Singapore is home to several InsurTech start-ups; in this publication, I will profile two Singapore headquartered start-ups: DocDoc and Axinan; who have made key announcements in August 2019.
- On 7th August 2019, DocDoc closed a $13M financing round, bringing its total funding to $24.6M .
- On 21st August 2019, Axinan announced that it has acquired a combined insurance and reinsurance license from Labuan , effectively making its transition from insurance technology vendor to licensed risk bearing entity.
- On 27th August 2019, Axinan partnered with Indonesian e-commerce giant, Bukalapak, to offer electronics insurance for buyers and transit insurance for both buyers and sellers, with Sompo Insurance as the underwriter. 
The problem of a lack of structured data together with opacity in the healthcare system (resulting from asymmetric information) is what DocDoc aims to address.
There’s a story behind every scar. The couple-turned co-founders required a liver surgery to be performed on their 90-day old baby. In spite of their extensive professional network (Grace was a Managing Director at Medtronic), they were unable to find a suitable expert. In the end, the couple had to bear the expense of flying and housing Koichi Tanaka along with his team from Japan for a two-week period. The opacity in the healthcare system combined with their frustrating personal experience was enough to convince Grace and Cole that they needed to do something.
- Operates in 8 Asian countries with over 23,000 contracted doctors on the platform.
- Backed by notable investors including HK Cyberport Macro Fund, 500 Startups and ADAMAS Finance Asia, DocDoc has raised $24.6M in venture capital funding.
- B2B2C approach – partners with insurance companies to provide value-added services to their policyholders.
The highlights from a one-hour conversation with Cole are provided below:
“What is the difference between Data Science and Machine Learning/Statistics?”
Cole believes that Data Science is concerned with building sensible structures to store and query data. Whereas, Machine Learning/Statistics is concerned with analysis of (structured) data to build explanatory and predictive models.
In healthcare, analysis is a relatively easier task, structuring the data is the main challenge. Cole believes that a significant number of problems in the healthcare industry today can be resolved with structured data. He says, “In medicine, most algorithms are surprisingly simple, what is complex is the underlying knowledge model which is used to store data and its various relationships”.
“What is a major problem in healthcare today?”
Cole takes the example of the game of Chess. In particular, he describes that the board and the set of permissible moves by each piece provide “structure” to the game of Chess. The sequence of moves chosen by each player is representative of “data”. Cole believes that developing a game like Chess is a harder proposition than playing the game Chess.
He ties back the Chess analogy to the healthcare industry today – the underlying problem is a lack of structured data (emphasis on structure). As a patient, you have a right to access basic information about the medical expert who is treating you. For example, if you require a hip replacement, you should be able to check the surgeon’s track record of performing hip replacements along with their medical qualifications, academic publications and relevant patient feedback.
As the healthcare industry stands today, it is not possible to query a database (or set of databases) to extract this information for patients. Transparency is also in the best interest of insurance companies (“payers”) as it allows them to verify that claims are being disbursed to avail of services provided by qualified practitioners at market rates.
DocDoc operates as a B2B2C healthcare and health insurance technology focused start-up. DocDoc has established partnerships with health insurance companies and is embedded within the customer journey (currently, it does not have a standalone direct B2C app). Policyholders can simply click on a button such as “Find care” on their insurance portal and they will be directed to DocDoc’s medical concierge. When a policyholder contacts DocDoc, a trained doctor (doctor discovery consultant) guides the policyholder through their healthcare journey and leverages DocDoc’s AI-powered doctor discovery engine, HOPE, to provide data-driven advice and to recommend a panel of doctors for the policyholder. This panel of recommended doctors is customized to suit the medical requirements of the policyholder’s condition or the requested procedure.
The service is free of charge to doctors. Doctors are selected based on expertise only. Instead, insurance companies pay for better healthcare outcomes for patients, reduced cost, and transparency.
DocDoc’s proprietary AI-powered doctor discovery engine, HOPE, stands for “Heuristic for Outcome, Price and Experience.” HOPE applies DocDoc’s knowledge model and learning algorithms to extensive proprietary data collected from the DocDoc network. The knowledge model allows DocDoc to structure the vast amount of proprietary data they collect.
DocDoc’s team seeks doctors, clinics, and hospitals with excellent outcomes who believe they are the best at what they do. The team spend hours with each doctor (in some cases over 10 hours), investigating the quality of care and documenting procedures and conditions where the doctor excels. In addition, information regarding the doctor’s track record, cost of treatment, patient feedback and academic qualifications is collected. This information is entered into HOPE which finds a best match between individual patient’s needs and a doctor’s experience.
This process is transparent from the viewpoint of the patient and insurance company since the criteria for doctor-patient matching is known (outcomes, price and experience) and the process is data-driven.
The next potential step for DocDoc is to build an automated TPA (Third Party Administrator) – given that the company has access to structured data, it is possible to design a (multi-layered) rules-based system to manage claims payout. Naturally, there will be corner cases and fraud models may forward claims for human inspection. Automation can help reduce costs and speed up the claims process.
During our conversation with Cole, he highlighted that countries with nationalized medical programmes can keep costs under control due to the purchasing power of the state (compare statistics here). He suggests that DocDoc can help improve the overall state of the (private) healthcare industry by reducing informational asymmetries (for example – lack of clarity regarding market rates of treatments, hidden incentives behind recommendations etc).
Without delving into complexities of economic theory, competitive markets are efficient and there appears to be a strong (macro)economic argument in favour of what DocDoc is working towards. It wouldn’t be surprising if a B2G (business-to-government) model emerges as a parallel to the existing B2B model.
- “Knowledge is power” and insurance is a data-business, it is not far-fetched to see DocDoc transform into a data-driven insurance company in the (near) future. Alternatively, it could partner with a capacity provider (for example, a reinsurer) to underwrite its own insurance policies. Interestingly, in episode 3 of the Asia InsurTech podcast, Chris Garrett from DocDoc touched upon this idea.
- Positive selection amongst doctors – the rigorous vetting process that listed doctors undergo serves as a signalling mechanism (for quality of service, domain expertise etc.) However, it should also be noted that doctors who self-select to be part of the DocDoc network already send across a signal that they can be trusted and are qualified.
Igloo is a on-demand lifestyle insurance app developed by Axinan; policies are underwritten by FWD Insurance and Sompo Insurance. A work-in-progress, the app, currently available in Singapore and Indonesia, offers Phone Screen Protection (PSP) and travel insurance.
Axinan has a patent pending for a Machine Learning algorithm that can detect existing phone screen damage through analysis of a user-taken selfie during underwriting. This permits the insurance partner to underwrite old phones as well. To file a claim, a customer simply must follow in-app instructions and visit a partner repair centre.
Igloo currently supports 800 devices including the iPhone X (at SGD 19.90 p.a. this product seems reasonably priced given that repairs cost SGD 42 with AppleCare+ and a whopping SGD 418 without!)
Axinan has also developed Phone 360 cover which includes diagnostic tests for underwriting devices prior to insurance policy issuance. Igloo in Indonesia has also started to cover all electronics and gadgets including home appliances and kitchen appliances by using the same technology.
In the B2B segment, Axinan leverages its expertise in high frequency and low premium insurance by partnering with e-commerce companies. Broadly, insurance policies for goods sold on e-commerce platforms may be classified as return shipping insurance and transit insurance.
Axinan offers comprehensive transit insurance for products purchased on e-commerce platforms which covers loss during transit, damage during transit and returns. On top of that, Axinan also offers electronics and gadget insurance via partners (i.e. Bukalapak), for protection against accidental damage.
Using ML algorithms, Axinan assesses the fraud risk for each transaction by using data collected during the e-commerce customer journey (such as contents purchased, buyer and seller information). Thus, Axinan computes a dynamic premium for each transaction which reflects the underlying risk associated with the concerned transaction.
It also includes a proprietary claims management approach which is proactive, secure and efficient. Axinan has partnered with Asia’s leading marketplace platforms such as Bhinneka, Bukalapak, Lazada, Shopee, Shopify, Tokopedia and T-mall for its enterprise offering.
As the firm looks to expand its footprint in SE Asia and beyond, Axinan continues to look out for underwriting partners in different regions. If you’d like to speak with the team, do reach out through email at email@example.com.
- Axinan’s capability to underwrite old mobile phones (for screen protection) should not be overlooked. As the firm expands this product to laptops, tablets and other appliances that have longer ownership cycles, this patent will reap E-commerce is a segment in SE Asia that is witnessing tremendous growth (a 2018 estimate suggests that e-commerce revenues in the region win greater benefits (for both end-customers and Axinan).
- It’s licence in Labuan sets it apart from most InsurTech firms in SE Asia (with the exception of Singapore Life, which is a licensed carrier in Singapore). Axinan is able to enter into a fronting arrangement with local insurers. Research conducted by Allianz  suggests that Malaysia will witness a 8.2% YoY growth in insurance premiums over the next decade; Axinan is uniquely positioned to leverage high smartphone penetration (57.5%)  in Malaysia.
- It is important to note that Axinan has secured a combined insurance and reinsurance licence. Specifically, the reinsurance licence permits a faster go-to-market strategy for Axinan in Asia outside of Malaysia subject to local insurance regulations and finding local insurers who are willing to cede risk.
The InsurTech ecosystem in Singapore, and Asia at large, is extremely active – if you’d like to hear or learn more about the ecosystem, please feel free to follow the Asia InsurTech Podcast (AIP) – the team led by Theresa and Michael upload a weekly interview with founders, investors and industry leaders. In addition to the interviews, AIP will run a news show, the fist of which may be found here or via your favourite podcast app.
Views expressed are the author’s own and do not reflect those of his past or current employer(s). The author does not have any financial or other stake (direct or otherwise) in any entity quoted within this report. This report has been produced for educational purposes. Further, this report should not be treated as legal, financial or any other form of advice. The author is not liable for financial or any other loss that may arise to the reader or an affiliated party as a result of information presented herein.
This report is not sponsored in part or in whole by any party and has been prepared by the author for the Asia InsurTech podcast.
About the author
Rahul is an Insurance Product Manager at Laka Insurance, a London headquartered early stage InsurTech start-up which recently won at the British Insurance Awards 2019. He spent his childhood in Mumbai, India and holds a master’s degree in Statistics from the University of Warwick.
As an Ambassador at the Asia InsurTech Podcast, he has a keen interest in the InsurTech ecosystem in Asia. If you found this article interesting, feel free to reach out via LinkedIn or Twitter. Any comments, feedback or constructive criticism is welcome.