YBF #FinTech pitch night

It’s getting difficult to keep up with all the FinTech activity in Melbourne – from Meetups to pitch nights, from hubs to incubators. The latest Next Money / York Butter Factory / Fintech Victoria pitch night was a showcase for three startups-in-residence at YBF. As such, it was not the usual pitch competition – more an opportunity for the startups to hone their presentations.

First up was Handy, an app-based solution that connects trades with customers to streamline the settlement process for property insurance claims. There is an industry-wide low-level of satisfaction with property claims – which can take up to 60 days to process, even though 80% of claims are for less than $5,000. Handy offers a faster solution, and doesn’t require a lengthy estimate or quoting process, using instead fixed-price rates. With a target market of 100,000 claims per annum, Handy expects to generate 25% savings to the insurance industry, as well as having a broader societal impact in terms of speedier claims, better appreciation of service providers, and more consideration of the respective needs of householders and trades. Launching an MVP in November, there are four insurance firms in pilot test mode. Aiming for a white label solution, Handy will charge clients basic setup and maintenance fees, as well as volume transaction costs (although the exact pricing and revenue model still needs to be worked out). There were audience questions about the liability for quality of work and dispute resolution, the trade supplier on boarding and verification process, and the process for communicating to policy holders whether their insurance provider or broker is covered by the platform.

Next was FinPass, a startup appealing to the 40% of the workforce expected to be freelance by 2020 – a key feature of the gig economy. Targeting so-called “slashies“, FinPass is designed to help customers apply for personal loans when they don’t have a single, steady or stable source of income – and therefore, may lack a formal credit rating or personal credit score – while adhering to the five Cs of credit. Using a combination of blockchain and API to validate a loan applicant’s income profile, FinPass would then make this data available to approved lenders (subject, presumably, to consumer credit and lending standards, customer privacy and data protection requirements). To be fair, this project was fresh from winning a recent hackathon event, and therefore is still at the concept stage. However, it was clear that much needs to be done to define the revenue model, as well as designing the actual blockchain solution. Audience feedback questioned the need for a standalone solution, given the existence of various block explorers, APIs, vendors, protocols and bank feed sources. In addition, while blockchain provides a level of transaction immutability, and since only the hash-keys will be captured, the SHA’s will only confirm the hash itself, not the veracity of the underlying data?

Finally, there was Resolve, a two-sided market place for the insolvency services – a platform to buy and sell distressed businesses. Designed to capture turnaround opportunities, the platform has a target market of 14,000 transactions per annum – of which only 1% currently advertised, simply because it’s too expensive to use traditional media (i.e., finance and business publications). In addition, 92% of companies that enter insolvency return zero cents in the dollar to their creditors. Part bulletin board, part deal room, Resolve aims to create a passive deal flow for this alternative asset class. When asked about their commercial model, the founders expect a turnover based on a few hundred businesses each year, and revenue coming from a flat $1,000 per listing – but the key to success will be building scale.

Each of these early-stage startups represent promising ideas, revealing some innovative solutions, so it will be interesting to follow their respective journeys over the coming months.

Next week: Bitcoin – Big In Japan

StartupVic’s Machine Learning / AI pitch night

Machine Learning and AI are such hot topics, that I was really intrigued by the prospect of this particular StartupVic pitch night. First, this was a chance to visit inspire9‘s recently established Dream Factory – a tech co-working facility, maker space, and VR lab in Melbourne’s western suburb of Footscray. Second, the Dream Factory, housed in a landmark building owned by Impact Investment Group, was a major beneficiary of LaunchVic funding, and this event could be seen as a showcase for Melbourne’s tech startup sector. Third, with so many buzzwords circling AI, it offered a great opportunity to help demystify some of the jargon and provide some practical insights.

Image sourced from StartupVic

Instead, the pitches felt underdone – probably not helped by the building’s acoustics, the poor PA system, and the inability of many of the audience to be able to read the presenters’ slides. I wasn’t expecting the founders to reveal the “secret sauce” of their algorithms, or to explain in detail how they program or train their “smart” applications. But I had hoped to hear some concrete evidence of how these emerging platforms actually work and how the resulting data is specifically analyzed and applied to client solutions.

Amelie.ai

With a tag line of “powering the future of mental health” the team at Amelie.ai are hoping to have a positive impact in helping to reduce suicide rates. Unfortunately, judging by the way some key statistics are presented on their home page, the data (and the methodology) are not as clear as the core message.

Using technology to help scale the provision of mental health and well-being services, combined with mixed delivery methods, the solution aims to offer continuity of care. Picking up on user dialogue and providing some semi-automated and curated intervention, the presentation was big on phrases like “triage packages”, “customer journey”, “technical architecture”, “chatbots” and of course, “AI” itself, but I would have like a bit more explanation on how it worked.

I understand that the platform is designed to integrate with third-party providers, but how does this happen in practice?

Only when asked by the judges about their competitive advantage (as there are similar tools out there – see Limbr from a previous pitch night) did the presenters refer to their proprietary language models, developed with and based on user trials. This provides  a structured taxonomy, which is currently English-only, but it can be translated.

There were also questions about data privacy (not fully explained?) and sales channels – which may include workplace EAPs and health insurers.

Businest

According to the founder, “dashboards and KPIs only diagnose pain, Businest fixes it“. In short, this is intelligence business analysis for SMEs.

With a focus on tracking working capital and cashflow, as far as I can tell, Businest applies some AI on top of existing third-party accounting software. It identifies key metrics for a specific business, then provides coaching and videos to change business behaviour and improve financial performance. There is a patent pending in the US for the underlying algorithm, which prioritizes the KPIs.

Again, I was not totally clear how the desired results are achieved. For example, are SMEs benchmarked against their peers (e.g., by size/industry/geography/maturity/risk profile)? Do clients know what incremental benefits they should be able to generate over a given time period? How does the financial spreadsheet analysis assist with improving structural or operational efficiencies that are outside the realm of financial accounting?

Available under a freemium SaaS model, Businest is sold direct and via accountants and bookkeepers. A key to success will be how fast the product can scale – via partnering and its integration with Xero, MYOB and QuickBooks.

AiHello

I must admit, I was initially curious, and then totally bemused, by this pitch. It started by asking some major philosophical and existentialist questions:

Q: How do we define “intelligence”?
Q: Are we alone? Or not alone?

No, this is not IBM’s Watson trained on the works of John-Paul Sartre (cf. Dark Star and the struggle with Cartesian Logic). Instead, it is an analytical and predictive app for Amazon sellers. It claims to know what products will sell, where and when. And with trading volumes worth $2.5m of goods per month, it must be doing something right. Serving Amazon sellers in the US and India (and Australia, once Amazon goes live here), AiHello charges fees based on fixed licences and transaction values. The apparent benefits to retailers are speed and savings.

Asked where the trading data is coming from, the presenter referred to existing trading platform APIs, and “big data and deep learning”. It also uses Amazon product IDs to make specific predictions – currently delivering 60% accuracy, but aiming for 90%. According to the founder, “Amazon focuses on buyers, we focus on sellers”. (Compare this, perhaps, to the approach by Etsy.)

C-SIGHT

A new service from the team at Pax Republic, this latest iteration is designed to avoid some of the policy and reputation issues involved with managing, supporting and protecting whistleblowers. Understanding that whistleblowers can pose an internal threat to brand value, and present a significant human risk, C-SIGHT provides a psychologically safe environment for the Board, C-suite and workforce alike, and can act as an early warning system before problems get out of hand.

Sold under a SaaS model, C-SIGHT analyses text-based and anonymous dialogue, with “real-time data sent to different AI apps”. I understood that C-SIGHT combines human and robot facilitation, while preserving anonymity, and also deploys natural language processing – but I didn’t fully understand how.

In one client use case, with the College of Surgeons, there were 1,000 “contributions” – again, it was not clear to me how this input was generated, captured, processed or analysed. Client pricing is based on the number of invitations sent and the number of these “contributions” – what the presenter referred to as an “instance” model (presumably he meant instance-based learning?).

Asked about privacy, C-SIGHT de-identifies contributions (to what degree was not clear), and operates outside the firewall. There was also a question from the judges about the use and analysis of idiom and the vernacular – I don’t believe this addressed in much detail, although the presenter did suggest that the platform could be used as a way to drive “citizen engagement”.

Overall, I was rather underwhelmed by these presentations, although each of them revealed a kernel of a good idea – while in the case of AiHello (which was the winner on the night), sales traction is very promising; and in the case of Businest, industry recognition, especially in the US, has opened up some key opportunities.

Next week: Bitcoin – to fork or not to fork?

Agtech Pitch Night at SproutX

Judging by some of the news coverage, last week’s pitch night showcasing successful applicants to the SproutX agtech accelerator suggests that this will be a program worth watching. (Look out for the demo day later in the year…) With an initial cohort of 11 participants, this recent addition to Melbourne’s startup scene is showing there is an audience and a market for smart farming solutions. Founded by Findex and the National Farmers Federation, SproutX also enjoys support from Ruralco and Artesian, as well as the Victorian Government.

Given the number of pitches, my comments on each startup presentation are necessarily short:

AgriLedger

This project is driving social impact by focusing on farmers in the developing world. It offers a smart phone app that helps deliver products and services direct to farmers, such as solar power facilities and micro loans, and enables them to plan better and to share equipment with other local farmers. Currently active in Papua New Guinea, Kenya and Myanmar, AgriLedger has been supported by some high-profile NGOs and attracted some impressive backers and advocates.

However, the judges felt that the pitch didn’t contain enough of the story, or explain how it actually works.

Applant

With a tag line of “aTree in your home”, Applant has come up with a novel design for a vertical gardening system that uses aeroponics. The idea is to help people “grow more with less”, and to grow food where we live, work, eat and even play. With an underlying concept for modular food systems, Applant is about to launch a Kickstarter campaign.

The judges had hoped to learn more about the customer demand and the proposed
customer subscription model.

Bloomboxco

Delivering locally sourced and farm-fresh cut flowers direct to customers, my immediate thought was “flower miles”. Launching just recently with a monthly subscription model, Bloomboxco has already attracted around 35k followers on social media (mostly Pinterest). By its own admission, the service appeals mainly to women who enjoy contemporary design and lifestyle trends.

But the judges wanted to know what makes this business different: given that the current supply model for cut flowers is built on margin, how does Bloomboxco aim to compete?

Farmgate MSU

With their mobile slaughter unit (MSU), the team from Farmgate want to “open the gate to on-farm abattoirs”. Many farms do not have access to an abattoir thanks to industry consolidation and contraction. The MSU is designed to cut production costs, minimize animal stress, and reduce waste. While still relying on central butchery services, the MSU has the potential to add value, especially for premium products, as it can operate at smaller scale. Farmgate also benefits from having a team drawn from across the meat supply chain.

For the judges, the pitch could have done more to demonstrate the capability, and to explain what happens to waste and by-products.

Farmapp

Farmapp has developed a digitized and integrated pest management solution for greenhouse crops. Using data collected from various sensors and stored in the cloud, Farmapp uses visual analysis, helping farmers to reduce their use of pesticides and increase productivity. It is currently installed in 1200 greenhouses (mainly Columbia and Kenya).

The judges wondered about the competition, as they were aware of a number of other similar solutions.

iotag

This “fitbit for cattle” uses long-range GPS monitoring to track and manage livestock health. In addition to the setup costs for network base sensors, there is a monthly subscription fee to manage data.

There were no comments from the judges, apart from the representative from the farming community, who claimed to hate subscription services.

Smart-Bait

Smart-Bait uses sensors, cognitive APIs and programmed alerts to track feral animals. Current solutions (baiting, fencing, shooting) are either unreliable, inefficient, or non-selective. Instead, Smart-Bait is leveraging IoT and AI, and can be used offline giving further flexibility. Currently conducting farm trials, the founders say that there is government interest in the data.

For their part, the judges wanted to know if there were other applications for this technology – but more importantly, they wanted to know how it actually works.

Snaptrap

This product enables remote pest monitoring and control, especially fruit fly. It retrofits to existing systems, and has established a successful proof of concept. Snaptrap is targeting research, government and industry users, appealing to both growers and the bio-security market. Another subscription-based product, the founders claim there are many use cases, and the solution is scalable.

The judges asked about the data (what happens to it), and our farm rep again queried the use of a subscription model.

Thingc

With the goal of producing “intelligent orchestrated things”, Thingc aims to reduce the number of manual tasks and alleviate animal stress in livestock management. Using the notion of precision management, it takes data from monitoring sources and applies it yield forecasting.

The judges wanted to know “where’s the tech?”, who is the competition?, and what exactly is the end game?

TieUp Farming

TieUp uses an algo-based solution to compensate for the lack of data available for yield forecasting in horticulture. The data is being made available to farmers, industry and banks, using an aggregation of different technologies. The founders claim it to be both practical and customizable, while they see significant opportunities in South East Asia.

The judges wanted to know how it actually works, and to what degree it can support traceability of produce?

Water Save

As the name suggest, Water Save is designed to reduce water and power consumption on farms. With increased concerns about water efficiency and environmental impact of run-off on the Great Barrier Reef, Water Save uses existing irrigation monitoring systems (micro weather stations, sensors) and connects them into an integrated and networked solution. The system involves set up costs, hardware costs, and subscription fees, but a key goal is to reduce the use of fertilizers – creating both economic and environmental savings.

The judges wanted to know more about the solution for linking individual sensors, and whether it has the capability to monitor nitrates.

 

For most of these 3-minute pitches, the challenge was to tell enough of the “story” while still explaining how it works – and there was a sense that the audience understood the context as well as the problem, and probably didn’t need too much background explanation. Instead, they would have appreciated learning more about the technology and the potential to succeed – i.e, “why you?”.

Farmgate MSU was declared the winner by the judges, and voted the people’s choice by the audience.

Next week: ASIC updates – Sandbox and Crowdfunding (plus #FinTech hub)

Making an Impact at Startup Victoria’s Pitch Night

A relatively new term that was coined around the time of the GFC, “impact investing” can be seen in the same light as CSR, TBL, ethical investing and conscious capitalism, whereby businesses combine purpose with profit, underpinned by strong and open corporate governance, with the specific goal of delivering social and environmental outcomes. Not to be confused, of course, with NFPs or social enterprises.

The latest pitch night hosted by Startup Victoria, with support from impact VC investor Giant Leap Fund, presented four startups that all aspire to bring about some form of social impact, in areas such as: transport for women; gender diversity in the workplace; mental health; and training for disability support workers. (Surprisingly, there were no pitches from startups with a direct environmental impact.)

In order of appearance, the startups were (as usual, links are in the titles):

Diverse City Careers

Offering a new approach to recruitment, DCC only work with employers who meet their standards on workplace policies for women. Currently seeking $1m in investment, they claim that 50% of their candidates get shortlisted, and 25% get hired, and already have 80 accredited employers on their books.

Using an endorsement model for accredited employers, as well as standard recruitment services, DCC is able to generate both annuity and transaction revenue. By ranking employers and holding them accountable for their own policies, is able to promote best practice and establish industry benchmarks. DCC is now moving into industry and media partnerships, and plans to build a dashboard for analytics.

The panel of judges were keen to understand how DCC will maintain its point of differentiation, as well as build on its definition of diversity (e.g., transgender, transsexual and intersex). And given that there are federal initiatives already in this space, does an accreditation from DCC have as much value or impact?

Enabler

According to data provided by the presenters, around 1.9m disabled people in Australia need support workers. With the introduction of the NDIS, the number of trained helpers needs to grow from 300k to 600k, and there are currently 3,500 disability service providers to help train, recruit and employ these support workers. A key challenge is the quality of available education, with providers only spending $1,265 per worker per annum on training and development.

Enabler is seeking a $250k seed investment to launch a new product, comprising core content and training modules distributed online and delivered via mobile devices. With a focus on personalised content, Enabler is already in talks with 11 service providers and engaging with existing paying customers (who represent as few as 70 to around 1400 end users).

The key challenge I found with this pitch was the lack of explanation on why current training content and materials are proving to be so inadequate (even allowing for differences in individual learning styles). For example, what makes Enabler’s service so much better, and how will it achieve sustainable personalization in a product that needs to be both scalable and economically viable?

Shebah

This is a ride share service for women drivers and passengers (and their kids and pets), that grew out of economic and social necessity. It started life as a project on Go Fund Me, has since pivoted to Shebah, launched a mobile app, and is now available in Melbourne, Geelong, Brisbane, Gold Coast, Sydney and Sunshine Coast (with Perth, Darwin and Adelaide to follow).

Adoption among the disability community has been a notable side effect (e.g., enabling customers to get to medical appointments), and each driver gets a free consultation with a CPA about setting up an ABN etc.

Experiencing 40% growth in volume (and 100 new accredited drivers per week), the founder is asking for $500k funding to hire an in-house engineer/developer to build additional app functionality (such as pre-booking), scaling the business and growing to a minimum 1,000 rides per day. The app can already take multiple currencies, and there has been interest from Mexico, South Africa and Brazil.

With the various issues facing Uber and the gig-economy itself, the judges were naturally keen to understand how Shebah regards its own drivers (i.e., employees or freelances). For registration, tax and accounting purposes, Shebah drivers are treated as independent contract workers (sole traders), with no required minimum hours. (The founder mentioned potential plans to offer drivers share options in the business, which could prove an interesting business model.)

Despite some reasonably high-profile media coverage, Shebah has not undertaken any advertising campaigns, relying instead on general publicity and friendly ambassadors.

Asked about customer experience measures, the founder mentioned average waiting time, and driver retention as key indicators (apparently, the only 4% of Uber drivers last more than 12 months). Shebah also acknowledged that their fares are cheaper than taxis (but more expensive than Uber) with an average fare of $25, representing a margin of less than 10%

Limbr

With a tag line of “a place to be real”, Limbr is an app-based platform that is designed to take some of the stigma out of mental illness, and provide easier access to mental health services.

Despite the staggering mental health statistics, two-thirds of sufferers never seek treatment. To break down some of the barriers and overcome access issues, Limbr offers a three-tier service: a free “social network”, a personal dashboard tool, and online support from qualified mental health professionals (“listeners, coaches, therapists”). The revenue model is a combination of subscription fees and commission from provider sales, plus evidence-based public funding.

The founders recognize it’s a highly fragmented market, so therapists are interested in the referral aspect of this new channel to market. (One challenge is that the current $10 bulk bill rebate to see a therapist is not available for e-health providers.)

The app plans to use popularity to drive traction, and while the message that it’s “OK to share” is designed to be positive and encourage a healthier approach to mental illness, there was some concern that in some ways, the internet has normalised the issue. The presentation mentioned that there are 20m posts about depression on Instagram. So, isn’t social media, along with increased isolation and anti-social online behaviour part of the problem?

Asked by the judges about privacy, authentication and trust, Limbr plans to go to market via therapist advocates, and will focus on moderation and data analytics.

Based on the night’s presentation, the judges awarded Shebah first prize, and it certainly was the most engaging and rounded pitch of the four.

Next week: More on Purpose