Neural network
The AI advisor
Learns the pattern in the cases and explains each recommendation afterwards by working out how much every answer counted.
What counted for one example investor
Meet an AI investment advisor that explains itself. Describe an investor and get a recommended mix with the reasoning behind it.
Researcher or reviewer? Start here instead
Age 38 · 18-year horizon · moderate risk tolerance
Recommended outcome
Growth
What drove this
Example investor 1 of 4
What the advisor does
Age, investment horizon, risk tolerance and a few facts about their finances. Made up is fine.
One of five investment mixes ranging from capital preservation to aggressive growth. When the case calls for it the advisor refers you to a human adviser instead.
Pick one of four explanation styles. Then decide whether you would trust what you were told.
Two advisors
Both learned from the same 400 cases reviewed by a panel of financial experts. One reasons like a network and the other like a checklist.
Neural network
Learns the pattern in the cases and explains each recommendation afterwards by working out how much every answer counted.
What counted for one example investor
Scorecard
A points table you can read in full. Every answer adds or removes points for each outcome and the highest total wins. No step is hidden.
Three rows of the real table: risk capacity
| Conservative | Balanced | Growth | |
|---|---|---|---|
| Low | -1.1 | -0.7 | -0.3 |
| Moderate | +0.6 | +0.9 | -0.5 |
| High | +0.4 | -0.2 | +0.8 |
Explanations
Pick any of them on the advisor page. Each is computed from the advisor's own numbers.
Which of your answers pushed the advice and by how much.
The smallest change to the situation that flips the advice.
The advisor's confidence with every other outcome shown beside it.
A conversation about the recommendation grounded in the same numbers.
Outcomes
Each bar shows how a mix splits the money across four kinds of asset.
Mix 1 of 5
Capital preservation first: mostly bonds and cash, a small equity sleeve.
Most of the money sits in bonds and cash, so the value moves little. Over long periods it may barely stay ahead of inflation, which is the price of that steadiness.
Why this matters
Nobody yet knows which kinds do which. That is the question this advisor was built to answer.
Investment apps increasingly recommend what to do with your money and the recommendation comes from a model. Following it helps when the model is right. Following it costs real money when the model is wrong. Most people cannot tell which is which from the recommendation alone.
Explanations are meant to close that gap. Yet an explanation can also make wrong advice sound convincing. Which kinds of explanation help people judge rather than simply persuade is still an open question.
The study
Read a case. See the recommendation with one kind of explanation. Say what you would do. Some recommendations are deliberately wrong and the debrief tells you which. The study is anonymous and takes about fifteen minutes with no account needed.