Lloyds Insurance Seminar

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Lloyds Insurance Seminar. Don Marsh – Senior Executive, Oracle Watchlist Screening 29 th February 2011. Awkward Questions. Isn’t that the Guy from Datanomic? What do Oracle know about Compliance Screening?. Who screens with Oracle WLS?. Automated Watchlist Screening – What is it ?. - PowerPoint PPT Presentation

Transcript of Lloyds Insurance Seminar

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Lloyds Insurance Seminar Don Marsh – Senior Executive, Oracle Watchlist Screening29th February 2011

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Awkward Questions

• Isn’t that the Guy from Datanomic?

• What do Oracle know about Compliance Screening?

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Automated Watchlist Screening – What is it ?

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Automated Watchlist Screening - Why it Matters

Financial services firms’ approach to UKfinancial sanctions

“It’s hard to understand how a firm can achieve its compliance obligations without ongoing screening of its customers on a frequent basis”

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What Happens if it Goes Wrong?

What Happens if it Goes Wrong?

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•Substantial fines and penalties against

• Companies• Individuals within

companies

• Lloyds TSB $350m• CSFB $536m• Aon £5.25m• ANZ $7m• ABN $500m• UBS $100m• Willis £6.9m

etc....•Brand damage and loss of reputation

What Happens if it Goes Wrong?

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•Substantial fines and penalties against

• Companies• Individuals within

companies

• Lloyds TSB $350m• CSFB $536m• Aon £5.25m• ANZ $7m• ABN $500m• UBS $100m• Willis £6.9metc....

•Brand damage and loss of reputation

What Happens if it Goes Wrong?

9

•Substantial fines and penalties against

• Companies• Individuals within

companies

• Lloyds TSB $350m• CSFB $536m• Aon £5.25m• ANZ $7m• ABN $500m• UBS $100m• Willis £6.9m

etc....•Brand damage and loss of reputation

What Happens if it Goes Wrong?

10

•Substantial fines and penalties against

• Companies• Individuals within

companies

• Lloyds TSB $350m• CSFB $536m• Aon £5.25m• ANZ $7m• ABN $500m• UBS $100m• Willis £6.9m

etc....•Brand damage and loss of reputation

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It’s all about the Data...

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Watchlist Data is Complex

Approx 300,000

names just on US OFAC list...

19 Aliases and 4 Locations

10 Aliases and 2 Date of Births

‘Simple’ matching is not enough

Watchlist Data is Complex

Customer Information is Complex

• Watchlist and customer data entries often include inconsistencies, inaccuracies or are incomplete

• Screening against data that is not fit for purpose reduces screening accuracy, increasing risks and costs

Unstructured Data Presents Screening Challenges

Parsing Names from Unstructured Name and Address Fields

Parsing and Enriching Location Data

Screen Data That Is ‘Fit For Purpose’

Who is Donald Mackenzie?

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Lloyds Insurance Seminar Don Marsh – Senior Executive, Oracle Watchlist Screening29th February 2011

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