Intro to Adenovo

Adenovo is a web-based risk management platform that helps lenders monitor their vehicular assets with tracking sensors and predicts delinquencies and defaults with machine learning analysis based on driving patterns data of borrowers.

Adenovo is a DCBP subsidiary that handles auto financing. As part of my role at DCBP, I occasionally assisted Adenovo with UX and UI. This is an unfinished project that I thought was worth sharing as it pertains to DCBP.

To comply with my non-disclosure agreement, I have omitted and obfuscated confidential information in this case study. The information in this case study is my own and does not necessarily reflect the views of Adenovo.


Here is the only screenshot for this project. Click on the thumbnail to view it in a separate window.


The Chinese car market is gradually shifting from cash to credit, and Adenovo saw an opportunity to help manage risk and provide competitive interest rates for retail investors.

The problem is retail investors typically hold smaller portfolios, they are less likely to tolerate risk, which makes them more susceptible to misinformation and particularly stories about assets disappearing after default.

Even with all the sophisticated hardware solutions, retail investors were still unable to trust the system. The general consensus wasn't convinced and refused to join, despite the tempting earnings potential.

How might we give retail investors the confidence they need to trust new innovations with their savings?


Introducing the Adenovo Web Control Panel, a risk management tool that provides real-time tracking, analysis and prediction of vehicles based on the data of a borrower's driving patterns.

An interesting insight we uncovered was investors weren't trusting the technology because it was happening behind the scenes. Some investors believed they understood the concept, but were unable to fathom the idea that we could predict future vehicle locations, or or detect potential delinquencies.

It quickly became apparent that seeing how the technology works with their portfolio is the key. Seeing that every detail of their investment is monitored and continually scrutinized by a more advanced system than they ever could have imagined puts their minds at ease.

Real-time tracking of where vehicles are may be commonplace, but predicting where they will be with predictive driving patterns shows them that we are one step ahead. This guaranteed that when the time came for repossession, the assets would not disappear.

The option to request repossession is also added for extra peace of mind, so investors can feel more in control.

Although there is still much work to be done, we’re confident that showing investors the future is the way to empower them with the confidence to invest.

It is an unfinished project, but I hope it sheds light on the type of problems I worked on adjacent to DCBP.


This web control panel was still in development when I left the company. However, this was part of DCBP, for which we raised one of the largest Series A funding rounds in Taipei from Alibaba Entrepreneurs Fund, a subsidiary of Alibaba Group.


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