The Business of Data Podcast Business of Data by Corinium

Rapid advances in data-driven technology and a precipitous rise in catastrophic flood events in the US presented an opportunity for this InsureTech startup
There are 62 Million homes at moderate or extreme risk of flooding in the US, according to insurance risk assessment firm Verisk.

Homeowners insurance does not typically cover flood damage and up to 50% of homes in high-risk areas have no flood insurance at all. This amounts to a serious problem, argues the founder of InsureTech startup Neptune Flood Insurance Jim Albert in this week’s episode of the Business of Data Podcast.

In the past, most flood insurance in the US was provided by the National Flood Insurance Program (NFIP). Now, powered by innovative technologies, nimble insurgent companies are shaking up the status quo.

“The NFIP has done an exceptional job over the years, but as with most government programs, technology has started to outstrip what has happened within the flood space,” says Albert. “And so, what I tried to create with Neptune when I founded it in 2016 was an ‘Amazon-like’ buying experience in flood insurance.”

“You can get one-click buying for virtually everything else you do in life,” he continues. “So, we tried to make it easy to buy flood insurance in the US through the use of data analytics and a really simple online quoting platform.”

The game-changing, automated approach championed by Neptune Flood Insurance was not without its skeptics. In 2016 when the company was founded, the idea of digital insurance was even more revolutionary than it is today.

“There was a lot of skepticism about digital insurance [back then]. Could a digital model actually replace the traditional back room full of underwriters?” Albert recalls. “[Especially] when I explained that we don’t have any underwriters. In fact, the underwriter is the computer.”

What sets Neptune Flood Insurance apart from its competition is the speed that customers can get a quote and buy their flood insurance online.

We’ve proved in the model at this point,” Albert says. “We pull in about a hundred different data elements in one second when you enter the address, and we do the full evaluation right then and there.

The application of this technology could not be timelier. Not only are flood events likely to occur more often in the US, but due to the pandemic no-one wants to have an inspector in their home, nor to wait weeks for an estimate.

Do [customers] want to sign on to a days or weeks-long slog to finally get the information that they need?” Albert concludes. “Or [do they] want to go to one site that has seemingly all the information with a really good price and great coverage options? That’s what we see happening.”

Key Takeaways

Many homes at high risk of flooding in the US are uninsured. A lack of awareness of the risks is one cause, but catastrophic damage can take years to recover from
Data has paved the way for a better solution.  By pulling together data from a multitude of sources, Neptune Flood Insurance can provide a policy in seconds
Hyper-personalization is on the way. Other types of insurance companies will soon take advantage of advanced, data-driven technology to provide highly personalized policies to their customers

The best way for companies to provide premium experiences to their customers is a cloud-enabled platform, argues USAA Assistant Vice President and Head of Information Management for P&C Allen Crane in this week’s podcast
USAA Assistant Vice President and Head of Information Management for P&C Allen Crane has a simple message for those companies yet to begin their cloud transformation journey. Start now.

The USAA built their cloud infrastructure from the ground up to provide services with the ‘wow’ factor, as Crane explains in this week’s episode of the Business of Data podcast.

However, cloud transformation initiatives are complex, challenging and require careful planning. A process that Crane compares to a pilot building an aeroplane in flight.

“We’re building a new plane in the sky that has to fly higher and faster than the one we’re already in,” Crane says. “And once we get that other plane flying, we have got to get all of the passengers off this plane and onto the new plane while it’s still in the air.”

In addition, Crane says, it is essential to obtain the support of senior leadership for such a long and complex transition to be a success.

“The most important thing in my mind is that the support starts at the top,” Crane says. “If you don’t have that level of support from the top you really won’t be successful.  You can’t do something at this scale at the grass-roots level.”

Companies must be able to provide their customers with premium experiences to remain competitive, argues Crane. Cloud transformation is an essential first step to achieving this.

“The world is moving to the cloud. Your user experiences will be enabled by the cloud. Machine learning and AI and all of that will be dependent on the cloud to deliver the kind of expectations that you want to deliver for you customers,” emphasizes Crane. “The sooner you get there the better off you will be.”

Key Takeaways

Plan the transition carefully. Migration to the cloud requires a retooling of the foundations of your data infrastructure
Win the support of senior leadership. Long and complex cloud transformation initiatives require the support of those at the top to be a success
Get started early. The sooner your company starts the cloud transformation journey, the sooner your customers will reap the benefits

Sherene Jose, VP and Chief of Staff, Cyber and Intelligence Solutions at Mastercard explains how they reimagined their fraud detection teams as revenue-generating innovation machines
You might not have heard of Mastercard’s cyber and intelligence solutions team, but you have probably used their technology.
Chip and PIN, contactless payments and even biometric-secured purchases are all part of the growing arsenal of payment solutions they oversee at the financial services giant.
In fact, creating innovative ways to make shopping safer and easier for their customers the team’s core purpose, explains Mastercard VP Chief of Staff Cyber and Intelligence Solutions Sherene Jose in this week’s episode of the Business of Data podcast.
“Theoretically, the best way to achieve zero fraud loss is to just reject every transaction, right?” quips Jose. “[To prevent that] we have to intelligently find ways to navigate the consumer experience and minimize any security risks.”
The Birth of Cyber and Intelligence Solutions at Mastercard
Prior to 2014, Mastercard had fraud detection and management teams dotted around the business. These decentralized teams were primarily seen as a function of cost control, designed to minimize fraud losses for customers.
Then came the big idea: Consolidate these departments with external expertise and create a new, revenue-generating cyber intelligence unit for the business. This unit is now responsible for protecting Mastercard’s payment ecosystem from fraud, creating innovative solutions for its customers and differentiating their core offerings.
Of course, patching together a newly conceived cyber intelligence unit from a combination of disparate teams and newly acquired startups is easier said than done.
“There was an evolution where teams working in specific verticals of authentication and fraud management and so on learned to come together and think across different verticals,” says Jose. “I could immediately sense the excitement, the sense that things are possible because of this paradigm shift. That mood continues to this day.”
Now, the cyber and intelligence solutions unit is at the forefront of innovation and fraud prevention for the company. In the first eight months of last year alone, their AI-powered cybersecurity system ‘Safety Net’ blocked over $113 Million USD in fraudulent transactions in the US.
Innovating Payments While Maintaining Customer Security
The uptake of technologies like contactless payments, spearheaded at Mastercard by Jose’s team, has skyrocketed during the pandemic. For Jose, the goal is to continue to create seamless and safe ways for their customers to shop, whether that’s online or in-store.
“An example of this would be digital wallets, right? You don’t have to key in your password or your PIN to just go ahead and [make] transactions,” she explains. “That’s the kind of seamless experience that we are trying to recreate in every channel.”
To do this, it is vital that Jose’s team understands rapidly changing customer needs. By leveraging data and analytics, they are able to build a more complete picture to work from as they create highly secure and innovative payment solutions.
“Mastercard as an organization has a very conservative and consumer-centric approach to data and analytics,” she explains. “We never want to store any personally identifiable data. The insights that we get from data in aggregate is what powers our solutions.”
“What is top of mind for us is how do we keep our ecosystem safe and how do we keep our stakeholders safe in this environment?” she concludes. “There’s a lot more that we can do and we’re working hard towards it by leveraging the power of data and analytics.”
Key Takeaways
• Fraud management need not only be a ‘cost’. By leveraging their expertise, fraud teams can be turned into

Di Mayze: WPP’s Community-Led Approach to Data and Analytics

Lisa Allen, Head of Data and Analytical Services at UK mapping agency Ordnance Survey, reveals how its data is helping the government respond to COVID-19

Ordnance Survey, Great Britain’s state-owned mapping agency, has a data culture that stretches back to its founding nearly 230 years ago. It supplies geospatial data and services to hundreds of customers from insurance companies to the police and local councils.

Innovation and data science are at the heart of everything Ordnance Survey does, as Ordnance Survey Head of Data and Analytical Services Lisa Allen says in this week’s episode of the Business of Data podcast.

“We manage one of the key national data assets for Great Britain,” Allen says. “The original purpose of [Ordnance Survey] was to collect [data] for cartographic purposes. But actually, now we want it to for analytical purposes.”

“The [Ordnance] Survey has been supplying data during the outbreak and we’ve been in great demand,” she continues. “We’ve really seen [the agency] come into its own.”

The Data Informing the UK’s COVID-19 Response
Thanks to its long heritage, Ordnance Survey boasts a world-class approach to geospatial data science. Its data stores contain more than 500 million geographical features and are updated 20,000 times a day.

Keeping such a crucial dataset up to date a huge responsibility and requires close collaboration between data scientists and surveyors, as well as the use of third-party data and machine learning techniques.

The events of 2020 have underscored how vital this work is. Thanks to the data at its fingertips, Ordnance Survey has been able to provide the British government with data and insights throughout the pandemic.

“COVID-19 has really shown the importance of data,” Allen remarks. “This epidemic is about, ‘Where are the outbreaks?’ And all the information you need to know is based on location.”

“What I’ve really seen during the epidemic is the OS come into its own,” she adds. “We’ve been asked questions about our mapping. We’ve been asked, ‘Where are the care homes? Where are the supermarkets? Where are the GP surgeries?’”

Lisa Allen, Head of Data and Analytics Services, Ordnance Survey“During an emergency we’re available 24 hours a day, every day of the year at no cost”

Ordnance Survey has a contract with the British government that sees it provide geospatial data and location data to public services organizations. It also provides services ranging from providing basic maps and identifying ‘points of interest’ on them to data matching.

“This is especially important for things like addressing,” says Allen. “So, during the pandemic, making sure the letters went out to the vulnerable [and] making sure those addresses were right.”

Following the news that the British government has become the first to authorize a COVID-19 vaccine for use, an end to the pandemic may be on the horizon. But the Ordnance Survey’s work is far from over. The agency will continue providing world-class data-driven services long after the crisis is over, just as it has for hundreds of years.

Meena Thanikachalam, Head of Data Architecture at Ally Bank explains how building a world-class data platform in the cloud will transform the customer experience and build loyalty

Traditional high-street banks were not at the forefront of the digital revolution. However, customers today demand instant access to high-quality digital experiences – a trend that has only been accelerated by the pandemic.

Banks must use their data to develop a better understanding of their customers’ needs, argues Meena Thanikachalam, Head of Data Architecture at online bank Ally in this week’s episode of the Business of Data podcast.

Thanikachalam heads up the team responsible for creating an innovative cloud-based data and analytics platform for the bank that is designed specifically with the customer experience in mind.

“We are building a world-class data platform that will help improve our customer experience,” says Thanikachalam. “And will also help deepen our customer relationships and increase customer loyalty.”

A core element of this customer relationship is to create an experience for the customer which feels bespoke. That is why Ally Bank have done the work to understand what their customers need and when they need it.

“This platform is also looking at integrating omni-channel data and also data that we have collected about customer preferences,” she says. “Based on that we would provide a targeted and personalized experience for them.”

Ally Bank is also using AI initiatives like cognitive computing and conversational AI to further enrich the customer experience and enable customers to do more without needing to speak to an agent.

“In banking specifically, cognitive computing is used predominantly to have human-like conversations,” Thanikachalam says. “That is one area [in banking] where I see AI penetrating a lot.”

Key Takeaways

Develop a 360-degree view of the customer. Understanding what your customer needs and when they need it will help you shape your strategy.
Write the data strategy to inform the customer experience. Identify what data is needed and which metrics will most effectively influence the customer.
Don’t forget the guiding principles. Scalability, reliability, performance efficiency, and operational excellence should guide your architectural work.