New York - Senior insurance executives are concerned about governing and managing the crushing volume of data their companies maintain these days, especially in light of stricter reporting requirements.
That’s the word from the Insurance and Actuarial Advisory Services (IAAS) practice of Ernst & Young LLP. The group came up with that and other findings during its third Actuarial Transformation Roundtable, a forum where insurance executives discuss issues, challenges and best practices.
A survey of participants revealed 88% of attendees agree that, “data management issues currently impact the ability to provide reliable, valid financial data.” At the same time, more than half (56%) say they do not have a dedicated data governance team in place and 67% do not have a formal data management program.
“Companies need to engineer a culture shift,” says Steve Goren, roundtable moderator and leader of the Ernst & Young IAAS Actuarial Transformation practice. “It is crucial to get everyone to acknowledge data governance and quality as key corporate priorities and reflect this in their operating practices and processes.”
Recognizing that problems will multiply over time, insurers need clean up data and change processes, says Goren.
“We have termed the data management evolution ‘Actuarial Transformation,’ and it includes the move to an automated, controlled, yet flexible technology-based environment” he says.
Other highlights of the roundtable dialogue and survey included discussion of harnessing data improve quality. Nearly three-quarters (73%) of participants say the quality of their data needs at least some improvement and half (50%) acknowledge that their actuarial team spends between three and five “person days” per month correcting data quality issues.
Having acquired vast quantities of data, typically spread over numerous legacy administration systems, companies are struggling with integration. Preparing data for input into the valuation and modeling engines used in actuarial processes has become time consuming as insurers struggle with inconsistency stemming from the fact that various systems use different definitions. One participant suggested companies invest in building a data dictionary, which may slow the process in the short term but eliminate future quality struggles.
Another issue was higher expectations for regulatory compliance and litigation. The vast majority of participants (93%) agreed that the assumptions they use in actuarial models constitute data that must be stored and managed. In fact, many acknowledged they are building meta-data repositories to hold information about data, such as how they develop their assumptions, in order to satisfy auditors.
“Insurers are fighting an ongoing data battle as they look to address who owns the data, how it should be maintained, who should have access to it and, most importantly, how to bring it together and integrate it in a way that will make it useful,” says Goren. “All of these issues relate to basic decision making and overall financial reporting and, if positioned appropriately, should gain C-suite attention.”
Meanwhile, data governance is becoming a C-Suite imperative, according to attendees. The group agreed the data management challenges the industry faces require organizational change. Data governance--the process and organizational structure developed to create control--was offered as the solution. However, the group cautioned that governance must be addressed from the top down and must have strong C-suite commitment.
A data governance idea beginning to gain favor is the addition of a full-time Data management organization (DMO) between the corporate C-suite and the business line operations level. The idea was well received by roundtable participants, and some have already moved in that direction.
The DMO is guided by the C-suite and, in some cases, an executive-level data governance committee. The DMO needs to build strong partnerships with the lines of business–the operations, accounting, IT and actuarial teams–to bridge the gap and assure communication among groups. The DMO is also responsible for putting rules in place about managing data, maintaining legacy data and handling data from new products.
“Creating a DMO is a strategic investment,” says Goren. “Too often, companies avoid taking a strategic view of data management because it is too painful, but the initiative more than pays for itself in the long-run.”
Attendees also debated the subject of breaking the love/hate relationship with spreadsheets. They spent considerable time discussing the use of spreadsheets in a Sarbanes-Oxley (SOX) world. Spreadsheets are used extensively in actuarial valuation departments, with more than half (51%) saying they use between 10 and 50 spreadsheets to determine financial statement transaction amounts each quarter.
Participants agreed the flexibility and transparency of spreadsheets would be difficult to do without, particularly for quick analysis, top-side adjustments and system testing. That drives the hesitation to convert to models. At the same time, they recognize that new regulations and added compliance hurdles make the conversion necessary, and some even acknowledge that they are barely meeting SOX requirements. In fact, some point out that the documentation and version control required today has eliminated a lot of spreadsheet flexibility, thus decreasing the appeal of spreadsheets.
There was consensus that it would be nearly impossible to eliminate spreadsheets but that there is a need to pare down. Most participants say they are moving in that direction, and some point to a goal of cutting out 80% to 90% of spreadsheets.
To transfer spreadsheet calculations to formal technology applications, actuaries must team up with IT, attendees say. Companies must also expand and enhance their valuation data warehouses.
Participants agree that valuation actuaries have become tied up in data management, spending too much time updating, maintaining and controlling spreadsheets. That work interferes with their efforts to focus on delivering business intelligence.The group expressed frustration about the time left in the financial reporting process for analyzing and explaining results. Many expressed concern about jumping new hurdles, such as principles-based reporting, without making significant changes to current practices.
“Just as critical as data input is output for analysis,” says Goren. “There is a significant opportunity for companies who transform their processes. They will not only enhance their data quality, but free up their actuarial department to focus on the area where they can truly add value… business decision support.”
Source: Actuarial Advisory Services (IAAS) practice of Ernst & Young LLP
Register or login for access to this item and much more
All Digital Insurance content is archived after seven days.
Community members receive:
- All recent and archived articles
- Conference offers and updates
- A full menu of enewsletter options
- Web seminars, white papers, ebooks
Already have an account? Log In
Don't have an account? Register for Free Unlimited Access