemental prize: business support grant 500,000 yen

The real estate startup Restar develops information search / analysis platform Remetis targeting enterprises dealing with real estate investment. The market size of real estate fund is huge in Japan and the total amount of managed asset is estimated to be 33 trillion yen (about $290 billion), but the firm pointed out that the available information to manage real estate efficiently is insufficient. For example, to acquire essential information to manage a certain real estate properly such as surrounding conditions of room availabilities or market prices of rent, gathering online data from more than 100 websites and even from paper-based data is a must.

With Remetis, users can acquire such information in one-stop and upload rent income / expense data automatically. It also acquires development situation data of competitors and creates summary chart or report automatically. In cooperation with MUFG Bank, Restar verified whether Remetis can automate asset evaluation / rating works for the bank’s loan customers.

Audience Award / Microsoft Azure Award / DEJIMA Award winner: Orphe Track by No New Folk Studio

• Mentor: Joh Konno (Globis Capital Partners), Kotaro Sasamoto (Dentsu Ventures)
• Microsoft Azure supplemental prize: use right of Microsoft Visual Studio Enterprise for one year
• DEJIMA Award supplemental prizes: member user right of DEJIMA, event-holding right, novelty T-shirts

No New Folk Studio develops the smart shoes Orphe mounted with LED light and motion sensor. It was an epochal decision that the firm known for an IoT (Internet of Things) startup or a hardware startup aims to collaborate with the financial organization.

The firm develops the smart shoes Orphe Track that a small-sized device can be inserted into its insole, enabling foot data collection linking with a mobile app. Focusing on the fact that not a few runners injure their knees while running, the firm realized an unique analysis method of runners’ landing by using its own algorithm based on running data acquired from the shoes, without requiring any expensive sensors unlike conventional methods.

CEO Kikukawa was inspired by the data published from the Japanese Ministry of Land, Infrastructure and Transport that a step a day reduces medical cost by 0.065 – 0.072 yen (about 0.06 cent). He applied for this accelerator program aiming to construct an ecosystem where users can have benefits through personal foot data collection. The firm also developed a platform in which coins are accumulated by running, tying up with the blockchain startup Zerobillbank and others.

See also:

• Progress update on Tokyo hardware startup’s Orphe LED smart-shoes

AndGo

• Mentor: Noriaki Sakamoto (The University of Tokyo Edge Capital), Yasuhiro Yoshizawa (Inclusion Japan)

AndGo takes on research and development of technologies related to encryption, blockchain and hardware wallet and has been developing a cold wallet in which cryptocurrency can be saved.

Generally, the security of user-owned cryptocurrency can be maintained by saving it in cold wallet without depositing it in an exchange, but there are still some issues in utility such as users having to memorize a lot of secret words.

AndGo realizes restoring core for both utility and safe use, cryptocurrency transfer method with QR code and multi-component authentication by a combination of smartphone and cold wallet. The firm plans to start sales of the cold wallet earlier next year. After the pitch, the firm discussed technical issues with the staffers of Kabu.com and Paygent affiliated by MUFG.

Signal by Factbase

• Mentor: Kenichiro Hara (DCM Ventures)

Factbase develops the information portal focusing on cryptocurrency named Signal with two key functions; Signal Board is a market forecast function with web-based dashboard and Signal Alert notifies users by LINE when an event that may have a significant impact on the cryptocurrency market occurs.

In contrast to the stock and exchange market based on legal tender, the cryptocurrency market is much influenced by information disseminated online. By understanding contexts and by arranging miscellaneous information using Big Data and AI (artificial intelligence), Signal realizes a system to provide information correctly to users.

The firm plans to distribute its first premium content that exhibits BTC FX (Bitcoin foreign exchange) trading techniques with actual examples, and users can subscribe to it for 10,000 yen since July 30th.

See also:

• Japan’s Factbase unveils cryptocurrency market forecast platform at Blockchain Expo

Translated by Taijiro Takeda
Edited by “Tex” Pomeroy

See the original story in Japanese.

Bank of Tokyo-Mitsubishi UFJ held a Demo Day for MUFG FinTech accelerator in Tokyo early this month. Though it has previously hosted a FinTech Challenge or a hackathon program in relation to the startup community, this is the bank’s first attempt at running an accelerator program.

Among the participants gathered from the end of 2016 through January of 2017, five teams took part in the program after clearing the selection process. The teams had been based at a working space named Garage for four months from this April. Operated by MUFG FinTech accelerator and located inside Tokyo Bankers Association Building alongside the FINOLAB FinTech hub, their Garage sojourn was spent making product improvements or brushing up services while receiving instructions from mentors.

During this Demo Day, the results of four months’ efforts were unveiled to persons in charge at MUFG group companies, venture capitalists and the media. Teams evaluated highly by the jurors     received a business assistance bonus or other goods as supplemental prizes.

Jurors at the Demo Day were:

• Masaru Murai, Supreme Advisor, TX Entrepreneurs
• Takane Hori, Partner, Mori Hamada & Matsumoto
• Hironori Kamezawa, Managing Executive Officer, Mitsubishi UFJ Financial Group
• Eiji Sumi, Executive Director, Mitsubishi UFJ Research & Consulting
• Muneki Handa, President and Representative Director, Mitsubishi UFJ Capital

Additionally, the five participating startups were awarded the PR Times prize (complimentary use of press release distribution service PR Times gratis for a fixed period, from August of 2016 to July of 2017).

Top Prize winner: Xenodata Lab.

• Mentoring by Minoru Imano, Globis Capital Partners
• Supplemental prize: 2 million yen (about $19,700) as business assistance bonus

Among 3,600 listed companies in Japan, only 500 companies account for 14% of the total stocks have their financial analysis reports issued by securities companies for use by individual investors as investment decision reference material. Most mid- / small-scale companies with stocks targeted mainly by individual investors do not issue financial analysis reports, so investors must collect statements of account, timely disclosure documents or financial results documents, then analyze those documents by themselves.

Xeno Flash developed by Xenodata converts information on documents related to financial reports into table data by XBRL (eXtensible Business Reporting Language) analysis, PDF table analysis and PDF chart analysis. Specifying important points from table data with its own original algorithm, it extracts background sentences from the enormous text data behind the specified number data by natural language processing. The total process from collecting documents to analyzing information will be completed within one minute per stock.

Its value proposition is that users receive information about every company quickly after a financial results announcement, when only important parts are proposed, and offered excellence in viewing information using infographics. The team plans to launch service at Kabu.com Securities within 2016. In the future, it will explore possibilities of information provision for individual investors via retail-type brokerage firms as B2B2C (business-to-business-to-customer), information distribution to new media, service expansion to cover overseas stocks, or service development to wholesales-type brokerage firms having financial analysts as B2B (business-to-business).

Runner-up: Alpaca DB

• Mentoring by Jun Nakajima, Archetype
• Supplemental Prize: 1 million yen (about $9,800) as business assistance bonus

Alpaca, which had developed a trading platform Capitalico in the past, developed anew Alpaca Scan during the accelerator period. This tool analyzes relevance between stock price fluctuation and various data in real-time through continuous monitoring of 7,000 stocks listed on US exchanges and by using AI (artificial intelligence) technology focused on market data. Based on past price fluctuation data or news, it helps users understand which stock and how much of this to own, how much the stock price is likely to rise in the future, or when to trade.
Simultaneously, the firm developed its own database named MarketStore as a back-end infrastructure for Capitalico or Alpaca Scan focused on financial time-series data. It is more cost effective compared with Oracle or Kx; in addition, the firm also succeeded in reducing the amount of RAM required as the database works with just a percentage of the resource. The time taken for algorithm analysis on Capitalico was dramatically shortened to about 10 seconds, although it had taken 30 minutes as of this March. On the platform, 7,000 types of ‘model’ have been created so far.

Henceforth, the firm plans to launch a service to support foreign currency reserve-building at optimal timing, based on MarketStore or Alpaca AI Engines for the Japanese internet bank Jibun Bank. This bank was established upon joint capital investment by Bank of Tokyo-Mitsubishi UFJ and the telecom carrier KDDI. Also, the firm will develop jointly a trading tool utilizing AI for Kabu.com Securities.

See also:

• Capitalico, forex algo-trading platform, wins FinTech startups gathered at FIBC in Tokyo
• Japan’s deep learning startup Alpaca raises $1M to launch AI-based forex trading platform
• Japan’s Alpaca launches Labellio, image recognition deep learning AI

AWS Award winner: Smart Idea

• Mentoring by Akira Kurabayashi, Draper Nexus Venture Partners
• Supplemental Prize: Amazon Fire Tablet and other Amazon goods not for sale

Smart Idea had already developed an account book app named Quick Money Recorder which ‘can be input only in 2 seconds,’ and the app has been downloaded 3.5 million times since its launch back in August of 2012. Among smartphone users living in Japan, 10% of the women in their 20’s to 30’s are Quick Money Recorder users, according to the team. For what kind of services targeting its own wider range of woman users does the team propose to cooperate with financial organizations?

In retail-type financial business, demands for fund occur in response to life events of customers, so that every financial organization expects to approach the presumed users at the time of their life events, but that is not easy due to lack of information or methods of approach. On the other hand, some surveys revealed that women in their 20’s and 30’s, mainly targeted by Smart Idea, have worries such as ‘cannot save up money’ or ‘have no idea about money, have nobody to ask.’

So, Smart Idea suggests a concept called ‘Fintainment’ which combines Fintech and Entertainment, and developed two apps: Okane Navi and a chat bot app. Okane Navi is an app adopting quiz factors related to financial services into a love simulation game in which 70% of women in 20’s and 50% of women in 30’s are absorbed in Japan. Users play a quiz game to obtain rewards, but they are not allowed to continue on without watching a movie for every five questions. The chat bot app allows users to receive proposals about ideal financial services by answering questions generated by AI.

Smart Idea plans to hold a life planning seminar which targets women in 20’s and 30’s together with Mitsubishi UFJ Trust and Banking. By leading Okane-reco users to Okane Navi or the chat bot app, the firm aims to increase the number of Okane-reco users to 3.5 million and to grow the entire service to a 10 million user-scale.

See also:

• Japan’s Quick Money Recorder, personal budgeting app, exceeds 3M downloads worldwide

Zerobillbank

• Mentoring by Kengo Ito, Genuine Startups

Zerobillbank, started last year in Israel and financially supported by Samurai Incubate, is developing ZerobillCore which enables the issuance of original virtual coins based on the blockchain, and an app Z-Wallet which enables receipt of the issued coins based on position, time and information acquired from sensors.

In the pitch, the Zerobillbank team demonstrated how to issue and provide virtual coins called ‘Marunouchi Coin’ as an example (the Demo Day was held in Marunouchi, Tokyo) to users holding the Z-Wallet in the Marunouchi area. It allows for issuance of coins to users within a fixed distance from a certain base point using the Geo-fence idea. Since Z-Wallet works as a sensor / beacon as well, various settings are available such as providing coins to users who have visited a certain place or who walked a certain number of steps.

As for assumed cooperation cases, the team suggested issuing ‘life insurance coins’ according to the users’ number of steps or exercise amount, by tying up with life insurance companies in order to develop health encouraging-type insurance products, or issuing ‘automobile insurance coins’ according to the insured cars’ track record or linking with telematics data by tying up with non-life insurance companies.

Moving forward, test operations of the reward system at Bank of Tokyo-Mitsubishi UFJ and implementation of a point system for third-party websites at Kabu.com Securities are scheduled, and with Mitsubishi UFJ NICOS, Zerobillbank looks to find ways of utilization for reward development with its cooperative partner companies.

Knowledge Communication

• Mentoring by Yasuhiro Yoshizawa, Inclusion Japan

Knowledge Communication had launched a cloud service Nare-com AI supporting easy use of AI or deep learning this March. Nare-com AI shortened the time needed for algorithm selection for machine learning to 2 weeks, equivalent to one-fourth that for conventional technologies, and also realized automation of the selection process, which formerly required data scientists, using the roundrobin technique for both algorithm and parameters. The team has begun considering means of utilizing Nare-com AI for banking services during the accelerator, and set a goal to develop a service enabling use of data mining and the modeling process for less than 500,000 yen (about $5,000) / within a day, while such kinds of service generally require tens of millions of yen / more than two months minimum.

Knowledge Communication had modeled a judgment process based on 20,000 SME (small and medium-sized enterprise) financial statements and information about judgment by persons in charge of financing at Bank of Tokyo-Mitsubishi UFJ regarding whether each SME is appropriate as an investment target or not. Inputting SME financial statements for this year into the model made from last year’s data as trial, the team succeeded in creating reference information on some 4,000 companies for investment decision within 30 minutes. It is valuable to semi-automate a part of the judgment process under conditions actually used until last year, although conventionally persons in charge of financing had to judge based on data of target companies such as capital adequacy ratio, plus his / her experience and intuition.

In the future, the team expects the service to be used for stress test of financial works at banks, sampling of potential customers of new services having the same characteristics asw other service users or list sampling of candidate borrower companies that are likely to have financial demands.

---

It is unclear with what kind of KPI (key performance indicator) MUFG FinTech accelerator is managed, but it is easily assumed that the number of suggested cooperation projects with MUFG’s group companies is one of the most important evaluation criteria. Some of the cooperation projects would generate revenue sharing or sales immediately after graduation from the program. That may be one of the attractions for startups to participate in the operational company-type accelerator.

Although initially future plans of MUFG FinTech accelerator had been undecided because it was the first attempt for Bank of Tokyo-Mitsubishi UFJ, at the closing ceremony the manager of the accelerator Eiichi Kashiwagi (General Manager of Global Innovation Division, Bank of Tokyo-Mitsubishi UFJ) expressed his willingness to start accepting application for the 2nd batch from this autumn or within the year, upon considering the results of the 1st batch.

See also:

• Agribuddy, financial app for rural farmers in Cambodia, wins Nikkei FinTech competition
• How up-and-coming Japanese FinTech/cloud startups are aiming at global market

Translated by Taijiro Takeda
Edited by “Tex” Pomeroy