Overview:
As per the Wikipedia, Insurance is a form of risk management primarily used to hedge against the risk of a contingent, uncertain loss. Insurance is defined as the equitable transfer of the risk of a loss, from one entity to another, in exchange for payment. An insurer is a company selling the insurance; the insured, or policyholder, is the person or entity buying the insurance policy. The amount to be charged for a certain amount of insurance coverage is called the premium. Risk management, the practice of appraising and controlling risk, has evolved as a discrete field of study and practice.
The transaction involves the insured assuming a guaranteed and known relatively small loss in the form of payment to the insurer in exchange for the insurer’s promise to compensate (indemnify) the insured in the case of a financial (personal) loss. The insured receives a contract, called the insurance policy, which details the conditions and circumstances under which the insured will be financially compensated.
The below figures shows how IT could be bundled in each of the insurance companies’ processes. At every level we can bundle some key IT modules that definitely will increase the efficiency of overall insurance engine.
1.0 Challenges in Insurance Industry from an IT standpoint :
In Insurance industry companies have grown continuously, through merger and acquisitions. In this process they have amassed a legacy environment that is crowded with disparate and disjointed applications and infrastructure. The business model of Insurance companies (most of which are organized around a product line like life, health, personal, commercial etc.) discourages the consolidation of IT systems and business processes. This results in duplicate costs and inefficiency for the company.
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Insurance companies require a robust, flexible and scalable modern IT system to compete in the highly competitive market. But they are faced with a host of technology challenges like legacy systems modernization and replacement. An average corporation spends 90 per cent of its software budget on legacy system maintenance and so there is little left for new software development and IT-enabled business innovation which is actually the need for the hour.
There was no clear enterprise solution for Insurance- no ERP system available! The third party software was a point system to launch a single product only. This has resulted in a complex, cobbled together mix of aging systems, preventing any new offerings from IT.
1.1 Challenges to legacy system modernization
1. Lack of documentation – Systems are so old that there are no longer any support documents
2. Use of Multiple technologies to write legacy systems prevents easy fit into an enterprise architecture plan
3. Lack of master data management makes it difficult and costly to move to a single platform
4. Staff have not kept pace with the changing technology
All these challenges make it impossible to replace the legacy systems. On the other hand modernization will reduce maintenance, support, up gradation and infrastructure costs.
1.2 Challenges in eliciting data from the legacy system for Business intelligence
The four pillars of a data quality improvement programme (Taken from http://peterjamesthomas.com/category/business-intelligence/data-quality/)
There are a number of elements that combine to improve the quality of data:
* Improve how the data is entered
* Make sure your interfaces aren’t the problem
* Check how the data is entered / interfaced
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The purpose of this research project, Structured Data Types into Internet-scale Information Systems to Utilize the Internet as an Effective Business Tool, is to better understand the Internet and actual applications. Enormous amounts of composite information have been accumulated within corporations, government organizations and universities. Such information continues to grow at ever-increasing ...
* Don’t suppress bad data in your BI
As with any strategy, it is ideal to have the support of all four pillars. However, We have seen greater and quicker improvements through the fourth element than with any of the others. We now touch on each area briefly.
1. Improve how the data is entered
Of course if there are no problems with how data is entered then (taking interface issues to one side) there should be no problems with the information that is generated from it. Problems with data entry can take many forms. Particularly where legacy systems are involved, it can sometimes be harder to get data right than it is to make a mistake. With more modern systems, one would hope that all fields are validated and that many only provide you with valid options (say in a drop down).
However validating each field is only the start, entries that are valid may be nonsensical. A typical example here is with dates. It is unlikely that an order was placed in 1901 for example, or – maybe more typically – that an item was delivered before it was ordered. This leads us into the issue of combinations of fields.
Two valid entries may make no sense whatsoever in combination (e.g. a given product may not be sold in a given territory).
Business rules around this area can be quite complex. Ideally, fields that limit the values of other fields should appear first. Drop downs on the later fields should then only show values which work in combination with the earlier ones. This speeds user entry as well as hopefully improving accuracy.
However what no system can achieve, no matter how good its validation, is ensuring that what is recorded 100% reflects the actual event. If some information is not always available but important if known, it is difficult to police that it is entered. If ‘x’ will suffice as a textual description of a business event, do not be surprised if it is used. If there is a default for a field, which will pass validation, then it is likely that a significant percentage of records will have this value. At the point of entry, these types of issues can be best addressed by training. This should emphasise to the people using the system what are the most important fields and why they are important.
Some errors and omissions can also be picked up in audit reports, which is the subject of the section 3. below. But valid data in one system can still be mangled before it gets to the next one and we will deal with this issue next.
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2. Make sure your interfaces aren’t the problem
In many organisations the IT architecture is much more complex than a simple flow of data from a front-end system to BI and other reporting applications (e.g. Accounts).
History often means that modern front-end systems wrap older (often mainframe-based) legacy systems that are too expensive to replace, or too embedded into the fabric of an organisation’s infrastructure. Also, there may be a number of different systems dealing with different parts of a business transaction. In Insurance, an industry, the chain might look like this:
Simplified schematic of selected systems and interfaces within an Insurance company
Of course two or more of the functions that we have shown separately may be supported in a single, integrated system, but it is not likely that all of them will be. Also the use of “System(s)” in the diagram is telling. It is not atypical for each line of business to have its own suite of systems, or for these to change from region to region. Hopefully the accounting system is an area of consistency, but this is not always the case. Even legacy systems may vary, but one of the reasons that interfaces are maintained to these is that they may be one place where data from disparate front-end systems is collated.
There are clearly many problems that can occur in such an architecture and simplifying diagrams like the one above has been an aim of many IT departments in recent years. What we want to focus on here is the potential impact on data quality.
Where (as is typical) there is no corporate lexicon defining the naming and validation of fields across all systems, then the same business data and business events will be recorded differently in different systems. This means that data not only has to be passed between systems but mappings have to be made. Often over time (and probably for reasons that were valid at every step along the way) these mappings can become Byzantine in their complexity. This leads to a lack of transparency between what goes in to one end of the “machine” and what comes out of the other. It also creates multiple vulnerabilities to data being corrupted or meaning being lost along the way.
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Let’s consider System A which has direct entry of data and System B which receives data from System A by interface. If the team supporting System A have a “fire and forget” attitude to what happens to their data once it leaves their system, this is a recipe for trouble. Equally if the long-suffering and ill-appreciated members of System B’s team lovingly fix the problems they inherit from System A, then this is not getting to the heart of the problem. Also, if System B people lack knowledge of the type of business events supported in System A and essentially guess how to represent these, then this can be a large issue. Things that can help here include: making sure that there is ownership of data and that problems are addressed at source; trying to increase mutual understanding of systems across different teams; and judicious use of exception reports to check that interfaces are working. This final area is the subject of the next section.
3. Check how the data is entered / interfaced
Exception or audit reports can be a useful tool in picking up on problems with data entry (or indeed interfaces).
However, they need to be part of a rigorous process of feedback if they are to lead to improvement (such feedback would go to the people entering data or those building interfaces as is appropriate).
If exception reports are simply produced and circulated, it is unlikely that anything much will change. Their content needs to be analysed to identify trends in problems. These in turn need to drive training programmes and systems improvements.
At the end of the day, if problems persist with a particular user (or IT team), then this needs to be taken up with them in a firm manner, supported by their management. Data quality is either important to the organisation, or it is not. There is either a unified approach by all management, or we accept that our data quality will always be poor. In summary, there needs to be a joined-up approach to the policing of data and people need to be made accountable for their own actions in this area.
4. Don’t suppress bad data in your BI
We have spent some time covering the previous three pillars. While we have generally had success operating in this way, progress has generally been slow and vast reserves of perseverance have been necessary.
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More recently, in BI programmes, improvements in data quality have been quicker, easier and almost just a by-product of the BI work itself. Why has this happened?
The key is to always highlight data quality problems in BI. The desire can be to deliver a flawless BI product and data that is less than pristine can compromise this. However the temptation to sanitise bad data, to exclude it from reports, to incorporate it in an innocuous “all others” line, or to try to guess which category it really should sit in are all to be resisted
So the “warts and all” approach is the right one to adopt ethically (if that does not sound too pretentious), but we would argue that it is the right approach practically as well. When data quality issues are evident on the reports and analysis tools that senior management use and when they reduce the value or credibility of these, then there is likely to be greater pressure applied to resolve them. If senior management are deprived of the opportunity to realise that there are problems, how are they meant to focus their attention on resolving them or to lend their public support to remedial efforts? This is not just a nice theoretical argument. The quality of data dramatically improve in a matter of weeks when Executives become aware of how it impinges on the information they need to run a business. Of course a prerequisite for this is that senior management places value on the BI they receive and realise the importance of its accuracy. However, if you cannot rely on these two things in your organisation, then your BI project in Insurance has greater challenges to face that the quality of data it is based upon.
2.0 The Solution
2.1 IT enabled Insurance carrier transformation
By focusing on the business drivers behind the IT systems modernization efforts, insurance companies are able to overcome the impediments to system transformation that has kept them mired in legacy environment for a tad too long.
2.1.1 Outsource
To mitigate the business risk and access the systems and skills required to launch new and innovative products the entire process can be outsourced. This can help the company launch new product in lesser time to the market. The need for implementing a new technology and training the staff for the same can thus be avoided. The data migration process from legacy systems can also be avoided in this case.
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This Outsourcing can be done by the companies who plan for a new business opportunity and want to mitigate risk and decrease time to market.
2.1.2 Cloud based modernization
When companies find it costlier to transform their legacy systems into latest technologies, they can make use of the cloud based transformation. The cloud-based systems provide pay-per-use options for legacy systems modernization which were previously not available. There are consulting firms that provide advisory services to evaluate and implement cloud computing options, from initial knowledge sharing to full case road map for implementation.
This option can be followed by companies who want to decrease the time to market but do not want to outsource the entire task to a third party
In Summary, Insurance companies are challenged by complex, irreversible and often out of date legacy IT systems. Besides being expensive to maintain, legacy systems adversely impact business. The erosion of competitive advantage and is compounded by discounted premium growth, escalating customer expectations and compliance guidelines.
Advantages of using IT :
* Increased chances of fund approval and enhanced business decision support system with a succinct strategy to achieve the same.
* Improves the business value of modernization initiative and the longevity of change through better-aligned business and technical architectures
* Reduces operational costs by optimizing processes and use of technologies
* Enhances product flexibility / speed-to-market due to improved underlying technology
* Ensures greater integration and interoperability.
* Decreased modernization costs through efficient execution.
The below figure gives us a brief scenario model as to when to use what kind of information technology tools
3.0 Available solution for Insurance sector by IT Vendors.
3.1 Information management solutions for insurance
Insurance information management solutions are designed to help profitability, revenue and customer satisfaction by enabling One to:
Segment and analyse customer value.
Generate tailored cross-sell and up-sell opportunities.
Provide a level of service proportional to the customer lifetime value for effective retention.
Measure the impact of the deployment of marketing and sales initiatives using metrics such as lead conversion rates.
Strengthen relationships with agencies.
Generate a learning process that leads to accuracy and speed of response to market changes.
3.2 Sales and Customer Service Solutions for Insurance
Insurance sales and customer service solutions assess the effectiveness of distribution networks and help in taking strategic and tactical measures that can help directly improve profitability. Insurance sales and customer service solutions help improve the effectiveness of point-of-sale systems through consolidation, up-front risk screening, straight-through processing, online and soft copy forms, and automated workflow processing.
* Sales and customer service solution include
* Claims management
* Policy administration
* Underwriting
* Customer service, and
* Distribution
4.0 DATA ANALYTICS
Data analytics in coming out in a big way to aid IT implementation in Insurance sector. It helps the industry in following ways :
4.1 Customer intelligence solutions for insurance
Customer intelligence solutions provide an integrated platform designed to deliver a single view of One customer by assimilating data from multiple sources. Using analytics tools, we can generate insights to help One identify, understand and segment customers, enabling One to deliver targeted offers. The solutions and web and social-media analysis capabilities helps design customer-centric sales, service and marketing plans while listening, in near real time, to the voice of the customer.
4.2 Supporting customer retention by optimizing customer communication
Data integration and analysis capabilities aid in clustering and segmenting customers. These behavioural segmentation analyses can help make more accurate and informed decisions for more optimized customer interactions and communication. In addition, communication initiatives tailored to specific segments and target audiences to help One attract and retain customers. Enterprise-wide communications strategy facilitates and manages enhanced interaction through a wide variety and combination of communication channels.
Enabling a more unified and accurate view of customers
Insurance solutions can capture and analyse structured and unstructured customer data to help better understand customers and more accurately anticipate their needs. By facilitating the integration of information from multiple and disparate touch-points such as social media sites, call centres and various communications devices, it can provide with more current, timely and accurate insights about customers. In addition, it can enable information access and management that is beyond the traditional data warehouses and sources across the enterprise—helping to gain a single, holistic and more unified view of customers.
4.3 Insurance Software Product Performance
The Insurance Software Product addresses planning and performance management process areas that enable the agility to the organization needs to create business value. The Insurance Software Product helps to :
* Establish clear and concise targets for each manager or product.
* Calculate revenues, expenses and claims based on adjustable historic trends.
* Develop revenue planning scenarios.
* Automate the calculation of earned premium and unearned premium reserves (UPR).
* Determine the premium spread by product.
* Plan current accident year claims by peril when calculating the incurred dollar (size and frequency or loss ratio).
* Build a balance sheet by product that enables users to enter a premium debtor’s rate and adjust as necessary the trended deferred acquisition cost (DAC) items.
* Plan forecasts in a local currency then convert it to the corporate standard currency using corporate rate tables
* Enable reporting and analysis by product line and product.
4.4 Integrate data and achieve deeper business insights
Insurers often struggle to get the right data to make decisions in a timely manner. Too frequently, insurance executives do not trust the data they are given or it is not presented in a user-friendly way, nor is it structured to answer the key business questions. In addition, insurers have rarely been able to forecast multiple business scenarios accurately to determine the most profitable course of action. Finally, despite the tremendous value of actuarial insight afforded the planning and product design process, what is actually used for a cost basis is often out of date and inflexible when it is applied to the exercise of product planning and pricing.
The first step is to consolidate data, storing all relevant transactional, product, claims and expense information in an accessible enterprise data warehouse. Next is to apply appropriate reporting and analysis tools to the task of understanding as much as possible about product lines and individual products.
4.5 Operational excellence based on intelligence
The Insurance Software Product provides a hierarchy of dash-boards and reports that help users gain increasingly deeper levels of under-standing of information from across the company. A business intelligence portal begins with a high-level view. The portal may be tailored to view reports based on a user’s level of security and/or responsibility. One can see revenue reports for all products and product lines or for a single area of responsibility, such as a specific product line, product or combination.
4.6 Drive insurance product and overall profitability
With the Insurance Software Product, One can assess Insurance Software Product in the context of corporate goals and objectives with budget and forecast constraints. Using targeted, prebuilt data, process and policy models, One can help affect a company’s profit and loss statement in a positive way.
5.0 Advantages of implementing IT in Insurance sector.
Actuarial Analysis
Insurers base their rates on actuarial models that seek to determine what risks are more or less likely to experience a loss. Insurance companies are using technology to analyze years of claims and policyholder data searching for correlations between risk characteristics and claims. Technology has allowed actuaries to analyze risk at a much more precise level of granularity.
Policy Administration
Most insurance policies are still printed and delivered to policyholders by mail each year. The process of creating these documents used to be accomplished by armies of clerks, technicians and typists. In most cases, this repetitive task has been completely re-imagined using technology. Customer data is maintained in massive databases, where it is accessed by computer systems that automate the renewal of each policy. Policies are assembled using complex software packages and printed using advanced high-speed printers.
Automated Underwriting and Rating
Every insurance policy undergoes an underwriting process that determines if the insurance company is willing to provide insurance. If the risk is acceptable, it is then rated, to determine the price the company will charge. Once the purview of highly trained underwriters and rating technicians, this process is now automated, with only the most unusual risks requiring personal attention.
Client Data
Insurance carriers maintain accurate and updated client data records. Information technology must be both secure and comprehensive enough to store multiple names, addresses, telephone numbers, email addresses and other pertinent details.
Policy Details
For those insurance companies providing policies across multiple lines of insurance, information technology requirements become even more complex. Details of each insurance policy, ranging from life, home, auto, boat, liability and business products, need to be accurately recorded and merged with client data.
Claims Management
Investigating, paying and recording claims data is crucial to any insurance company’s financial stability. Information technology plays a vital role in allowing carriers to record claims details and share data with police, other carriers, attorneys and beneficiaries. Advanced computer software ensures important information remains accessible and updated.
Beneficiaries
Life insurance companies utilize database technology to record policy owners’ beneficiary designations. Aside from the personal details of the insured individuals, beneficiary names, addresses, telephone numbers and death benefit portions are of monumental importance.
Payment Information
Perhaps the most essential area requiring accurate and efficient information technology is an insurance company’s client payment details. Above all else, billing and invoicing systems generate the necessary revenue to keep the company in business. Cash flow remains vital to daily operations and without superior information technology and processing systems, the carrier’s financial stability is at risk.
6.0 How modernization is happening in Insurance Industry :
Insurance companies are challenged by complex, inflexible and often obsolete legacy IT systems. Besides being expensive to maintain, legacy systems adversely impact business. The erosion of competitive advantage is compounded by low to moderate premium growth, increasing burden of regulatory compliance and customer expectations. Modernization of IT infrastructure will remain an incomplete exercise without strong alignment between infrastructure modernization and modernization of the operational context. It should consider the long-term landscape of the industry, industry benchmarks and enterprise strategy.
Insurance Modernization solution provides a comprehensive set of business and technology components to improve modernization planning and design, make a more robust case for change, increase the efficacy of the transition and optimize business value derived from modernization.
Most insurance companies are facing the multiple challenge such as increasing cost of operation, regulatory pressure, low perceived business-IT alignment, and old inflexible technology infrastructure. These pressure is compounded by low to moderate premium growth and the increasing burden of regulatory compliance. Some of the challenges faced by the companies are show in the figure.
Several root cause lie in the business process and technology dimension, many insurer focus on addressing technology problem in form of legacy modernization. In a majority of modernization efforts, changes to technology are not mapped to impact on process, people or service metrics. It is therefore important to appreciate that modernization of IT infrastructure in itself remains an incomplete exercise, until there is a strong alignment between technology of the operational context- people and process. Indeed for best result we should think in long term basis of the industry, benchmarks and enterprise strategy.
Capability driven approach to Insurance Modernization- We should think business capabilities as the building blocks. Any entity broken down in the set of core business capabilities as depicted in the figure below for the average insurer.
These core capabilities can further be broken down in the smaller entities or lower level capabilities. These lower levels can be termed as the business capabilities. Business capability represents a collection of attributes capturing people, process and technology. We can think of Business Capability as a service. Each business capability should have at least one service level agreement. The picture of business capability broken down into its layers, along with an SLA is shown in the picture below.
For example : One of the capability that the company wanted to acquire is Electronic Document Management. This capability can be broken down to lower level capabilities like :
* Automated Content Capture
* Content Management
The benefit of analysing an Insurance company from the lens of business capabilities include
Capability Improvement measure are a good way of judging the long term efficiencies because they are more constant than traditional process improvement analytics; processes change frequently, impacting most process improvement efforts before they are completed.
Capability focus enables the capture of activities external to insurance companies (usually 3rd party systems), which allows company to view its entire operational environments. Capabilities drive the definition of service level metrics allowing for improved performance and management. Capabilities do not derive value highlighted and can be extracted. More importantly, service valuation enables prioritization – a key to an improvement effort.
This approach involves three distinct phases.
* Increases the likelihood of funding approval and business support with a clear, strong case for change
* Improves the business value of your modernization initiative and the longevity of change through better-aligned business and technical architectures
* Reduces operational costs by optimizing processes and use of technologies
* Enhances product flexibility / speed-to-market due to improved underlying technology
* Ensures greater integration and interoperability
* Reduces overall modernization costs through efficient execution
7.0 Conclusion
Insurance companies using IT can leverage more from their operations and perform better. They can use IT to reduce the costs, increase the sales of various insurance instruments. IT enables companies with the better management of the whole organization. But this all comes with a word of caution that a poorly developed IT infrastructure can shoot up the operations cost so before implementing a new solution from an IT vendor the insurers must ensure that this new capability is adding something to the bottom line and will help them to position their selves better in long term.
References
Information Technology in the Insurance Sector | eHow.com http://www.ehow.com/facts_6790988_information-technology-insurance-sector.html#ixzz24BKzcMzL
http://www.deloitte.com/view/en_US/us/Industries/Insurance-Financial-Services/4ea1ea2d152a7310VgnVCM3000001c56f00aRCRD.htm#
en.wikipedia.org/wiki/Insurance
http://www. .com/industries/insurance/industry-offerings/Pages/insurance-modernization.aspx
http://peterjamesthomas.com/category/business-intelligence/data-quality/
http://towergroupedge.exbdblogs.com/2012/07/31/technology-value-risk-in-insurance-it-road-map/
https://strategymeetsaction.com/the-role-of-social-media-in-insurance/
http://www.innovationininsurance.com/
