No matter who wins UK election today, homeowners get a small break thanks to Neos Insurtech with AI + IOT


UK Insurtech Neos was in the news last week for raising a £5M Series A round, led by Aviva Ventures with strategic partner Munich Re.

In this post we dig below the news headlines to understand the trends illustrated by what they are doing.

More than a random buzzword generator

At one level, one could view Neos as combining all the hottest buzzwords to unlock VC funding:

  • Insurtech
  • IOT and connected home.
  • AI via Chatbot.

Our belief is that the hype cycle and the reality cycle are disconnected. Yes, all the above are hot, hot, hot. Yes, all will fall into the slough of despond, because that is what happens to all overhyped trends. Yet all three have huge value – if applied properly to solve a real pain point. That is what we now turn our attention to.

A win/win/win proposition

Neos is creating a win/win/win proposition for:

  • Homeowners. Brits love the expression “a stitch in time saves nine” meaning that paying attention to something small now – like a plumbing leak – will prevent an expensive disaster later.


  • Service contractors. They will benefit from a flow of work to fix those things – like the plumber coming in to fix a leak.


  • Insurance companies. They save on preventable expensive disaster claims and re-establish themselves as being central to their customer’s lives (not just a premium bill to be paid each month).


Look at this chatbot conversation to see something that will resonate with almost every homewner:

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That makes IOT and connected home useful in a way that the oft-hyped milk buying fridge does not do. It also shows the use of AI Chatbots to deliver something useful; we believe that AI Chatbots will become as ubiquitous as websites and mobile apps, no longer a source of advantage, simply a must have item.

Now if only somebody could apply that same thinking to something even more precious than a home – the human body. Prevention is the back to the future of healthcare and health insurance and IOT sensors and AI Chatbot will be the key to this market as well.

UK innovation is alive and well

My home country has been down in the dumps since Brexit and goes to the polls today to decide who will lead the future of the country.  Whatever direction the country goes in, innovation will be the key to jobs and prosperity. Neos shows that UK innovation is alive and well.

Join the debate;

On this election day, do you think UK can reclaim tbe fintech capital of the world title?

Bernard Lunn is a Fintech thought-leader and deal-maker. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.

Millennial Mortgages – Can AI deliver a human touch to home lending?


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Every year $25 Trillion in new mortgages are issued. Mortgage is perhaps the biggest investment decision consumers make in their lifetime. However, the mortgage process is inefficient, highly intermediated with many pain points and remained has so without too many disruptions for decades.  Low interest rates and squeezed margins define the current state of the incumbent mortgage lenders, who can hardly think of a better way of doing business. Two startups Habito in the UK and Better in the US are using AI to add efficiencies to different parts of the Mortgage processes.

Habito is a UK based startup that is the first to use Chatbots to address the Mortgage advisory/broker space. Habito’s Digital Mortgage Advisor (DMA) looks up details of a customer’s financial life (e.g. employment, salary and personal life plans) with real-time market mortgage rates to calculate an indicative monthly payment. The DMA explains the impact the customer’s decision will have on the mortgage numbers as a traditional mortgage broker would, but in a fraction of the time (average 10 minutes). Habito is founded by Daniel Hegarty, who was Wonga’s head of Product, and is backed by angels including Transferwise CEO Taavet Hinrikus, Funding Circle’s founder Samir Desai and Yuri Milner.

Better, a startup based out of New York led by Vishal Garg, have managed to address the broader mortgage process, right from advising them on the right mortgage option, using AI ofcourse, to funding the mortgage. They have hired the CTO of Spotify to help them with AI capabilities that would personalise the mortgages to the customer’s financial profile. Since their launch in 2014 they have managed to fund over $500 Million in Loans. Earlier this year Better raised $15 Million from Kleiner Penkins and Goldman Sachs that valued them at $220 Million.

"I'm sorry if some of the 'affordability' questions we're require to ask may seem inappropriate."

A JD Power survey earlier this year, found that 62 per cent of people under 35 who bought a home this year said they would use a mobile app for a mortgage application, if their lender provided it. The home buying process, which is meant to be a happy phase in life, often turns out to be traumatic, filled with uncertainties. We have seen some startup activity in the real estate/proptech space (Purple bricks in the UK), real estate transaction management (on Blockchain), and real estate valuations using IoT data monitoring. However, the major pain points in the mortgage process have been broadly overlooked.

Mortgage Pain

Better and Habito have managed to look at the Mortgage lending process and improved it through clever technology, processes and business model changes. Let’s look at a few example pain points within the traditional mortgage process.

Inefficiency #1: Customers looking to buy a property typically need to factor in a few weeks to get a letter of verification (called Agreement in Principle in the UK). This letter states how much the customer can borrow, at what rates and what the monthly payments would be. So if by chance a customer found a property that he would like to move quick on, he would generally be disadvantaged. Cash only customers always have an advantage in real estate transactions.

The Millenial Way: Better have approached this as a two stage process. The first stage where they get information from the customer, and tell them what products are available for them. This is done by proprietory AI algorithms similar to Spotify’s algorithms to provide personalized music. At the end of this process customers would have a verified pre-approval letter reviewed by an underwriter. Better claim this letter would be available in 24 hours from the time the customer has made the request. The second stage kicks in after the customer has found a property, where the mortgage economics revolves around the property.

Inefficiency #2: The process of choosing the lender involves a lot of variables, however, customers generally go with the lowest overall cost of the mortgage (including various fees, upfront monies and Monthly EMIs) for the best period. They often lack visibility and guidance on what would be better for them, a larger upfront deposit or a larger monthly EMI.


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The Millenial way: Better provide complete transparency in terms of what is good for a particular customer – a higher upfront payment, or higher monthly EMI. This would depend on how long the customer intends to live in the property chosen, which in turn would decide if the break even would occur within that period.

Habito takes an unbiased and a personalised approach to choosing mortgages depending on the customers profile. The AI behind it ensures that customers are at the heart of the mortgage recommendations.


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Inefficiency #3: Mortgages often come with various costs attached to them, which is primarily because there is a person behind the scene trying to sell and close the deal for the lender, and this person needs to get paid. Also, mortgage brokers often sell products that get them better commissions

The Millenial Way: Better mortgage has no hidden costs, and it is completely free of admin charges. Better employs staff who will unblock the mortgage process, and help people through it, rather than sales staff to close deals. Their loan officers never get paid commissions. That’s a much needed change.

Habito charges equivalent fees across all mortgages as AI algorithms don’t have vested interest (yet). This ensures the customer gets the best product suited for his needs, everytime.

Inefficiency #4: Mortgage lenders offer a rate, but very often during or just before the process of the application increase the rates. I know a few friends and colleagues affected by this completely unacceptable approach by Mortgage lenders.

The Millenial Way: Better mortgages offer full transparency throughout the mortgage process. The use of technology to hold all mortgage information centrally, and loan officers who are not incentivised to mis-sell products helps too.


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As a Better customer, you can stay on the mortgage process 24 X 7, all 365 days. If a customer wanted to progress quickly on a property over a weekend (day or night), unlike high street banks, they would be able to get the required approval letters. That truly feels like a Millenial way to Mortgages!!

AI is no human

These are some interesting stories of efficiencies being added to the Mortgage process and business model, through intelligent AI algorithms. However, I firmly believe AI cannot completely replace a human on a Mortgage or an Insurance conversation. If I were going through a home buying process, or an insurance claim for a car accident, I prefer to talk to a human who understands the emotions of the process and treats it with empathy. However, I believe AI can add efficiencies, make the process unbiased, and provide personalised insights through thousands of data points that the human brain can’t cope with. The human in this process will just need to be – humane.

The US mortgage industry is $8.4 Trillion in size, and the top four fintech firms offering mortgages do just about $1 Billion in funding. There is still a long way for these firms to go, but a ground up approach to mortgages, cool technologies, and of course a human touch throughout the process can definitely proivde a happier home buying experience for customers.

Arunkumar Krishnakumar is a Fintech thought-leader and an investor. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.

Fintech solutions to problems of #GAFA people


Happy New year to all. We are all #GAFA (Google Amazon Facebook Apple) people with different passports and IDs.

Our predictions “2017 Tech, Strategic, and Investment trends in WealthTech” are already out there for testing. In this first post of the year, I want to focus on a complicated topic that concerns all #GAFA people (and please stand out, if you are from another planet).

Personal data monetization is the GAFA business backbone and I foresee that in 2017 we will be hearing more about the ethics of monetizing our data in Fintech too.

I also have a wish list that includes seeing more Fintechs focused on “gating” our data, empowering us with a choice, and sharing subsequently revenues with us.

Three picks for a 2017 watch list

I picked three companies that are worth watching because they recongize our problems as #GAFA people and intend to help us.

A Telco

In September 2016, Spain’s Telefonica announced that in 2017 they will roll out a platform to enable their users to manage the use of their personal data from Google and Facebook and WhatsApp. Users will be able to block or require compensation through the OTT platform.

The Spanish carrier Telefonica is involved in many ways in the 4th industrial revolution. Telefonica owns a startup incubator based in the UK, Wayra, focused on digital business ventures since 2012 and offering the potential to access the 300million Telefónica customers globally.

Telefonica Germany (a subsidiary of the Spanish Telco) is launching O2 Bank, a digital bank, in partnership with Fidor Bank. This will allow German clients in a few minutes to open an O2 bank account (Fidor has the banking license which is valid all over Europe). The identity check will be done via a video on the customer’s smartphone. To transfer money, customers have to enter the mobile phone number of the recipient in the address book and select it for a transaction. The O2 Banking MasterCard can be activated or deactivated directly at any time via the app, and the card details can be presented for online shopping, without having the physical card in hand. A financial planning tool provides an overview of their spending and on request they can be notified in real-time of transactions and events by app push messages sent to their smartphone. Smaller consumer loans will be available directly via the app. O2 banking phone contract holders will “also benefit from a variety of perks and add-ons” when using O2 Banking, such as increased 3G or 4G data allowances (Source).  

In 2017 we all need to watch how the OTT platform that empowers users with the monetization of their personal data, will be combined with the O2 Banking services.

A true digital bank

September 2016 was also when SeccoAura started accepting registrations on their alternative way of monetizing personal data. SeccoAura launched in the fashion industry, allowing customers, to earn Tokens if other users “Like” what they are wearing. If “Likes” on SeccoAura lead to a “Buy”, then the SeccoAura customer who wore the “Liked” item, will earn a referral bonus. The concept could be applied to any retail purchase and wealth can be created through these tokens.

We covered the concepts behind this breakthrough business model in Secco Bank and the Future World of MyDigitalAssets.

A chatbot Fintech

Novastone Media is a UK-based tech firm in the space of information security (similar in a way to the space that Symphony, the Wall Street darling, operates in). Novastone Media’s financial services offerings are targeting private banks, financials advisors, robo-advisors, retail banking and corporate banking.

Solutions include secure messaging platforms that empower conversations, increase engagement, offer security and compliance accountability. Novastone Media prospect clients can choose to use their messaging, chatbot, WhatsApp-like solutions, in a more conventional way. That would result in simply offering finserv end-customers protection from #GAFA using personal data.

In 2017, we will be watching whether any Novastone Media finserv client will choose to monetize their customer data securely collected through these solutions and share revenue with the end users.

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Daily Fintech Advisers provides strategic consulting to organizations with business and investment interests in Fintech & operates the Fintech Genome P2P Knowledge Network. Efi Pylarinou is a Digital Wealth Management thought leader.

2017 Tech, Strategic, and Investment trends in WealthTech


Watson helped me write this post. I fed him all Daily Fintech posts from last year and all the conversations on the Fintech Genome and gave him access to all my Tweets, Quote Tweets and Replies (he said he couldn’t access my Linkedin interactions; are they gated?).

Paolo Sironi and Susan Visser, would welcome such a use-case of Watson’s capabilities; but for now it is only in my dreams that this happened which I dare to share with you today since it is “Charles Dickens season”. I don’t qualify as poor in the conventional social understanding but I am poor in cognitive tech resources for my Fintech thought leadership.

Last year in December we issued a Warning (just before the traditional year-end predictions)

The truncated message from the myth of Icarus, is that it is dangerous to fly high; but the forgotten message is more important for Wealth management: “It is equally dangerous to fly low”.

It is Not Safe anymore to continue “business as usual”. This is a Warning.

The warning is still very valid and the only clarification I’d like to add is that when we talk about “Wealth Management” don’t just think we are referring to services offered to mid to higher end clientele. This category extends to any level of “wealth creation” that can be derived from small amounts of conventional currency savings, or a low digital credit score. It also encompasses the Capital Markets infrastructure and the regulatory environment which sets the rules of the game of wealth creation at a wholesale level.

End-users continue to push the transformation boundaries. Fintech startups, incumbent institutions in financial services, Financial software vendors, Telcos, and Cloud service providers, are responding to this unstoppable trend. The old adage “If it aint broke, don’t fix it” isn’t anymore valid. The Icarus warning “It is equally dangerous to fly low” encapsulates the reality of our era that is breathing down our neck “Danger to become obsolete”.

For our smartphone readers, I am confining myself to an outline of themes in Wealth Management and Capital Markets for 2017:

The 2017 technology-led trends

  • AI and ML will be the technology that will be “a must have” shifting from “nice to have” and “transactional only”. AL and ML will be leading the movement towards Invisible and Contextual wealth management services. For those that have been investing in AI for many years and have yet to be compensated for being early; 2017 will provide them with great signs of relief. This era will be the AI& ML Walk and Talk starting 2017.
  • The macro environment will continue to be challenging and will result in a genuine shift in wealth creation. For years, it has been Buffet vs. Soros (fundamental vs. macro) and passive vs. active. 2017 will be the year that we will increasingly entrust wealth creation to AI & ML guided processes (mostly actively managing passive financial products (like ETFs) and customization towards goal-base investing).
  • 2017 will be the year that it becomes clear that an API offering will leapfrog a White Label offering. For those that have both and are agile, it will be work out very well.
  • 2017 will be the year that the ISDA agreements in the Swap market give way to Smart contracts.
  • There will be more digital wallets opened in 2017, than any other adaptation of a Fintech service (payment service, digital bank account, robo-advisor etc). Looking at new financial assets for 2017, there are two possibilities to consider. The P2P loans as part of our fixed income allocation and cryptocurrencies as part of either our FX exposure or to include in the commodities allocation or the inflation protection risk buckets. Both have significant regulatory hurdles to face, however, the rate of adaptation of these new assets (not yet recognized as such) will favor significantly cryptocurrencies. P2P loans as an new asset class will not gain significant traction in 2017.

The 2017 strategic trends

  • We will be seeing more of the “Sell-side empowers the Buy-side” shifts mainly out of the US.
  • We will be seeing more cross-selling innovations in wealth creation launched by the incumbents and partnerships of Fitnechs; the US and China will lead.
  • The Transparency movement in wealth management will pick up speed. 2017 will be about Transparency rather than Disintermediation, which became “out of vogue” already in 2016 with more collaboration between startups and incumbents than genuine disruptive moves.
  • 2017 will be the year that IBM, Microsoft, Amazon etc, the Big cloud computing providers will no longer be the Gorillas on the Fintech stage that go unnoticed.
  • 2017 will be the year that Asset managers wake-up and shift from asset-gathering mode and the traditional way of managing the entire investment cycle process. From all parts of the ecosystem they have been by far the laggards. Brokers have been the leaders on the transformation highway.
  • 2017 will also be the year that private bankers and independent Financial advisors are brought further up to speed. The incumbents for which private bankers work for and the affiliated incumbents that the IFAs collaborate with (for custody or execution etc) will empower them.
  • European regulators will continue to lead. PSD2 will influence all other continent regulatory thinking. The FCA will focus more on international collaborations. The Global Innovate Finance summit will become more of a genuine global summit.

The 2017 investment trends

In this part, I share my predictions and also pose a few questions (I don’t have the answers on their timing) because they are important considerations to keep in mind.

  • Alternative wealth creation in 2017 will only refer to what Secco bank is aiming at (i.e. create wealth from digital assets like reputation and monetizing our own data) and cryptocurrency investing.
  • In 2017 I will be writing more about emerging cryptocurrencies investment managers rather than Vanguard, Betterment, and Fidelity and their investment performance. In 2016, we only watched cryptocurrency exchanges and brokers.
  • The cash piles that are sitting around the world wont be reduced significantly in 2017, simply because those chasing them (from Fintechs to incumbents) are in their second phase of innovation and users (like myself) still have to consider three dozen apps to cover all financial needs from Fintechs.
  • The ICO unstoppable trend will continue but will remain predominantly for blockchain related ventures. In 2016, the first steps in shedding light in the very opaque private markets were taken (Title III in the US, ICOs, Stock exchange innovations for private companies to prepare their IPO). This trend will be slow in penetration but will continue with the East joining.
  • Will 2017 be the year for the huge market opportunity of Chinese robo-advisors to create and offer an investment portfolio that can truly match the risk profile and goals of the Asian end-users; rather than being constrained from the very limited local investment pallet?
  • Will 2017 be the year that we all start considering investments in the Goldmans’ or the Alibabas’ because of their strides in Fintech innovation? This I foresee, is two years down the road.

Have a great holiday, for all our readers taking a digital break starting this week.

Daily Fintech Advisers provides strategic consulting to organizations with business and investment interests in Fintech & operates the Fintech Genome P2P Knowledge Network. Efi Pylarinou is a Digital Wealth Management thought leader.

The agile ‘just in time’ AI powered CFO


According to an EY report, the average age globally for a newly minted CFO is 42. Unsurprisingly, they’re a highly educated bunch, with 27% of CFO’s surveyed having completed an MBA and 27% holding a chartered accountancy qualification.

Highly educated talent with years of experience usually doesn’t come cheap. And for small to medium businesses, this could mean forking out a salary in the range of $130,000 to $250,000 to land themselves a C-Suite financial executive.

So with CFO’s trading at premium, is there any way the knowledge, analytical brains and strategic insights a CFO possesses could be mass produced for less? For companies turning over between $1M to $5M per year, deep learning, big data and AI is quite possibly the answer.

Medical profession leads the way

We need not look far to see a similar story of knowledge democratisation at play – medicine. In late 2015, computing powerhouse IBM acquired Merge Healthcare, a medical imaging business with a collection of over 30 billion X-rays, CT and MRI scans. These images are ready fodder for it’s hungry AI protégé Watson. IBM plans on using the data, alongside other diagnostic indicators such as pathology results, genetic data and clinical studies, to train Watson to recognise diagnostic patterns and abnormalities.

The impact of these sorts of deep learning initiatives in the medical sector is huge. When presented with a patient in the future, in order to diagnose and treat, Watson will be able to call on a database of knowledge far wider than any medical professional alone. The era of Dr House could soon be eclipsed by that of Dr Watson – and it’s hard to see how patients stand to lose.

The ‘just in time’ CFO

The parallels to financial decision making in the business sector are evident. At any one point in time, to effectively manage an organisations financial health, CFO’s must monitor and then interpret a myriad of data points. Not only must they track internal financial metrics, but they are increasingly required to keep a steady pulse check on the wider financial markets, investor sentiment, and microeconomic indicators pertinent to their sector. With data often fragmented internally and externally – and shifting fast – decision making is a complex undertaking.

For small finance teams, such as those in small businesses, the problem is compounded by a lack of headcount. In many instances, the financials are only looked at in depth once or twice a year by an external accountant. That means, for the rest of the year, business owners are left to their own devices, often unaware or unable to comprehend looming financial mishaps, like cash flow shortages or inventory issues.

But, what if a business owner or lower level finance executive could tap into an online CFO, powered by a Watson engine, and obtain insights and recommendations in a heartbeat? An engine with access to numerous financial data sources in real time – internal and external – crunching the numbers and providing ‘just in time’ answers to company specific operational and strategic financial questions? This flexibility would help small business build financial agility into their operations in an affordable way, without the need to rely on static financial planning sessions or expensive advisors.

Watson powering sales efforts already

A great use case for Watson in the business world can be seen in RedAnt’s SellSmart, an offshoot of the the IBM Watson Ecosystem. Using the cognitive engine, the app addresses the pain point of sales staff struggling to keep up to date on ever increasing swathes of product knowledge. Responding to natural language questions, the app can promptly deliver the product information required for the sales member to assist the customer, improving the in store relationship and increasing the likelihood of closing the sale.

Financial data could be delivered in a similar way. Tomorrow’s small business CFO may very well sit within an iPad, and thanks to cognitive AI, might understand what business owners are trying to ask about the financial well being of their businesses, without them necessarily having to use complex technical financial jargon in order to get there.

CFO Watson might be able to:

  • Analyse sales across online competitors and advise what future inventory should be purchased to capitalise on market trends
  • Forecast and recommend various pricing strategies with respect to their impact on revenue and profit
  • Automatically redistribute cash across 2 or 3 term deposit accounts to maximise interest earned verses working capital on call.
  • Crunch weather patterns and advise the business to renegotiate an order placed with a supplier for summer stock
  • Pick up on consumer sentiment to target marketing spend and sales efforts more effectively

Today the concept of a small business ‘Virtual CFO’ is merely a case of outsourcing financial decision making to an accountant or financial expert. It still doesn’t replace the human at the end of the chain providing the advice and recommended actions after crunching the numbers and interpreting the reports.

Given the financial insights required by small business are significantly less complex than larger entities, utilising AI at the development stage it is at today is feasible. Overly engineered solutions for financial management are not required for this sector. But being able to translate financial data sets, trends and patterns into reliable and actionable insights is.

Daily Fintech Advisers provides strategic consulting to organizations with business and investment interests in Fintech. Jessica Ellerm is a thought leader specializing in Small Business.

On Monday, Daily Fintech will take a holiday for Easter. For the first time since we started in August 2014, there will not be a daily post. Fintech aficionados can still surf our archives of over 400 research notes.  

Riskgenius – the Google of Insurance Policies

By Rick Huckstep

In the world of commercial insurance, brokers and agents are reviewing policy agreements in their evenings and at weekends. These contract reviews are consuming masses of labor, are time consuming and open to error. This isn’t a small cost to the industry either. The 150 largest Independent Agents alone employ around 500,000 people with half of them in admin roles. There has to be a tech solution to this…let me introduce you to Risk Genius – the Google of insurance policies!

The issue is this. Insurance professionals across the world are struggling with contract reviews.  And this inefficient process is impacting underwriters, agents, and brokers alike.

The industry is full of anecdotes of professionals reviewing contracts at the weekend whilst they’re “watching” their kids at soccer school. Or of agents reviewing contracts for customers in their travel time between workplaces. And of product underwriters who simply do not have the time to review all of the contracts they are sent.

Let me put this into context with a simple Use Case

Today, commercial insurance brokers and agents need to review insurance policy agreements when advising clients on their insurance requirements. They do this by comparing different policy agreements and documenting the comparisons in a ‘like for like’ format in a spreadsheet format.

This is a manual review process. The agent or broker often does this as a side task, out of office hours, at home in the evenings or the weekend.

And here’s the rub. It’s a thankless task that is time consuming, repetitive, and open to human error. It also relies heavily on human decision-making in less than perfect circumstances. This is cause for concern for insurers from the associated risk and exposure of giving bad advice based on a poor contract review process.

This is where RiskGenius comes in.RGlogo_988p_Web_Mixed_Stacked

To tell me how they plan to transform the commercial P&C industry, I Skyped with co-founder and CEO, Chris Cheatham. Better known on social media as the ‘Dr Dre of the Insurance Industry”, Chris is an attorney by trade with a love of rap music, science fiction and machine learning technology. Chris has already established a successful startup in ClaimKit, a collaboration platform for claims management in the surety, insurance and legal space.

Over the course of an hour, Chris explained to me how he and his co-founder, Dan Burchett designed and built a platform that applies machine learning to the review process for commercial insurance policies.

“Its been a tough nut to crack and taken a lot of hard work and effort”, according to Chris, who gives all the credit for the technology solution to Dan, who’s more Tony Stark than your typical CTO.

What we do is take an insurance policy and load it up onto the RiskGenius platform. First, it is analyzed and indexed, which takes a minute or two. We’ve written algorithms that can break down and understand an insurance policy. And, just like Google, RiskGenius will look at the content, organize it and make sense of it. We use the algorithms to categorize and structure the content of the policy documents so that they can be reviewed. The output is a simple to understand and review policy, and the user can export out results in a spreadsheet format.

“We’re going through the same process as the agents. It’s just that RiskGenius is reading the text faster and applying more rules using machine learning technology.”

The purpose of RiskGenius is really clear. This is a solution that benefits the Insurance agencies.

As Chris told me, “a key challenge for insurance agents is sales. How do they go get business in a competitive marketplace?  RiskGenius is their best tool for fixing this. First, we take the pre-existing policy. By reviewing it with others, the agent can see the gaps in the cover and the weaknesses in the policy conditions. Now, the agent can explain these gaps and help the commercial client to get the right cover for their commercial business. Up until now, this has been time consuming. But with RiskGenius, the sales agent can process the policy very quickly and then go and explain any shortcomings.”

And this is not the end of it, because once a contract has been indexed and cataloged then the fun starts. Now agencies and brokers can start to build libraries of policy agreements across their client base and within the firm. It is common for many variations in policy wording for the same terms and conditions. These are often unnoticed and hard to review in their entirety across the firm. With RiskGenius, agents can comment on and review multiple variations of similar clauses with clients and with the agency to establish the most favorable for all parties.


RiskGenius is about to go live in February and this week they secured $1.8 million in series A fund raising from lead investor Flyover Capital (reported here on Startland News, Kansas City’s Home for Innovation News).

The approach they take will significantly increase the speed, consistency and accuracy of the contract review process.

Quite simply, RiskGenius are using technology as an alternative to hard labor and in so doing; they reduce the contract review process completion time from days to minutes.

As Chris says, “Can you imagine why anyone would manually review contracts in 5 years time?”

The author, Rick Huckstep is an InsurTech thought leader. Daily Fintech Advisers provide strategic consulting to organizations with business and investment interests in Fintech.