• AI與資料科學 打造未來的金融應用

    AlphaLoan專注研發智能化之貸款比較/申請/KYC及信用風控,重新定義借貸活動

  • Applying for A Loan Is Not Easy

    AlphaLoan的解決方案能將貸款整體流程從5天縮短至10分鐘,並提升銀行業績40%

    1

    貸款比較

    貸款資訊複雜,造成使用者不易找到適合的銀行申請,銀行也無法有效找到目標客群

    2

    申請

    申請程序人工,對使用者來說既耗時又麻煩。銀行後續分析評分也會遭遇很大的問題

    3

    身分認證及KYC

    身分認證程序繁複,文件辨識耗費人工。對使用者來說每次申請都有極大阻力

    4

    信用評分

    金融評分雖穩健,但卻逐漸無法適用於年輕客群。獲取更多資料源及分析應用有極高的技術門檻

  • AlphaLoan

    用AI預測模型,根據個人化的資料,從其他上百萬筆數據預測出最適合自己的信貸方案。「實貸比較網」為台灣最大信貸通路入口,並持續整合銀行API及自主開發之技術。

    AlphaApply

    免除繁複性的申請流程及文件準備,提供使用者秒完成申請金融商品的體驗

    AlphaKYC

    讓使用者一次性證明身分/意圖及相關文件,同時協助機構夥伴線上快速認證使用者

    AlphaCredit

    智能化風控,提供完整包含金融數據及其他大數據之信用評分。能在10分鐘之內完成自動化評分。同時介接機構進行消費分期,讓使用者使用一個信用額度,處處通行。

  • Media Press

    AlphaLoan打造下一代信用風險管理科技

    經濟日報

    凱基銀結盟AlphaLoan信貸網 開放數位信貸程式

    蘋果日報

    AlphaLoan實貸比較網運用AI 讓用戶找到最適合的信貸申請銀行

    DigiTimes

    [Meet創業之星] 擔心貸款被拒?AlphaLoan要做你和銀行之間的信任溝通

    數位時代

  • We're Hiring

    We're looking for people who love DATA as much as we do.

    Engineering - Full Stack Engineer

    • Improving our backend infrastructure and database schema to help users better utilize our applications
    • Writing additional ETLs to gather, structure, and normalize data from new and existing sources for our database.
    • Creating additional internal APIs to expose this data to front end applications.

    Product Team - Senior Credit Risk Manager

    • Owning and leading the development of Credit Risk Strategy and Policy.

    • Overseeing and monitoring of the development of Credit Scorecards (You can be hands on with this should you want to do so).
    • Developing effective Credit Risk MI.
    • Regular Stakeholder Management.
    • Contributing to Group Strategy and Forecasting in respect of Credit Risk and Impairments.

    Data Team - Data Scientist

    • Selecting features, building and optimizing classifiers using machine learning techniques
    • Data mining using state-of-the-art methods
    • Extending company’s data with third party sources of information when needed
    • Enhancing data collection procedures to include information that is relevant for building analytic systems
    • Processing, cleansing, and verifying the integrity of data used for analysis
    • Doing ad-hoc analysis and presenting results in a clear manner
    • Creating automated anomaly detection systems and constant tracking of its performance