Gov-Funders

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  Gov-Funders Funding Application site prototype UI.

Problem

Coronavirus and subsequent social distancing rules have impacted service industries heavily.

EU member states have a range of financial instruments available to sustain technology and innovation, but the existing institutional structures are not geared for channeling financial support to restaurants, concerts, business events, art production, etc.

There is urgency. Profit margins in service, culture, and art sectors are very low, leaving businesses and the entrepreneurs with very little, or no buffers at all.

Financial and emotional investments in these "life's work" -businesses are huge. Now there is genuine fear for loss of mental health and even suicide among the entrepreneurs & their employees facing bankruptcy.

Different funding models have been proposed ranging from helicopter money to boosting demand by issuing subvented service vouchers. Each approach comes with its own pro's and con's.

Indiscriminate bulk funding has a high risk of abuse and might cause market distortions & rampart inflation.

On the other hand, subvented voucher schemes to boost consumers spending are slow to ramp up. They also create complexity for both the consumer and the merchant. Printing vouchers is also expensive, while fully digital vouchers would inevitably exclude people with limited digital skills e.g. the elderly.

Furthermore, the relationship between issuing the voucher and channeling funds to businesses is indirect. If we accept that there is urgent (weeks, not months) need for operating capital injection to prevent insolvency of many businesses, the indirect scheme might be too slow to roll out to have impact before it is too late.

Solution

Gov-Funders is a scheme of public-private match funding, which is designed to support service, culture and arts sectors.

In this model, a service provider in need of financial support to sustain the business during the Covid-19 crisis can apply for public funding. The funding decision is based on historical financial data of the applicant's business and additional industry specific parameters & thresholds set by the policy makers.

The funding decision is immediate, and given up to certain amount for a fixed period of 3 months at time.

To claim the funds, the service provider needs to make sales of products, or services as the best they can. This can mean providing discounted products, which are adapted for social distancing (e.g. take-away meals, virtual delivery), or by selling vouchers for consumers to be used when the business can resume up normally.

Use case 1: A ticket to a live concert costs 80€ and there is fairly predictable volume of demand for the shows. Event host converts the concert to the Internet, but no-one is willing to pay 80€ for a concert on their computer. Would the fans of the bands be willing to vouch 5-20€ to support their favourite artists? While an online concert is not what the fans would normally pay for, there could be appetite for small spending. Public funding would then bridge the gap between what the organisers and the band needs to sustain themselves, and what the audiences are willing to pay for.

Use case 2: A restaurant offers a high quality meal for 2 people normally at price of 80€. They can convert to serving picked up and delivered meals, but the customers are not willing to pay 80€ for it; meal can be lukewarm when served, delivery time is unpredictable, and the experience doesn't include the ambience of the great service. There could be willingness to pay 15-20€ for such a meal, but the business still needs the 80€ to be operational. Public funding could bridge that gap.

With this approach, the business can apply and get immediate funding, but there is the element of market decision making. This introduces the necessary checks and balances that the businesses seeking for public funding are actually doing something which the market is willing to pay for.

Auto approved match-funding would reduce the administrative burden in funding decision making. This is needed to make sure the money can be channeled to the industries in desperate need of operating capital in time to make the impact. Time is of the essence here, because the impacted sectors are notorious for having very limited buffers and many businesses are already folding.

Because match funding is —just a promise—, the business still needs to see the effort to sell their product to someone willing to pay at least something for it. This should reduce the abuse of frivolous funding claims, as fraudulent, or utterly silly products, are unlikely to generate substantial revenue regardless of their low cost.

This mechanism is being used in innovation match-funding. Perhaps it could work also in funding the service, culture and art sectors if adapted correctly.

What it does

If there would be a decision to provide temporary public funding to rescue the impacted sectors, the administrative workload can be expected to be overwhelming. There would be a huge flood of funding applications with a wide spectrum of purposes & legitimacy.

Gov-Funders would be a stack of technology, which makes it easy for the service providers to submit a funding application easily and without the need for complex application process.

If the application could be based on verified business records (e.g. trade register, tax records and publicly available financial statements) and predetermined parameters, they can be processed by automated decision making technology. The funding decision would therefore be immediate.

The merchant would get a funding promise for grant support (or a composite of grant & loan), where the public funding would match any sales with the ratio needed to make the product viable for both the merchant and the consumer.

Public funding would be proportional to the historic size & nature of the business and issued for 3 months. After the first period, there is a check-point to see if the funding is still needed and has everything in been done diligently.

The benefit of this system is that it is immediate and would not require any additional technology from the merchants or the customers: Merchants with online stores, which support discount codes can promote a code, which automatically give the customer the subvented prices. Merchants without such capabilities can inform about the amount of discount as a written notice and calculate the discount to the customer manually.

At end of each month the merchant reports the sales using an automated system and receives government funding on their account within 3 working days. This is very important to keep up the money circulation and make sure the business has sufficient operational capital to pay for rents, salaries and other fixed expenses.

Financial controllers will make random checks, study analytics, and process abuse reports to direct enforcement resources where they are needed. Any abuse of the support funding would result in reclaiming of the funds retroactively, as well as to criminal prosecution if the abuse is intentionally malicious.

How I built it

Website for processing the funding applications. Integrations to government databases to fetch business ID and tax data to automate the data input as much as possible. This serves dual purpose: the data is easy to input accurately and it is verified so that it can be used in automated decision making.

Parameters are unlikely to be very complex so there isn't need for a complex AI or machine learning technology, so its quick to build. However, if there is AI capabilities, which are relevant & fast to deploy they would be ideally be used to make sure the automated decision making process is solid.

Challenges I ran into

Our team lacks data scientists and funding experts to build a proper funding application evaluation model. We are getting advices from mentors and experts, but the challenge is too complex to be realistically solved in just few days.

Diligent work would also be needed to evaluate which sectors and which kind of business cases would be viable for this funding model. For example, if the restaurant is located in a building, which is completely closed and there is no way of opening it up, their chances of generating any revenue is —very— limited, while the need for direct capital injection is accentuated. For such cases there should be non-automated decision making process. During the weekend we couldn't work out a solution for this vector and was scoped out even though we consider such cases probably the most critical and urgent to address.

Furthermore, more detailed work would need to be made on how to establish the thresholds & parameters and how to build up the decision making algorithms needed in the automated decision making. That would require specialist knowledge and serious effort to roll out something like this

Accomplishments that I'm proud of

We have attracted very positive feedback for this project and some really cool minds have joined in as contributors. We feel that the interest toward the idea is a very encouraging signal that the approach we are taking has validity and relevancy & is worth of exploring.

What I learned

Over the weekend we have made interviews with potential users of the system. This included both restaurant owners and their potential customers.

To our surprise the initial idea we had about subvented vouchers given for the consumers was knocked down almost uniformly by our study group participants .

One participant from Switzerland reported that their country is the promised land of vouchers and it is driving her crazy. She couldn't stomach a single voucher more, because they always have issues with validity, they are never with you when you need them, etc, etc. According to her, she would not opt in to yet another voucher scheme regardless of what is on the offer. Others agreed her and much preferred the simplified model where the merchant informs them about the discounted price and they pay what is due to be paid, fully understanding that there is a subvention scheme funded by the state.

From the service provider side we learned during the interviews that the need of financing is immediate and it must boost operational capital immediately. Voucher scheme was deemed to be too complex and vague to make sense operationally. A clear funding decision with a predictable financial numbers, fast money circulation, and simple fund reclaim process is a must to make it viable.

What's next for Gov-Funders

We are currently working on the presentation material and looking for policy makers and experts interested in the concept.