As I’ve established in earlier posts in this series, manual data entry creates multiple problems for insurers: data quality issues, operational complexities, and the difficulty of maintaining fast turnaround times due to an inability to accurately forecast demand and workforce scalability, to name just a few.
Insurers can begin to tackle these problems by taking a look at some of the new options available to facilitate data capture: newer, more advanced character and word recognition technologies, as well as vendors that specialize in data capture and combine the powers of crowd sourced labor and advanced machine-learning-enabled optical character recognition (OCR) and intelligent word recognition (IWR) algorithms.
When considering data capture technologies, insurers should ask themselves a few key questions to help identify if a change is warranted, and if so, to help guide the decision on where to start:
Impact: Is the need to centralize data – both from legacy systems and newly-captured sources (such as MDC) – an ongoing challenge for your organization?
Quality and risk events: Is the elimination of not in good order data from handwritten forms essential to your firm’s governance structures, compliance and risk management?
Complexity: Do you have difficulty determining the quality, type, and amount of data in your legacy system, due to disparate or fragmented silos or inaccessibility? Is the cost of manual data entry and review becoming prohibitive?
Competition: Are you using your legacy data as effectively as possible to update business processes, improve internal and customer-facing experiences and gain market share?
Current state of data capture: Is OCR currently used in the business? Is it primarily for indexing purposes or also for bulk data capture? What are the accuracy rates?
How much manual data entry is required to achieve accuracy targets? What are the most critical forms from a business intelligence, customer experience, and regulatory risk perspective?
Once these questions have been answered, the need will be apparent and the starting point will have been identified. The insurer will be well on its way to changing how quickly it is able to get to a high-quality, structured, digital data set, which in turn will enable a much stronger ability to predict, react and achieve.
By achieving a higher speed to quality data, insurers will get the following benefits:
– An improved ability to react effectively to customers’ and prospects’ requests, thereby enhancing the customer experience, retention and growth.
– Advanced analytics, which increases the speed and quality of business insights. This in turn improves the effectiveness of the insurer’s actions – driving profitability, market growth and retention.
– Reduced regulatory and compliance risk, which has huge ramifications for profitability, as well as growth and customer retention.
Thus, data capture is of the utmost importance to insurers. A highly accurate, digital data set quickly enables the levers of market growth, customer retention and profitability.