KoinWorks, an online P2P financing platform for small and medium enterprises (SMEs) in Indonesia, has added Lendable to its cap table after the emerging market debt provider and investor injected US$10 million into it.

This round comes just over a month after KoinWorks raised US$20 million in  debt and equity investment from Quona Capital.

Also Read: Going big? Then Go e27 Pro.

“As a company that focuses on productive sector funding, KoinWorks will aim to strengthen digital SMEs in Indonesia, with the support of thousands of retail lenders and other financial institutions that have been working together with KoinWorks to boost the growth of digital SMEs, particularly during this pandemic,” said Co-founder Benedicto Haryono.

KoinWorks provides a Machine Learning-based platform to connect lenders and borrowers. On the platform, both parties can fulfil their needs of either gaining maximum returns every month or getting an affordable online loan.

The firm claims that it currently has 400,000 users in its platform, with almost 220,000 lenders.

KoinWorks has previously raised US$1.4 million in Series B2 round from Japanese financial services company Saison Capital.

Special Initiatives

The lending platform has initiated several programmes to support digital SMEs in Indonesia. They include #LokalSupportLokal, a microsite which involves public, brands and media to donate their social media pages to promote products offered by SMEs.

In partnership with East Ventures, KoinWorks also recently completed a donation programme, called KoinDonasi, for test kits and genetic research upon COVID-19 vaccines.

Also Read: [Updated] Indonesia’s KoinWorks raises US$20M from Quona Capital

Previously, the company offered educational loans, with plans to launch eight new services in 2020, including gold saving, according to Jakarta Globe.

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In our legal work, we found that many technology companies tend to neglect to protect their intellectual property assets. It can be embarrassing for founders especially when they’re fundraising.

If it was discovered during legal due diligence by venture capitals or investors, you may also lose some contractual leverage.

I mean, if you are a technology company, what else would be more important apart from your team if it’s not your intellectual property assets?

First, intellectual property (IP) assets refer to a set of legally recognised assets under the law such as copyrights, trademarks, industrial design, and patents, and so on. But in this post, we’ll focus on copyrights and trademarks as they seem to be more common IP assets that generally apply for many technology companies and startups.

Let’s take a look at the simple steps on what to do below.

Do you own your technology?

It is crucial for technology companies to ascertain if they actually own the technology.

Also Read: What tech startups need to know about Intellectual Property in China

For instance, when an early stage company is just starting out, it may have outsourced certain product development to a third party such as an outsourced software developer (as opposed to developing the MVP or prototype in the house).

In this case, everyone needs to sign the necessary IP assignments for the company. This usually includes all developer, service, any business agreements with another party, and in all employment, consulting, or advisor agreements to the company.

Have you protected your technology?

Usually, the most important intellectual property asset for a technology company relates to its source code.

In every country, there is an intellectual property office that is in charge when it comes to filing work. For example, under Malaysian laws, a company can protect its source code by voluntary filing to Malaysia Intellectual Property Office (MyIPO).

Source code such as lyrics or manuscripts falls within the scope of a “literary work” under the Copyright Act 1987.

This is different from a trademark which refers to a sign, design, or expression which identifies products or services. Like copyright, to protect your trademark, you need to do a trademark filing to the regulator. This can be done by engaging a trademark agent or by self-filing.

Before filing, the standard practice is to do a search on the current database and see if they are any similar trademark filing that may have been done over a similar name or logo. A good trademark agent would be able to highlight your prospect of succeeding in a filing application or if it may be better if you change your name.

Also Read: Screwing up IP law is an easy way to doom your startup

As a technology company or startup, you also need to decide on the level of protection. The protection is territorial in nature. In other words, you need to file a separate filing in every country that you wish to protect your IP assets.

In Malaysia, previously a company may be required to engage a trademark agent to do filings in every country that it seeks to be legally protected. But thanks to the newly-amended Trade Marks Act 2019, companies can now file worldwide protection over its trademark by a single filing to the regulator.

You should speak to your legal counsel on whether you should do worldwide protection.

How do you monetise your technology?

When it comes to monetising your IP assets, for a technology company, you need to demonstrate proof of your IP ownership. So if you have an unclear IP assignment, it may be more difficult for you to monetise your software or services.

Owning a technology itself does not automatically generate money for a business. A technology company generates income by licensing the use of its certain software such as ‘Software as a Service’ (SaaS) which can be a B2B or B2C solution.

This is where having a licensing agreement or even a term sheet in place can help save cost and time.

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COVID-19 is a black swan event and it fundamentally changes the way we pursue Machine Learning in the real world. For businesses facing these rapid changes, the AI/ML models currently live in production are trained off of data that is very different from today’s pandemic situation.

A simple example is, a huge reduction in commercial flights might mean a drop in the accuracy of weather forecasts. Large-scale weather forecasts are made using sophisticated computer programs that model a virtual world. The accuracy of the output of such a model depends on the quality of the input.

One of the usual sources of input is an aircraft, feeding back real-time wind data. COVID-19 has considerably reduced the number of aircraft operating. As a result, the incoming information has dropped and forecast winds at cruise height can no longer be verified and the feedback loop into the global model is much weaker.

Similarly, finance models (used for credit analysis, asset pricing, demand forecast, etc.) taking unemployment data into consideration will see some extreme input variables never seen previously. A look at unemployment data that was just released this week. The reading of 17 million people filing for unemployment is four to five times the next highest reading and a more than 25 times sigma event.

Any model using unemployment data as input and making a decision on this data is using a feature that is more than 25 Sigmas outside of the expected value. This is an event that would be calculated to happen once every 100,000 years!

A model working on this input is unable to handle every unexpected event perfectly and give an accurate response.

Also Read: This Machine Learning startup helps breast cancer patients customise treatment, predicts risk of recurrence

ML models are trained on previously seen observations to predict future scenarios. However, today these models are seeing events different from what they were ever trained on.

Many businesses (especially in credit and finance) have hundreds to thousands of live production models running in their organisation, making incorrect decisions on data that affect their business outcomes across sectors – health, business, finance, gig-economy, credit, commerce, auto-traffic and travel to name a few.

The models that are likely to have problems in the coming days or months span credit, home pricing, asset pricing, demand forecasts, conversion/churn models, supply-demand for gig companies, ad pricing, in addition to several others.

With that in mind, it’s important to think about the model observability, overall systems resilience to these inputs, and the ability to troubleshoot as issues arise. The most important thing is for teams to have models that are observable; if you can’t observe, you can’t adapt. This means having instrumented detection+analysis on model decisions.

As a rule of them for model observability It is important to look out for the following:

• Events that are outliers should be detectable and surfaced automatically
• Outliers events should be linked with analytics for troubleshooting the model’s response
• Monitoring distribution shifts in input data because of these events
• Robust splicing and filtering capabilities for model input

Also Read: Differences between AI and Machine Learning, and why it matters

Input Variables:

Key Input-level monitors that an AI/ML model should have in production while factoring in the black swan events:

• Input checks to determine if values and distributions of features are drastically different than normal benchmark periods
• Checks on single events or a small number of recent events detecting out of distribution issues
• Detect if the features your model is most sensitive to, have changed drastically and factor that in accordingly
• Statistics to determine how far off the features are from the training set

Model Response:

Once you know the input to a model has changed, the next thing to monitor is how the model is responding to extreme inputs.

• Check the model’s performance for specific subclasses of predictions. Certain sectors such as Energy, Airline, or Travel might have significant risks. Best is to have fast online checks against various groups of predictions
• Use prior periods to produce worst-case and base case scenarios to then compare against outcomes
• Monitor the predictions in real-time against every new truth event (real-world prediction feedback) you receive
• If real-world feedback is not possible due to time lags, use proxy metrics — things you can predict and measure to determine the models’ performance

Also Read: Differences between AI and Machine Learning, and why it matters

Overall best practices:

The best practice for production ML models is not far off from best practice for production software — building observability tools to understand what is happening when models or software is live to catch issues before it impacts your customers. Some best practices for production ML models during these extreme environments are as under.

Track and identify outlier events

Tracking input data and model performance on outlier events is key. Annotating these events and being able to filter upon outlier events can help when gathering training data for future extreme environments. It is also important to consider whether to include outlier events in data for future model training. The model will be proactive against future extremes, but it also might think extremes are the new normal.

Decide on a Model Fallback Plan

Understanding how the model has performed in the past during extreme environments can help understand how the model is performing now. If the model is not performing well, it is best to set up naive forecasts based on the last N minutes or N Days and compare the model performance to this naive model.

Find look-a-like events

It is important to have enough observability into past similar events to set up look-alike modeling for this current situation. For example, if your model took in unemployment data as input, you might be able to leverage unemployment data from similar economic downturns, such as the 2008 recession.

Also Read: Survival vs growth: ShopBack CEO shares 3 golden rules to withstand the pandemic

Build a diverse portfolio of models and compare model performance

Real-time models that are reacting to the external world might be performing better today than batch predictions. Having a diverse portfolio of models enables teams to compare model performance and route traffic to models that are reacting better to extreme environments.

Combine various models by ensembling or stacking

Stacking or ensembling different models like tree-based or penalised regression models together would reduce the estimation error of the output and make the forecasts more robust during extreme events.

Know the uncertainty of your model’s predictions

Real-life modelling scenarios can be marketed with the absence of a good model altogether. In these cases, do you know how uncertain your model is? In this case, do not rely on point estimates rather return the model’s predictions with its confidence levels. In extreme periods, the uncertainty band will increase providing valuable information about the unreliability of point estimates

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While running his design-centric online furniture startup Fabelio in Jakarta, Krishnan M Menon used to travel to rural Indonesia a lot.

During these trips, he would visit many Usaha Mikro Kecil Menengah  (UMKMs) or MSMEs located in Tuban, Cirebon and Jepara.

These visits made him realise that while the archipelago has 56 million MSMEs, the technology revolution was only happening in the “premium” Indonesia. The sector and the country would benefit if these businesses were digitised and included in the financial ecosystem.

“I started brainstorming on how to support and accelerate the process of digitalisation. I discussed this idea with Lorenzo Peracchione, my long-time friend and former boss at Lazada. And this led to the birth of BukuKas,” Menon tells e27.

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Launched in December 2019, BukuKas helps owners of MSMEs understand and manage their financial flows effectively with a free-to-use digital ledger mobile app.

“Starting BukuKas reflects our dream to help millions of business owners, who form the backbone of the real Indonesia,” Menon remarks.

Menon, a serial entrepreneur, and Peracchione, who has previously worked in Luxola, had come very close to starting a business together several times, but their plans didn’t materialise. Now, with BukuKas, they found a vision that was very relevant to both of them personally.

“Helping small businesses is a very personal mission for me since I grew up in a family that ran a small agricultural business. I saw my father experiencing problems managing cashflows and collecting credit first-hand,” says Peracchione, narrating the story behind BukuKas.

While Menon has in the past built Freecharge, besides Fabelio, Peracchione helped cosmetics e-commerce startup Luxola to launch its Thailand business from scratch. Following its acquisition by LVMH-owned Sephora, Peracchione built its mobile business in Southeast Asia from the ground up.

Book-keeping made easy

Many small businesses in Indonesia still traditionally manage their finances using pen and paper. Furthermore, they struggle to get visibility and have no clue about the profits they earn.

The BukuKas app provides a simple book-keeping solution that can record sales, expenses, accounts receivable, and debt. It can also send reminders to their customers to pay back.

“The app allows small business owners to save 40 minutes a day as they can now avoid tedious manual calculations and reconciliation,” Menon boasts. “Our users say they manage to improve their profits by 10-20 per cent every month as they manage their expenses better and have an easier time collecting money from customers.”

The startup is now working on several new features that will help MSMEs improve sales, financial services and stock planning.

COVID-19, a blessing in disguise

As of April 2020, BukuKas has signed up over 250,000 merchants. The number has increased by 50 per cent since the outbreak of the pandemic.

“Offline businesses relying on retail outlets have been hit hard by restrictions imposed in light of the pandemic, with several claiming revenue drops exceeding 60 per cent. As a response, small merchants are trying to shift their focus to online channels, especially informal ones like Instagram and WhatsApp,” says Peracchione.

“BukuKas makes it easier to keep track of business activities across different online channels and facilitates remote business management, as users can access and manage bookkeeping anytime, anywhere via mobile,” Peracchione explains.

Also Read: Indonesia’s logistics aggregator Shipper secures US$20M Series A led by Naspers

One key lesson that COVID-19 has taught the founder-duo is that they need to invest more time and resources into understanding and helping merchants better.

“We see our merchants affected by the virus outbreak. To help them out, we have started promoting their business on our social media channels and  conducting English classes for free to up-skill them,” says Menon.

Recently, BukuKas raised undisclosed funding from Surge, a scale-up programme run by Sequoia India; Credit Saison; and 500 Startups. It also has the backing of over 20 angel investors, including Happy Fresh CEO Guillem Segarra, and Kopi Kenangan founders Edward Tirtanata and James Prananto.

“The Surge team truly helps entrepreneurs build great companies. From guiding us through setting up our fundamentals right, to helping us execute on a day-to-day basis be it on hiring, strategy, product or pretty much anything we ask for, to exposing us to incredible entrepreneurs like Tokopedia Co-founder William Tanuwijaya, so we can be inspired and learn from them,” concludes Menon.

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Image Credit: BukuKas

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If you want to get to know the story behind the scenes – the highs, the lows, the struggles, the accomplishments – let’s start at the beginning, shall we?

It all started back when I was working at a bank with an even fancier title, Premier Account Manager (Need I say more?).

But you know that nagging voice in the back of your head? Well, mine was always telling me there was something missing. That I should break away from the nine-to-five grind and just start my own venture.

The trouble is that the voice in your head said, “So what if you don’t have what it takes to pull it off? All you need to do is be the hardest worker in the room.” Here’s the truth – There’s never going to be a perfect moment because it doesn’t exist. You need to make the moment perfect by reaching out and grabbing it with both hands.

So, that’s what I did, I quit my job a month before our wedding and flew to Australia with my newly-wed bride on what was supposed to be my honeymoon. But it ended up becoming a business trip instead.

Thus, I began my entrepreneurial journey, with a bucket list of ideas and a heart full of hopes which I later learned were probably all I needed at the time.

Back when I had travelled overseas for an exchange program, I witnessed first-hand the challenges that international students have to navigate to find a place to stay. It was from these personal experiences that I got the idea for my startup.

Also Read: Dathena closes US$12M Series A led by Jungle Ventures to protect businesses from cyber attacks

We have helped solve the very real problem of connecting students with verified, 100 per cent safe, and secure private accommodation with campus-like facilities for a smooth transition into university life.

A new beginning

The first year was brutal. I worked out of a tiny cabin in Delhi, reaching out to students who were struggling and relying on their word-of-mouth referrals to stay afloat.

My co-founder (and friend) Mayank chipped in from halfway across the world before finally joining me for good. Together, we built a simple listing page on WordPress, and with that, we were officially in business.

How’d we pull it off with zero technical know-how? Well, your guess is as good as mine. That, folks, is how we made it through the first year, oscillating between highs and lows – sometimes all in a single day.

As the year rolled by, the tiny cabin started to get a little too full for comfort. We moved operations to an airy, co-working unit that let us spread our wings, both literally and otherwise.

We were frantically trying to juggle between two worlds, setting up base in India and expanding in the UK.

I still remember when Mayank and I travelled to the UK for the first time, not as tourists but on official business, with back-to-back meetings that ran well into the night and last-minute travel plans that took us to the far ends of the city. We met accommodation providers who’ve now become long-term associates and welcomed interns fresh out of college. And I’m proud that many of them are still a part of our journey– successful managers and senior associates.

Also Read: How startups can harness e27 Pro and push for greater business success

While 2017 was the year of consolidation where we tested (successfully I must say) features that are now synonymous with our services, the year 2018 was undoubtedly the best year for us. We started off the year on a high note by launching our brand-new platform with end-to-end solutions, doubling our workforce, and ended it on an even higher note by establishing a strong referral programme with global universities, delving deeper into Ireland, Korea, France, and New Zealand. Phew, it was one hell of a ride, and I wouldn’t trade it for the world.

A land of opportunity

By the time 2019 had come rolling around, we had improved CRM automation and implemented AI to pre-emptively anticipate customer needs and accelerate user engagement. Since the world is our oyster, we never stopped exploring other opportunities and ended up expanding into the USA and Canada.

Coming to the present year 2020, we’re all aware of the unprecedented crisis that the world is facing. During this time, we have been hard at work, rewriting the playbook for success. We moved quickly in response to the unfolding situation with the global healthcare crisis, from adapting to the new normal of working from home to constantly coming up with new strategies to expand.

We are a tech-enabled platform that leverages the power of AI and ML to address a real-world problem, allowing us flexibility when it comes to working remotely. All of our existing team is developing their cross-functional skills, putting in extra efforts towards their tasks and going out of their way to pitch in where necessary.

Do you want to know the best part? We successfully hosted our first webinar where we partnered with experts from different facets of the education sector, all of which were done to address the concerns of one of our most valuable stakeholders – the students.

Also Read: How getting digital transformation right can help businesses get through a pandemic

It was just the confidence boost that we needed at a time like this, and now we’re well on our way to host the second one.

Given our whirlwind of a ride, I can say with certainty that I am extremely proud of what we’ve achieved, where we’re going, and the millions of student journeys we’ll make memorable.

Once we step out of our comfort zone and push the boundaries, that’s when we will become a better version of ourselves.

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Register for our next webinar: Fireside chat with Paul Meyers and Jussi Salovaara

Editor’s note: e27 aims to foster thought leadership by publishing contributions from the community. Become a thought leader in the community and share your opinions or ideas and earn a byline by submitting a post.

Join our e27 Telegram group, or like the e27 Facebook page

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