Hymans Robertson LLP is authorised and regulated by the Financial Conduct Authority Northamptonshire Pension Fund Importance of good data Lorna E. Lyon 21 October 2014
Agenda Background Employer lifecycle Data requirements Impact of incorrect data
Northamptonshire Pension Fund More than 53,000 members Managing assets of £1,543m* Over 200 employers A few pensioners over 100. Shared resources and expertise with Cambridgeshire Pension Fund *as at 31 March 2013
Valuing a single member
Valuing all members Source: Sample LGPS fund
Employer lifecycle Procurement Pensions Information Memorandum (PIM) Admission Contributions and bonds Ongoing Bond renewals, valuations and accounting Imminent exit Indicative cessation Exit Cessation
How do we impact on the results? Financial Salary increases Pension increases Discount rate / future investment return Demographic Longevity Early leavers Retirement age Dependants
How do you impact on the results? DATA
Name Date of Birth Title Date of Joining Date of Leaving Pensionable Pay Final Pay Part-time Hours Full-time Hours Changes Certificates of Protection NI Number Reason for leaving Opt-outs Opt-ins NI Class C/O Earnings Marital Status Employer code Postcode Added Years Augmentation Additional Contributions Contribution Rate Officer/Manual Worker Maiden name Spouse’s details Service Credit - transfers Year end info What membership data should be stored? Sex
Impact of inaccurate data ScenarioABCD SexMMMM DOB01/01/ /01/ /01/1965 Pensionable salary £25,000 £52,000 £25,000 Date of Joining 01/01/ /01/1998
Impact of inaccurate data: liabilities (Date of Birth) (Pay) (Date Joined)
Impact of inaccurate data: Contributions -3%
Name Date of Birth Title Date of Joining Date of Leaving Pensionable Pay Final Pay Part-time Hours Full-time Hours Changes Certificates of Protection NI Number Reason for leaving Opt-outs Opt-ins NI Class C/O Earnings Marital Status Employer code Postcode Added Years Augmentation Additional Contributions Contribution Rate Officer/Manual Worker Maiden name Spouse’s details Service Credit - transfers Year end info What membership data should be stored? Sex
Vita’s lifestyle effect (postcode effect) High life expectancy Mid life expectancy Low life expectancy
Vita’s lifestyle effect (postcode based) High life expectancy Mid life expectancy Low life expectancy Source: Club Vita research based on VitaBank as at January 2013
Employer lifecycle Procurement Pensions Information Memorandum (PIM) Admission Contributions and bonds Ongoing Bond renewals, valuations and accounting Imminent exit Indicative cessation Exit Cessation
What else could it impact? Benefits Benefit statements Finances of the employer GAD/EFA/Regulator Penalties
In summary Data is crucial Need accurate information from you
Any questions? Thank you