# Presentation: 063405

## A Trip to the Zoo

- Daniel Kern
- Risk Management
- Quality & Productivity
- Bank of America

## Knowledge model

- Knowledge = f(t)

## Knowledge block at time t

|  | Yes | No |
| --- | --- | --- |
| Yes | Know what we know | Paradox? |
| No | Know what we don’t know | Don’t know what we don’t know |

**Is it**
**known?**

**Can it be known?**

## Knowledge block at time t

|  | Yes | No |
| --- | --- | --- |
| Yes | Know what we know | What we think we know
Possible error,
mistake, etc. |
| No | Know what we don’t know | Don’t know what we don’t know |

**Is it**
**known?**

**Can it be known?**

## Knowledge block at time t

|  | Yes | No |
| --- | --- | --- |
| Yes | Know what we know | What we think we know
Possible error,
mistake, etc. |
| No | Know what we don’t know | Don’t know what we don’t know
Surprises,
Ah ha moments |

**Is it**
**known?**

**Can it be known?**

## What animals are we going to see?

**What animals are we going to see?**
**Where are the animals?**
**How many elephants are at the zoo?**
**Is it going to rain?**
**Am I going to be scared of the snakes?**

## Knowledge block before zoo

|  | Yes | No |
| --- | --- | --- |
| Yes | We’ll see elephants, lions, tigers... | Rain in the forecast. |
| No | Animal location?
Number of elephants? | Snake fear? |

**Is it**
**known?**

**Can it be known?**

## Knowledge block at the zoo

**Knowledge block *****at the***** zoo**

|  | Yes | No |
| --- | --- | --- |
| Yes | We’ll see elephants, lions, tigers... | Rain in the forecast. |
| No | Animal location?
Number of elephants? | Snake fear? |

**Is it**
**known?**

**Can it be known?**

## Knowledge block after zoo

|  | Yes | No |
| --- | --- | --- |
| Yes | We’ll see elephants, lions, tigers... 
Animal location
Number of elephants
No fear of snakes
Beautiful weather | Rain in the forecast. |
| No |  |  |

**Is it**
**known?**

**Can it be known?**

**How to apply in the****fight against financial crime?**

## What is financial crime?

**Money laundering**
**Criminal trying to hide the origin of funds by passing them through legitimate transactions**
**Examples**
**Avoid government reporting limits**
**Activity does not match customer**
**Fraud**
**Criminal trying to achieve financial gain through fraudulent activity**
**Examples**
**Deposit a worthless item, withdrawal real cash**
**Identity theft**

## Money laundering vs. fraud

| Money Laundering | Fraud |
| --- | --- |
| Occurs over time | Occurs in a “spike” |
| Difficult to know the “truth” | Usually easy to know the “truth” |
| Criminal wants to stay “under the radar” | Criminal “cuts and runs” |

## Fighting financial crime

|  | Yes | No |
| --- | --- | --- |
| Yes | Know what we know | What we think we know
Possible error,
mistake, etc. |
| No | Know what we don’t know | Don’t know what we don’t know
Surprises,
Ah ha moments |

**Is it**
**known?**

**Can it be known?**

## Why visualization?

**Challenges**
**Large data sets**
**Rare events in a dynamic landscape**
**Solutions (Wishlist)**
**View a large amount of data at once**
**Allow quick interpretation**
**“****Highlight” the interesting data points**

## What is next?

**Use knowledge to solve new problems**
**Use “the known” to lead to the discovery of “the unknown”**
**Visualization tools must be interactive**

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**!**

## Old saying

**Ignorance is bliss.**

## We are driving toward...

**Ignorance is *****momentary*****.**