Straight-Through Processing Helps Bolster Insurer Data Quality, Client Intelligence

With the continued turmoil in the financial marketplace, many insurance carriers are challenged to maintain profitability and identify opportunities for continued growth. And while yesterday's growth was driven primarily by volume, tomorrow's growth seems destined to lay with the carrier's ability to streamline business processes, leverage technologies to reduce operating costs and offer first-rate service to improve customer retention and loyalty.

Straight-through processing–better known as STP–is a term long associated with the financial services and securities industries. Utilizing workflow and business process technologies, STP is an initiative used to optimize the speed at which transactions are processed, allowing the seamless and accurate transactional exchange of information electronically, with little need for human intervention.

It is becoming evident with the advent of service-oriented architecture and Web technologies that STP will begin to play a larger and more prominent role in process transformation at insurance carriers.

Significant automation reforms are underway worldwide at insurance carriers large and small that seek to make the underwriting process less error-prone, and more productive, cost-effective and customer-responsive.

Carriers are trying to reform legacy processes and replace outdated technologies for several reasons:

o Declining quote-to-bind ratios indicate that they are hemorrhaging customers to more agile, customer-responsive competitors.

o Underwriting bottlenecks damage agent and underwriter productivity and drive up costs.

o Too much paper and too many hand-offs are already hindering a painfully slow process.

o A shortage of underwriting and claims personnel is expected as the baby boomer generation retires and takes their years of knowledge, experience and business-savvy with them.

It is no surprise that the underwriting process (for most carriers) continues to be rife with both inefficiencies and the potential for error. Consider the following systemic challenges:

o Inaccurate or incomplete data is bounced from customer to agent to underwriter and back.

o Lack of automation necessitates time-wasting manual interventions and multiple hand-offs.

o Siloed information and IT systems render some information all but inaccessible and demand that data be manually re-keyed.

o Inappropriate geographical benchmarks, such as ZIP codes, generate inaccurate data.

o Paper plagues the system, and manual intervention drives down efficiency and forces up costs.

For reforms to succeed, carriers need tools and strategies to streamline policy underwriting processes, improve the accuracy and consistency of critical information and enhance profitability.

They must create a new process workflow utilizing best practices that are driven by improved data quality, customer intelligence and location intelligence.

This will improve their ability to assess, manage and execute the selection and pricing of risk from the transactional level to the business portfolio level.

Among the problem areas that need to be addressed are:

o Data Quality: This has proven over the years to be the major reason for the success (or failure) of most key strategic solutions–whether they be customer relationship management, enterprise resource planning or enterprise application integration. These systems depend on accurate, reliable data to deliver true benefits across the enterprise.

Leading insurance companies are finding ways to integrate data into business processes, and in some cases, automate decisions with on-demand business analytics.

New tools include event-driven data platforms that capture business events in real-time, aggregate intelligence, apply rules, and even trigger queries when predefined thresholds have been reached.

o Customer Intelligence: This involves the process of gathering and analyzing information regarding customers, their details and their activities, that result in a deeper and more effective customer relationship.

Customer intelligence begins with reference data–basic key facts about the customer, including their geographical information. This is then supplemented with transactional data–reports of customer activity such as quotes, claims or customer service inquiries.

Newer technologies such as address matching and geo-coding correct, clean and standardize addresses. Geo-coding uses meaningful and highly precise geographic data–down to latitude and longitude–to more accurately determine the exact physical location of each address for territory assignment and precision pricing.

After all, ZIP codes are optimized for the delivery of mail–not for determining risk criteria.

o Location Intelligence:This is about the capacity to organize and understand complex phenomena through the use of geographic relationships inherent in all information. By combining geographic- and location-related data with other business data, organizations can gain critical insights, make better decisions and optimize important processes and applications.

Location intelligence technologies offer organizations opportunities to streamline their business processes and customer relationships to improve performance and results.

The ability to take a specific location and drill down using more exact geographic information allows insurers to more accurately assess risk assignment factors, such as the boundaries of flood zones, distances to the coastline and property location relative to earthquake fault lines, wind pools, sink holes and other higher-risk areas.

In the underwriting process, the returned values from such an analysis can also determine whether the policy application should be escalated to a supervising underwriter.

Take state premium tax as an example.

Many states now require insurers to pay a tax on insurance premiums that are written in specific jurisdictions in that state. Each year, the boundaries of these premium tax districts change, which results in residents being under/overcharged for premium taxes–or, in some cases, being charged for taxes when their address did not fall into a designated tax jurisdiction at all.

New geo-spatial technologies now automate the process to enable insurance carriers to correctly identify and append the correct state, county, township municipality and premium tax district information to each customer record. This means more accurate results, minimizing audit risk, eliminating fines and boosting customer satisfaction.

Today's location intelligence technology is enabling insurers to better identify and manage risk–not just in underwriting but in almost every business area of insurance.

Whether it is claims management, product development or marketing effectiveness, many carriers are now integrating location intelligence across the enterprise and reaping the rewards of greater efficiency, lower costs and, most importantly, the ability to better manage and control risk.

Automating the underwriting processes represents a critical step as carriers face mounting pressure to move faster and more efficiently in their underwriting operations to capture new revenue, as well as to improve profitability, operational efficiency and customer satisfaction.

In an era of higher costs, consumer empowerment and policyholder churn, insurance carriers must be more swift and responsive to customers, improve data accuracy and integrity, and drive unnecessary costs and manual activities out of underwriting processes.

Bill Sinn is Strategic Industry & Marketing Director at Pitney Bowes Business Insight in Philadelphia. He may be reached at Bill.Sinn@pb.com.