Bizcred

Search for other companies
Score matrix UI
Landing page to prompt Intuit integration

1 min pitch

I used to be part of a small business, just like 28M other small businesses in the US. One problem I faced then, was not receiving Accounts Receivables. This is a robbery, and something must be done.

Therefore my team is proposing BizCred, a new way to measure business credibility and reputation between businesses.

For this weekend, we are pulling information from Intuit’s Quick Book APIs to generate the reputation score.

We extracted late payments, unpaid ARs, business age from intuit’s quick book as well as use Machine Learning to predict payment delays.

We are essentially providing a platform for small businesses to see each others financial reputation without intrusion and with privacy. Think, credit karma for small businesses, to think about how and whether they want to work together.

As you can see here, ABC florist has a reputation score of 80, it seems like she is someone I would want to work with.

We hope to make accounts receivable, receivable again.

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Inspiration

I used to be in a small business and Accounts Receivable debt has a huge chance of being defaulted and being paid extremely late. If I had known about certain company’s financial reputation, I might charge a deposit or even not work with them to start with. Hence, there is a need to understand and find out the economic risk of doing business with some companies, and a reputation score needs to be created.

What it does

Bizcred offers a business reputation score without intrusion and privacy. It allows businesses to choose their partners based on their financial reputation and accountability.

Bizcred calculates a business reputation score, in the lens of invoice repayment likelihood. Businesses will be able to see specific scores on specific scores on financial payment history, amount of defaults, and derogatory marks that a company might have on top of a aggregated score.

This creates an ecosystem of trust, and companies trying to get top level accreditation.

How we built it

We used Intuits Quick Book APIs to generate bookkeeping entries. From these entries, we fed these entries into our machine learning model to predict future late payment duration and generate the score using ensemble learning.

Challenges I ran into

Lack of time, wanted to add hyphenate and other APIS Quickbooks had some issues with python integration How to come out the right fills and weights to come out with an accurate model Had to understand accountancy terms and make sense of quickbook.

Accomplishments that I'm proud of

Small team of 3 Built a working prototype Hack through the night and had fun!

What I learned

I learned more about small business and Account Receivables Learnt about how to use quickbooks in depth (truly amazing) Accountants might be replaced soon by quickbooks.

What's next for Bizcred

Integrating with other software small businesses might use to generate more data points. Get more users to build up the eco-system Consider working with financial institutions to provide bridging loans due to the lag time of Accounts Receivable payment Auto-prompt and reminder system Future behavioral analytics