# suspicious activity report (sar) drafting prototype

## problem

writing suspicious activity reports (sars) is manual and repetitive.

analysts copy transaction facts into narrative templates, which is time-consuming and error-prone.

## what this project does

this prototype uses python templates to generate first-draft sar narratives from synthetic transaction data.

it then evaluates the drafts for completeness (who/what/when/why) and readability.

all data is synthetic and reproducible, created with faker.

## project structure

- data/ → synthetic csv + text templates

- docs/ → example sar drafts, evaluation results, plots

- notebooks/ → main jupyter notebook with workflow

- requirements.txt → dependencies (minimal for v1)

## how to run

1. create a virtual environment and install dependencies:

  ```bash

  pip install -r requirements.txt

2. open the notebook:

jupyter notebook notebooks/sar_drafting_prototype.ipynb

3. run the cells to generate drafts, metrics, and plots.

results

dataset: 500 synthetic transactions

drafts: narratives generated from flagged alerts

evaluation: completeness checks + readability scores

visualization: histogram of readability distribution

next steps: adding spaCy for validation, rapidfuzz for novelty, and a variation layer for more natural drafts

disclaimer

this project uses only synthetic data.

it is for educational purposes only and is not a production compliance tool.

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