Analysis Featured

A new approach for a credit bureau for Small and Medium Entreprises

Though there are many databases like Dun & Bradstreet and Experian to check the credit history of a business, they are neither real-time nor able to offer any future predictions.

A young Sunnyvale-based fintech start-up; CRiskCo, is looking to solve the SME credit profile problem by offering a free credit-management platform to SMEs and leveraging their so-acquired data into analytics. With scale, CRiskCo can create a credit-risk database to help build SME credit rating models which will also allow for near real time credit risk monitoring.

Company background

The company was founded by Erez Saf, a veteran of SAP and CIO of eLoan (a p2p lender in Israel). He understands the pain point of businesses as he himself had to suffer delayed payments from a client. A one year wait to get his payment frustrated him and made him realize the issues faced in vetting business clients. The team has Amit Eisenthal as CTO and Tomer Levy as a product manager. Peter Hungler is the senior VP and was previously in Credit Suisse and Deutsche Bank.

The company has raised $350,000 in seed funding from PlugandPlay accelerator and Andrei Tkachuk, CFO of DemandForce( a company purchased by Intuit for $424 mil).

PlugandPlay is famous for backing fintech pioneers like PayPal and LendingClub. The company is looking to tie up a further $2.5 mil in seed funding for future expansion.

A 2 step approach

CRiskCo has two products- Criskco Approve and Criskco Monitor. Approve is primarily to help SME’s evaluate their clients and determine whether they are creditworthy or not.

The Approve product is currently free for SMEs. It connects and integrates with QuickBooks, SAP, Xero, Intuit and the main accounting systems of the SME. Using the historical payment data, cohort comparison and proprietary algorithms Approve will then rate the financial behavior and profile of a given customer of the SME. Through this process, Approve can help the SME’s decision maker to extend payment terms or not to a given customer. Through this process, CRiskCo builds a knowledge database on SMEs.

Leveraging this database, CRiskCo then offers Monitor, a product for traditional SME lenders to help them analyze and approve SME borrowers and to track their credit worthiness in real time.

The start-up charges SME lenders an annual fee for licensing Monitor and an additional monthly fee depending on the number of active accounts. The typical licensing fee deal is $25,000 and monthly charges vary from $2 to $20 per account, depending upon volume.

Monitor provides services to lenders at 2 levels . Level 1, provided via API, is useful in the KYC process and helps the lender understand its borrower’s end customers.  Level 2 helps in predicting the credit worth over time of borrowers by analyzing the behavior of their end customers. Though companies like BlueVine and FundBox work on a similar premise, their focus is on providing an end-to-end platform for online lending, whereas CrRiskCo’s priority is to provide traditional lenders with a platform which would help them save money by avoiding potential delinquents.

How it works

The company applies its deep learning algorithm on the relationship between the SME and its customers. This is executed by integrating itself into the accounting system of the user.  The company profiles the relationship and compares the financial behavior of the relationship to the known defaulter behavior. The similarity of behavior has a direct relationship with risk i.e. more the similarity higher the risk and vice-a-versa. The company standardizes the data, to ensure no bias remains due to the accounting system employed by the customers. It takes into account 73 parameters like invoice information, payment delays, average delinquency, days outstanding etc.

If another vendor has the same customer, the algorithm will pick the transaction history to further refine its model. The company correctly considers itself as an artificial intelligence and a deep learning company. Machine learning for constant refinement of the model is a necessity for its improvement and relevance to users.

Quantifiable Results

In a case study published by the company, an SME user was able to decrease account overdue from 96% of receivables to only 9% in just a few months. The average delinquent days reduced from a whopping 102 days to 8 days only. Most importantly, the SME was able to reduce the absolute credit exposure from $5 mil to $3 mil, freeing up $2 mil in cash flows.

Traction

The products were launched in September 2015 and the company has 14 vendors connected to the system, with $4M in daily open invoices and a total of $170M invoices analyzed.

It has been able to achieve a high growth rate in such a short period of operations and is in a pilot stage with factoring companies and community banks.

The company is developing an in-house sales team to target traditional lenders. It is also looking to incorporate a freemium model for SME users, potentially opening up another lucrative revenue stream.

The future in SME credit bureaus

The industry saw a major deal when Dun and Bradstreet acquired D&B credibility for $320 mil; highlighting the lucrative nature of the market. The founder feels that traditional lenders are using credit assessment tools which are based on a “100-year-old paradigm of voluntary reporting.”

The company is looking to revolutionize the process by streaming live data to credit providers and SME users which will help them take credit decisions on a real-time basis. The company is also looking to remodel the entire credit model infrastructure with its deep learning algorithms.

Its platform technology will become more and more valuable as businesses keep joining it and indirectly keep feeding it data about themselves and their customers. Eventually, once a particular tipping point is reached, the platform will experience the advantages of network effect and it can grow to be the de facto choice for credit information for SMEs.

 

Author:

George Popescu
George Popescu

About the author

George Popescu

Serial entrepreneur.

George sold and exited his most successful company, Boston Technologies (BT) group, in 2014. BT was a technology, market maker, high-frequency trading and inter-broker broker-dealer in the FX Spot, precious metals and CFDs space company. George was the Founder and CEO and he boot-strapped from $0 to a $20+ million in revenue without any equity investment. BT has been #1 fastest growing company in Boston in 2011 according to the Boston Business Journal and the only company being in top 10 fastest in 2012-13 as it was #5 in 2012. BT has been on the Inc. 500/5000 list of fastest growing companies in the US for 4 years in a row ( #143, #373, #897 and #1270). After the company sale in July 2014 until February 2015 George was Head-of-Strategy for Currency Mountain ( www.currencymountain.com ), a USD 100 million+ holding company focused on retail and medium institutional currencies, precious metals, stocks, fixed income and commodities businesses.

• Over the last 10 years, George founded 10 companies in online lending, craft beer brewery, exotic sports car rental space, hedge funds, peer-reviewed scientific journal ( Journal of Cellular and Molecular medicine…) and more. George advised 30+ early stage start-ups in different fields. George was also a mentor at MIT’s Venture Mentoring Services and Techstar Fintech in NY.

• Previously George obtained 3 Master's Degrees: a Master's of Science from MIT working on 3D printing, a Master’s in Electrical Engineering and Computer Science from Supelec, France and a Master's in Nanosciences from Paris XI University. Previously he worked as a visiting scientist at MIT in Bio-engineering for 2 years. George had 3 undergrad majors: Maths, Physics and Chemistry. His scientific career led to about 10 publications and patents.

• On the business side, Boston Business Journal has named me in the top 40 under 40 in 2012 in recognition of his business achievements.

• George is originally from Romania and grew up in Paris, France.

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