If you’re the head of underwriting, you don’t need anyone to tell you that the skies are stormy for your industry.
Times have changed since you began working at an insurance firm. Ten years ago, developing strong pricing looked different than it does today. You could rely on general pricing trends and market cycles. But now that’s changed.
Since 2008, massive changes have swept across the insurance industry. Pricing decisions now require more targeted and segmented data. Your job now demands that you get your pricing down to a science for one simple reason—the onus is now on you to generate revenue and profits in an increasingly sophisticated market.
In addition to these challenges, you are facing new competitors in the insurance industry.
Your traditional competitors are exploiting their technological prowess to enter your market with a definite edge. We know of one company that joined the technological momentum and lowered their loss ratio by 17%. With laser-focused data and analytics, companies like this are achieving sophisticated risk selection and are leaving the riskier policies for your firm.
Retiring before you have to implement sweeping technological changes is no longer feasible. And as you watch numerous policies go upside down, you’re wondering how much more pain—and pressure—you can take.
The good news is that there is an answer for your problems. The key to survival in today’s new environment is strong pricing.
You can evaluate how strong your pricing is. Click here to take the Assessment
Pricing Assessment: http://training.valen.com/assessment/
Strong Pricing: Your Opportunity to Make More Money
Strong pricing represents the only opportunity you have to increase your underwriting profit and lower your loss ratio. It’s the only thing that will keep you from suffering from adverse selection.
Everything else involved in your role is an expense. Once a potential policyholder has signed that contract, you are obligated to fulfill your promise and accept his or her liability.
You’re locked into an agreement that was made on limited knowledge. There’s a severe data gap between what your policyholders know about their risk and what you know.
To top it off, it’s an agreement you can’t drastically change with new information. You must have all the information you need upfront to create strong pricing.
Other industries have the ability to adapt their actions to changing forces. If an IT company releases a flawed version of software, the answer is simple. The company creates an updated version based on the new information it’s received.
In the insurance industry, the best opportunity to get it right is the first time.
As a result, you must rely on as much data as you can obtain. And even though your underwriters’ discretionary pricing has been informed by actuaries, these aggregated rates still allow you to lose more.
Your underwriters have to make individual judgments on each policy that comes their way. And where specific data doesn’t inform decisions, you’ll often find your underwriters rely on a big-bucket approach.
The fact is that your revenue (or the lack thereof) is generated on a much more granular level. You’re making and losing money policy by policy.
If you think that you are losing money because of an “irrational market” or the changing legal/statutory environment, you are misdiagnosing your problem of adverse risk selection.
To solve this problem and find accurate pricing, you’re going to need much more specific data than your actuaries can provide. You need a narrower focus.
In short, your job demands that you help your underwriters find strong pricing for each policy through predictive analytics built on solid data.
Strong Pricing: 3 Reasons Insurers Lack It
Not every insurance company relies on predictive analytics fueled by strong inputs. In fact, many insurance companies have a flawed approach to strong pricing.
To see if your firm has a faulty approach to predictive analytics, evaluate the strength of your pricing tactics. Click to take Free Assessment.
Here are 3 scenarios that might describe the situation at your firm.
- You’re solely relying on the instincts of your underwriters.
Your underwriters do have a massive amount of experience and expertise. But if you do not support them with predictive analytics, they will rely on something else much less accurate: their biases.
Biases contain your underwriters’ experiences and can help them steer clear of risky policies. However, biases can lead to neglecting policies that are profitable.
If a team member once underwrote a construction firm, only to absorb significant liability because of the general contractor’s negligence, he or she will likely avoid other similar businesses. Not all construction companies are equal, and there are a number of variables that determine a policy’s profitability.
If your underwriter doesn’t have access to specific, easy-to-use data, you stand to lose a significant amount of money by selecting a risky policy or rejecting a profitable one. In the end, your underwriter needs the support of predictive analytics. In fact, we’ve done a study that reveals the best pricing occurs when you combine predictive models with underwriter expertise.
- Your underwriters don’t have a user-friendly predictive modeling tool.
Sadly, many predictive modeling tools simply aren’t designed for your underwriter. If you’ve integrated predictive modeling into your firm, you may think you’re ahead of the curve.
The real question is this: Can your underwriters use the tools you give them?
Unless you provide a user-friendly interface, you’ll never tap into your valuable statistics. To see if your firm falls into this category, here are some questions to ask:
- Are predictive analytics delivered in a usable format? If your underwriter has to deconstruct an Excel spreadsheet to understand how to price a policy, your underwriter will have a difficult time implementing the new model of decision-making.
- Does predictive analytics provide real-time decision support? If your underwriters can’t access the data they need when they need it, then you may miss valuable opportunities.
- You lack strong data.
This third reason might be the most subtle of the reasons you lack strong pricing.
Even if you have a predictive, and usable, model for your underwriter, that doesn’t guarantee accurately adjusted premiums. The inputs for your predictive model may be based on faulty data.
For one, your data may lack the breadth needed to draw accurate conclusions. But there’s also another danger.
Insurers suffer from self-selection bias. Your firm probably has a tendency to insure a certain type of policy holder more frequently than another. And when you gather data from this pool, you deal strong pricing a staggering blow.
Your underwriters base their decisions on data from your company—not the data that describes the characteristics of policyholders across the nation. Unless a policy comes from the same category as the policies you’ve sampled, you have a shaky foundation for an accurate premium.
Strong Pricing: Your Solution
If you suspect your firm has a shaky or ineffective pricing strategy, you can take steps now to remove the obstacle that stands between you and strong pricing.
Evaluate your pricing practices with the How Strong Is Your Pricing? Assessment. You’ll gain valuable information that reveals how your practices and strategies are either strengthening or weakening your underwriting.
After you complete the assessment, you’ll be given a score report. Your score will help you see where your organization falls on the strong pricing spectrum.
Don’t rely on ineffective generalizations to explain your increasing loss ratio. Assess your firm’s pricing, and get specific with your organization’s needs. Click here to take Free Assessment.