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Data Integrity – Your questions answered

Data Integrity – Your questions answered. Sarah Denner Brown SDB Talking Direct. Don’t ask her any questions about data integrity and perhaps she’ll go away. A statement of the blindingly obvious.

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Data Integrity – Your questions answered

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  1. Data Integrity – Your questions answered Sarah Denner Brown SDB Talking Direct

  2. Don’t ask her any questions about data integrity and perhaps she’ll go away.

  3. A statement of the blindingly obvious Data is very, very, very, important to effective operational processes across the whole organisation.

  4. A few examples • Billing and collections • Legal compliance • Managing customers on and offline • Preventing fraud and money-laundering • Marketing

  5. Marketing -Who do you mail? Miss Florence Jones Holly Cottage 3 Church Hill Lane Monmouth NP13 2QT Mr. Kevin Jones Flat 21 Nelson Mandela House 135 London Road CHELMSFORD CM3 4AA

  6. Age ACTIVE SUBS. INACTIVE SUBS NUM. % NUM. % Difference In % Under 11 11 - 17 18 - 24 25 - 34 35 - 44 45 - 64 65 & Over Unknown 343 7,714 10,401 13,126 12,860 15,711 3,577 22,494 0% 9% 12% 15% 15% 18% 4% 26% 70 1,687 2,172 2,177 1,800 1,527 329 4,012 1% 12% 16% 16% 13% 11% 2% 29% Shaded bar = statistically significant difference

  7. £

  8. CRM And e-CRM THE BIG PICTURE

  9. …Excellent customer service Quality data, intelligently used

  10. Managing customers via the web? If anything…they manage us more often than not • Managing customers frequently translates to £0 • Engaging customers CAN sometimes translate to lots of £ • This all assumes that there isn’t someone in the organisation just giving that engagement away!

  11. A typical corporate CRM vision • “Become the provider of choice having the closest relationships with our customers… delivering the best treatment to each customer at the right time through the most suitable channel at the appropriate cost: a customer centric approach with each customer contact maximised in terms of value to the business and value to the customer” What does that mean in data terms?

  12. Warehouse in CRM context Serves three key objectives; • One consistent view of the customer and a level of data integrity that is fit for purpose • Permits direct access to data by business functions and manages its transformation into critical information and intelligence • Ensures that this intelligence is exploited across customer facing operations

  13. Customer intelligence out Raw data in Data factory:clean, match, dedupe. QA Data Refinery; analysis, business rules Other Retail stores Contact centres Sales Finance Web etc.

  14. Operational Processes

  15. “ The b****y customers just do not understand the problems we have” Major utilities supplier discussing the problems of migration from legacy systems and multiple systems

  16. Identification and collection of relevant data Moving the culture of the business data-wards Maintaining the integrity of your data Converting raw data to marketing information What is involved in CRM?

  17. Applying statistical techniques to analyse behaviour, isolate segments, score and rank individuals • Evaluate the economics of data collection and analysis • Capitalise on the economics of data-driven marketing programmes • Creatively act on the opportunities that emerge to develop individual relationships and the business as a whole

  18. £

  19. Money Laundering and Fraud (anti )

  20. How to Commit Identity Fraud

  21. How to Commit Identity Fraud www.nextdayid.co.uk www.uwantid.co.uk www.phidentity.com www.identacard.co.uk www.ypurphoto-id.com www.noveltyid.co.uk www.phakeid.co.uk www.legalfakeid.com www.fakeidexpress.com www.europeanid.co.uk www.fakeid.co.uk www.mrbateman.co.uk

  22. Regulation Requirements • Identity checking • Know Your Customer (KYC) • Monitoring transactions • Checking against Sanctions data • Checking against Politically Exposed Persons data • At the start of a relationship • Throughout the life of the relationship

  23. Know Your Customer KYC should be viewed as a corporate asset • Type of job - need to pay in cash? Likely demographics? • Salary – affordability? Supports credit? • Essential tool in the fight against money laundering

  24. Assessing the identity risk • Validity is satisfied where there is sufficient supporting evidence to confirm that a person of that name exists • Verification is the process of establishing that the applicant is the ‘data subject’ or ‘owner’ of the valid identity references

  25. Assessing the credit risk Look at the person’s: - • stability • time at address, time in employment • credit track record • adverse data • degree of commitments • ‘experience’ of handling credit • demographics • age, marital status, number of dependants

  26. Assessing the fraud risk • Soft fraud - misrepresentation • yesterday £10K salary in job 6 months • today £25K salary in job 3 years • Hard fraud - fabrication • inferred alias • ‘shared’ attributes • hits against known frauds • name • address

  27. Customer Data Sources of customer data • Physical documents • Source data relating to documents • Electronic data sources • customer records • transaction records

  28. Cabinet Office ID Fraud Study “The extent of the problem” • “Most current processes for issuing government documentation used for identity verification ….. do not meet the highest private sector standards of security”

  29. Cabinet Office ID Fraud Study “The way forward” • “ For most people, checks against databases run by credit reference agencies will give much more satisfactory validation and verification of identity “

  30. £

  31. Some costs of poor data • Company image • Annoyed customers • Failure to maximise opportunity • Out of control costs • Operational inadequacy • Fraud • Competitive disadvantage • Demoralised staff.

  32. But data costs… • Must invest to succeed • Data is for life not just for Christmas! • And there is a lot conspiring against you!

  33. Strategic difficulties • Multiple systems • No overall responsibility • No data strategy • Multiple channels of collection • Lack of senior management buy-in • Lack of personnel / technology / budget • Training and cultural issues

  34. What can we do to minimise the problems? Be strategic about it!

  35. Five things that successfuldata-centric companies do • Make data a corporate priority • Specify and implement a coherent data strategy • Enforce consistent house rules on collection • Integrate data from multiple channels • Have a strong data hygiene policy including getting it right from the start!

  36. What does a data strategy involve? • Understanding the day to day needs of the data • Determining the development of data usage and technical maintenance in the medium and long term • Relating data to every nook and cranny of the business • Determining the data to be collected • Implementing appropriate processes for collection

  37. What does a strategy involve? (2) • Quality assurance • Training and education from top to bottom • Establishment of strict business rules • Determining standards of data hygiene • Identifying and clearing problems (audits) • Implementing data maintenance procedures • Integrating customer data across multiple systems, channels and touch-points

  38. Purposes of a data strategy • Operational • Marketing • Legal compliance • Diversity and Equality Strategic direction and butt covering!

  39. Self Assessment Data Checklist • Does your organisation have a customer information strategy in place? • What customer details are captured? • How do you capture customer data? • What information is captured online? • What market research activities are done?

  40. Self assessment 2 • How do you work with your intermediaries? • How do you work with third parties and the information they provide? • How do you control and ensure the quality of your customer data? • How do you comply with the data protection act?

  41. Self Assessment 3 • How secure is your customer information? • How well are you achieving CDI across your various systems? • How well can you consolidate and deduplicate customer information? • How are your data systems designed and are they compatible with each other?

  42. Self assessment 4 • How well do your customer systems support the way in which you operate? • What are the analytical skills in your organisation and how are they organised? • What analytical tools does your organisation employ? • What processes are in place for customer data analysis?

  43. Why the strategic approach is best – Data collection example

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