Tag Archives: big data analytics

As IoT Expands, Risks Grow Even Faster

Get used to it. The Internet of Things is here to stay. In fact, IoT is on a fast track to make all manner of clever conveniences part of everyday commerce and culture by the close of this decade.

Tech research firm Gartner estimates IoT endpoints will grow at a breakneck 32% compounded annual growth rate over the next few years, reaching an installed base of 20.8 billion IoT units by 2020.

See also: Insurance and the Internet of Things  

Tiny, single-purpose sensors designed to collect rich profile data on individual behaviors — as well as on company systems — can already be found in all manner of medical devices, automobiles, TVs, gaming consoles, webcams, thermostats, utility meters, household appliances, manufacturing settings and wearable tech. Much more is coming.

It is incumbent upon the businesses that deliver both the IoT devices — and the new internet-connected services that IoT sensors make possible — to address the security exposures that are part and parcel of this rapid scale-up. Fortunately, cybersecurity vendors are stepping up innovation to do just that. Gartner projects that worldwide spending on IoT security will reach $348 million in 2016 — up 24% from 2015 spending — and will climb steadily to $840 million by 2020.

I recently sat down with Johnnie Konstantas, director of security solutions at Gigamon, a supplier of network visibility technology, to discuss what’s on the horizon. The following text has been edited for clarity and length.

3C: What is the core security challenge accompanying our rapid deployment of billions of IoT sensors?

Konstantas: IoT sensors are quite small and pretty cheap, too, and they don’t have a lot of memory on them. Their whole point is to store a little bit of information and then just forward it on to the cloud. If you think about how we traditionally use things like encryption and a firewall to secure a mobile phone or laptop, that’s very hard to do on a small IoT sensor.

So what you have is a conduit into the corporate network deployed for the purpose of receiving intelligence, and you can’t really push perimeter protection out to these IoT devices.

There’s no question IoT sensors can potentially be a way in. The IoT endpoint could get infected with malware, or it could be used as a lily pad to jump in deeper.

3C: What defensive approaches look promising?

Konstantas: A lot of it comes down to continuous monitoring. These devices are going to always be on, transmitting intelligence. The idea is to continuously understand what the IoT device is forwarding or receiving 24/7. Sounds like a tall order, but doing that allows you to essentially perform analytics on IoT-generated traffic. And with the proper kinds of security analytics in place, you will be able to surface anomalies.

See also: How the ‘Internet of Things’ Affects Strategic Planning  

3C: Sounds like big data analytics with an IoT twist.

Konstantas: Yeah, exactly. Big data analytics is nothing new. Security analytics is nothing new. But both are actually seeing a resurgence. Call it SIEM (security and information event management) 2.0 for lack of a better word. This time, SIEM is not so much about collecting large volumes of data; it’s more about getting the right kinds of data. It’s about pruning my data feeds to figure out whether I have any risks associated with my IoT deployments.

3C: What key developments are on the horizon?

Konstantas: I’ve been in security since ’98, so I’ve seen a few patterns play out. The one constant has been that when cool technology emerges — like our ability to do commerce on the web or virtualized storage and computing — adoption tends to be a lot faster than the arrival of the technology to secure it. So it’s fair to say that our desire to take advantage of sensor networks and IoT is going to outpace our ability to roll out security infrastructure to secure them as well.

More stories related to the Internet of Things:
Technological armor evolves to keep IoT devices safe from attack
Ripples from Internet of Things create sea change for security, liability
Consumers should brace for home network intrusions in 2016

This post originally appeared on ThirdCertainty.

Data Analytics Comes of Age for Agents

Sitting down for lunch with one of our top independent agents, I asked him about his business.  

“Things are great – we’re totally paperless now!” he responded triumphantly.

“So what are you doing with all of the data you’re collecting?” I asked.

“Oh, I’m too small to do any of that stuff,” he said with a shrug.

“You’re not,” I said. “In fact, it’s a powerful way for you to generate more business. Let me show you how….”

“Data analytics” sounds like rocket science—sophisticated, expensive, intimidating and beyond the reach of the typical independent agency. It isn't. Data analytics is simply the analysis of data that allows a person to make a better decision than they could without data.

The challenge occurs when there is so much data available that it becomes difficult to determine what information is relevant and what is not. It becomes even harder when the data is not stored in a way that can be easily analyzed.

Today’s technology allows people to analyze huge amounts of data in whatever form. Sophisticated software can identify patterns and relationships between millions of pieces of information that provide better insight into a subject. This is commonly referred to as “big data” analytics.

Don't get overwhelmed by these terms or the complexity of the algorithms used to analyze data. Just remember that the objective is to use data so you and your agency can make better decisions. Here are the key steps to improve your agency's performance:

Step 1:  Understand what you have

Your agency contains a treasure trove of information about your existing clients and potential customers.

Before you can even begin to run a data analytics program, spend time understanding the data you already collect. Start by creating a spreadsheet with all of the data you collect when you onboard a new client — for example, birthdate, home and work address.

Add information you collect as part of the underwriting process. For example, if you write a BOP policy for a client, capture all the additional data an insurer needs to evaluate the risk — the number of employees, store locations and industry.

When this spreadsheet is completed, you will discover the sheer volume of data you already collect about your clients.

Step 2: Understand what you want

Who are my most profitable clients? Are clients more profitable if I write both their commercial and personal lines insurance? How many policies per household do I need to maintain a high retention rate? How can I best target new clients? What type of people are my best referral sources? What marketing programs generate the best leads?

If you think you know the answer to these questions because you've asked them yourself, think again. Most agency owners base their answer on individual experience. That's no longer good enough. Insurance sales and marketing has transformed from an art to a science.

While the data you collect is extremely valuable, data analytics tools also allow you to incorporate outside data into your analysis. What information would you like to have about an existing client or a potential customer? What information would you like to know about a certain area or region?

Identify your “data gaps” — information you don't have but would like to have about a client or a prospect. This might include their net worth, whether they own another home or their business affiliations.  Consider any information you would like to have about a specific geographic area or other external information that would be helpful in allowing you to attract and retain clients.

Capturing all of this additional “outside” data is beyond the capability of any individual agency. But today there are companies that do just that. Find one that offers subscription- or transaction-based solutions, with little or no start-up costs, that are easily accessible by using their secure website. Find a platform you can use any time to plug in or access the data you want.

The data relationships that you build will allow you to create a strategic advantage. Stay away from cookie-cutter solutions that just provide “answers” to data questions. They don't allow you to differentiate the results of the data analysis.

Step 3: Put the data to work

Does your agency management system have a data analytics feature or tool? If it does, subscribe to it. If it doesn’t, demand that the vendor offer such a tool.

If your agency management system doesn't have a data analytics tool, reach out to the insurance company you write a lot of business with and ask if you can partner with them on a data analytics project. Offer to share your information if they will analyze your book of business. Make sure you play a key role in defining the data to be analyzed, and most importantly make sure you define the hypothesis or data relationship you are looking to uncover.

Take action

Today, customer acquisition and retention takes place in real time, or close to it. The more information you have about current and potential customers, the better you will be able to address their needs when and where they want it. That's why you need to embrace data analytics — it gives you the information you need, when you need it.

If you are like most agencies, you’ve already done the hard part by getting rid of your paper files and moving to an electronic agency management system platform. Now you need to start using your data.  You have a great opportunity to become a sophisticated marketer and drive better performance and growth out of your agency.

What are you waiting for?