AI-Supercharged Bank Statement Analysis

Algorithmic disclosure for

family lawyers

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Proposal Sheet

What is financial disclosure?

Divorce proceedings often require complex financial negotiations, and family lawyers shoulder the responsibility of ensuring transparency and fairness.


The (Family Law) Rules (2021) in Australia require both parties to a divorce to disclose their bank statements from the past 12 months, which is used by the court to assess the financial situation of each party accurately.


A family lawyer’s role in this process is to:

  • capture the pool of assets available to be divided up
  • understand each parties’ contributions to the marriage
  • pose specific queries to the other party if they have suspicion the other party may be embezzling assets


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Why is financial disclosure important?


Negotiation Leverage: Identifying unresponsible purchases and embezzlement of funds helps lawyers advocate for fair and equitable distribution of assets, protecting their clients' financial interests.


Child Custody Considerations: Financial behavior on bank statements can impact child custody & financial support decisions, as they provide insights into a party's financial stability and responsibility.


Supporting Legal Strategy: The insights derived from bank statement analysis inform legal strategies, allowing lawyers to build stronger cases and increase the likelihood of achieving favorable court outcomes.


But it’s inefficient...

Time Is Money 20

5 hours

per Family Lawyer, spent on disclosure

Law Firm

$100K

Yearly cost to a mid-size firm

$135M

Cost to Australian Market

Problem Statement

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Family lawyers face the arduous and error-prone task of manually collating and analyzing bank statements.


This time-consuming process is currently solved by manually requesting documents from clients and manually searching through statements for suspicious transactions


The demand for a more accurate, efficient and cost-effective solution can be met by digital transformation.


We interviewed 18 family lawyers

To validate our problem statement, we interviewed a range of family lawyers who all independently identified financial disclosure as a big pain point.

Hugely inefficient status quo

Family lawyers spend about 5 hours a week manually requesting documents, scrutinising statements, and inquiring about transactions.

2

RIsk of overlooking details

The level of scrutiny is variable, raising the risk of overlooking crucial details in certain cases.

3

Family lawyers express a clear desire for a solution that can automate the disclosure process.

Solution

Develop an integrated platform tailored for family lawyers that allows clients to seamlessly upload their bank statements. The platform utilises AI-technology & algorithmic analysis to automatically flag standout transactions, and provides family lawyers with a streamlined interface for efficient inquiry and analysis of these transactions.



Low-Fidelity Prototyping

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Matter Creation

Analysis Module

High Fidelity

Prototyping

Unbezzle

Our talented developers built our fully-scalable software solution using Python, OpenAI, Sveltekit, Flask & MongoDB and a Sydney-based server. We own full rights to our software and proprietary algorithms.

Here’s how it all works...

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Ai
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Easily onboard clients with Collaborative Sharing

A family lawyer may easily grant a client access to the platform, allowing them to upload bank statements, with AI guidance.

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Ai-POWered Transaction Categorisation

Our AI-integration allows our software to extract categorical data from the statement including the merchant, location & category of transaction.

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Quantitative flagging algorithm

Using the AI-extrapolated information, our quantitative algorithm is able to search for standout ‘signals’ to flag. This may include a recurring bank transfer to an unknown account, or suspected drug purchases.

1. Client

Interface

(Both sides )

Questioning flagged transactions

4. Solicitor interface

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Uploads

statements

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Flagged

transactions

2. AI Categorisation

3. Quantitative

Flagging Algorithm

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Passes on array

of data-points

Front-End

Stack Summary

Back-end

Product Demo

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Innovation, Impact & Value to Tech in Law


Our platform paves the way for


Machine Learning: Using historical data and user feedback, the machine learning model is continuously trained and refined to improve accuracy in detecting standout transactions, adapting to new and evolving methods of suspicious financial activity.


Scalability: The program’s ability to handle large volumes of bank statement enables lawyers to spend more time on higher-level tasks or take on more clients, boosting the productivity, accessibility and affordability of legal services


Improved Decision-Making: The program can provide insights and recommendations based on its analysis, helping lawyers make more informed decisions when negotiating or litigating settlements to achieve a more fair and equitable outcome for their client


The Management Team for the job

The team has the background, proven track record and vision to succeed

Matthew Duff

Founder, MD

Phil Virgona

Head of Quantitative Algorithms

Diane NguyeN

Head of customers

VICTOR PHAM

Head of Technology