ING Lease defeats fraud with smart identity matching
18.05.2009

In order to meet the market requirement for a rapid turnaround
of credit decisions, finance providers have invested in
automated underwriting systems. In difficult economic
conditions, the scale of fraudulent credit applicants increases,
putting greater pressure on automated decision systems and the
manual checks that supplement them.
Fraudulent applicants are using greater tenacity to access
limited credit facilities.
Credit providers must respond by implementing more robust &
sophisticated techniques to intercept fraudulent applicants.
Human Inference's automated fraud detection system replicates
the 'natural language processing' capabilities of a human brain.
Human Inference uses a knowledge base of language rules, facts and
logic to interpret personal data and achieve industy leading
matching against sanction lists and credit watch lists.
For example Human Inference will recognise that 'Dr John J
Farren', and 'Jon James Pharan PhD.' are probably the same
individual. Traditional techniques would not recognise this as a
match, and consequently a fraudulent applicant could slip through
the net.
ING Lease UK in Redhill, Surrey, has embedded the sophisticated
matching from Human Inference into it's existing ALFA Systems
application architecture, from CHP Consulting. ALFA's Business
Rules Engine (BRE) calls the Human Inference fraud detection
routines as part of the automated credit decision process.
Paul Stevens, Chief Information Officer at ING Lease UK states:
' Regardless of the increased volatility in the financial
markets, the need to ensure 'right first time, every time'
decisions at the speed required by introducers is an essential
element of a funders service. ING Lease UK, a key partner in the
introduced lease business market, is always seeking ways to improve
the quality of service offered to introducers and has selected
Human Inference to further enhance its market leading proposition.
Human Inference uses 'Natural Language Processing' to achieve
results which are quicker, more accurate and more consistent than
manual checks in a time critical, volume market'.
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