In the UK there is debate forming about how best to target benefits on the most deserving cases without building a dependency culture. For some time the UK Government has been using 'means tests' to ascertain whether a claimant needs State support, or whether they have independent resources that they should really rely on first. To further reinforce the 'best form of welfare is work' message many cash benefits have been replaced with 'Tax Credits' that allow those on lower incomes to keep more of the money they earn.
Whilst there is no doubt that this approach has led to significant realignment of State support to some, it has come at the cost; in the UK billions of pounds of benefits remain unclaimed each year (£4.2 billion (US$8.3 billion) by the elderly alone). There are potentially many reasons for this, but chief amongst them are;
- Some people are simply not aware of what they are entitled to
- Others are put off claiming because they are proud and would have to reveal their financial circumstances
- Some are concerned that they might inadvertently over claim and be accused of fraud.
- And some have a little savings and incorrectly assume that this precludes them from State support
Add to this the annual outcry about huge errors in the payments of benefits through the Tax Credit system (typically because of a change of the Claimant's circumstances and infrequency of calculation of entitlement) and it's clear that something has to change.
As has already been proven we can use analytics to identify socio-economic groups, predict likely future needs and even detect fraud, why do we not use analytics more to anticipate individual needs? Or put it another way, why doesn't the State, that knows far more about the benefits system and has access to huge amounts of data about citizens, take up the responsibility for calculating a claimant's likely entitlements and then present this portfolio to the claimant under the banner of "this is what we believe you are entitled to and this is why..."? If administered well, it could even reduce fraud and error currently made easier by a complex system of benefits calculations often undertaken in isolation.