Systemic Vulnerability Analysis of a High-Function ATM

1. Systemic Vulnerability Analysis of a High-Function ATM Tina Chang Lindsay Wiseman JuthamasChoomlucksana

2. Overview of Contents • Introduction • Background • Motivation for Analysis • Literature Review • Objectives of Research

3. Overview of Contents • Introduction • Background • Motivation for Analysis • Literature Review • Objectives of Research • Methodology • IDEF0 • HMSEM Workbook

4. Overview of Contents • Introduction • Background • Motivation for Analysis • Literature Review • Objectives of Research • Methodology • IDEF0 • HMSEM Workbook • Recommendations

5. Background • New high-function ATM is still in the design phase • Made assumptions in regards to the user interface due to the information being proprietary

6. Background • New high-function ATM is still in the design phase • We had to make assumptions in regards to the user interface due to the information being proprietary • High-function ATM • Requires user to sign up as member to use services • Have their picture taken • Scan their finger print • Enter in personal information • Social security number, phone number, address, etc.

7. Background • New high-function ATM is still in the design phase • We had to make assumptions in regards to the user interface due to the information being proprietary • High function ATM • User must sign up for the services • Scanning their personal identification • Scanning their finger print • Enter in personal information • Social security number, phone number, address, etc. • The ATM will then verify the information to accept or reject the application.

8. Motivation for Analysis • Human errors increase as automatic teller machines become more sophisticated.

9. Motivation for Analysis • Human errors increase as automatic teller machines become more sophisticated. • Leaves both long-time and new customers frustrated when they attempt to complete a wide range of transactions.

10. Motivation for Analysis • Human errors increase as automatic teller machines become more sophisticated. • Leaves both long-time and new customers frustrated when they attempt to complete a wide range of transactions. • A thorough human engineering psychology analysis can give a product design-criterion to avoid these frustrations and help keep their customers satisfied.

11. Literature Review (1) • Zimmermann and Bridger (2000) developed two ATM interfaces to compare the efficiency and error profiles in current use: • Green monochrome • Color displaywith newer displays and distinctly different software

12. Literature Review (1) • Zimmermann and Bridger (2000) developed two ATM interfaces to compare the efficiency and error profiles in ATM current use: • Green monochrome • Color displaywith newer displays and distinctly different software • Results showed withdrawals were the most frequent transactions at ATMs by observing 300 members using ATMs in South Africa.

13. Literature Review (2) • In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM.

14. Literature Review (2) • In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM. • All participants were required to be a current ATM user or at least possess an ATM card.

15. Literature Review (2) • In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM. • All participants were required to be a current ATM user or at least possess an ATM card. • Participants performed two tasks, withdrawal and balance enquiry, using a real-world ATM. • Showed that automatics speech recognition technology will not only improve system usability, but it also created a flexible interface in traditional ATM.

16. Literature Review (2) • In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM. • All participants were required to be a current ATM user or at least possess an ATM card. • Participants performed two tasks, withdrawal and balance enquiry, using a real-world ATM. • Showed that automatics speech recognition technology will not only improve system usability, but it also created a flexible interface in traditional ATM. • Moreover, user emotions in terms of fun, joy and excitement should consider in design of affective user interface.

17. Literature Review (3) • As Norman (1988) addressed, a good user interface can minimize the gap between the user’s knowledge and intentions with the system. • Other perspectives to include in ATM design; • Age • Usability by the blind • Psychological attitudes to innovativeness and computers (e.g., Adams and Thieben 1991, Mankzeet al. 1992, Burgoyne et al. 1992)

18. Objectives • Create a complete model of all transactions the customer can complete using this ATM

19. Objectives • Create a complete model of all transactions the customer can complete using this ATM • Compile a thorough list of human fallibilities that can occur

20. Objectives • Create a complete model of all transactions the customer can complete using this ATM • Compile a thorough list of human fallibilities that can occur • Create a list of recommendations for ATM design project manager and engineers to prevent these errors from occurring

21. Methodology • IDEF0 Model

22. Methodology • IDEF0 Model • Human Machine System Engineering Methodology (HMSEM) Workbook • Informal List of Potential Errors

23. Methodology • IDEF0 Model • Human Machine System Engineering Methodology (HMSEM) Workbook • Informal List of Potential Errors • Task analysis

24. Methodology • IDEF0 Model • Human Machine System Engineering Methodology (HMSEM) Workbook • Informal List of Potential Errors • Task analysis • Human Fallibility Identification and Remediation Methodology (HFIRM) Analysis

25. Methodology • IDEF0 Model • Human Machine System Engineering Methodology (HMSEM) Workbook • Informal List of Potential Errors • Task analysis • Human Fallibility Identification and Remediation Methodology (HFIRM) Analysis • Failure Modes and Effects Analysis (FMEA) analysis

26. IDEF0 Model • Used to represent all activities involved to complete a wide variety of transactions from the customers’ perspective • Included all controls, mechanisms, inputs and outputs for every activity the customer will be involved it • These mechanisms and controls were then further evaluated to help create an informal list of potential human errors.

27. IDEF0 Level A-0

28. IDEF0 Level A0

29. Informal List of Potential Errors • Created as we developed the IDEF0 Model • Connected the list of errors to where they could occur within the node list • Examples • Customer forgets to take ATM card back after sign-out process • Customer fails to enter in correct PIN because of layout of keypad • Customer may choose the wrong transaction because of poor viewing conditions

30. Task Analysis • Fill in the following bits of information for ten selected ‘youngest’ children • Purpose/Value Added

31. Task Analysis • Fill in the following bits of information for ten selected ‘youngest’ children • Purpose/Value Added • Location

32. Task Analysis • Fill in the following bits of information for ten selected ‘youngest’ children • Purpose/Value Added • Location • Frequency & Timing

33. Task Analysis • Fill in the following bits of information for ten selected ‘youngest’ children • Purpose/Value Added • Location • Frequency & Timing • Environmental Conditions

34. Task Analysis • Fill in the following bits of information for ten selected ‘youngest’ children • Purpose/Value Added • Location • Frequency & Timing • Environmental Conditions • Information Requirements

35. Task Analysis • Fill in the following bits of information for ten selected ‘youngest’ children • Purpose/Value Added • Location • Frequency & Timing • Environmental Conditions • Information Requirements • Sensory/Congitive/Motor Actions

36. Task Analysis ExampleA221: Choose account to withdraw from

37. HFIRM Analysis • Used the Human Fallibility Identification and Remediation Database (HFIRDB) to identify a formal list of human fallibilities for four of the ‘youngest children’ • Continued our analysis using FMEA

38. FMEA Analysis • Completed analysis for all applicable human fallibilities that were identified using the HFIRM analysis. • This helped us identify the following; • (Other) Contributing Factor(s) • Potential Failure Mode • Potential Effects of Failure Mode • Risk Priority Number (RPN) • RPN = Severity ∙ Probability ∙ Nondetectability

39. FMEA Analysis Example:A221: Choose account to withdraw from

40. Recommendations • Make sure all features are physically accessible by roughly 95% of adults • Redundancy • Use lighted features on ATM to be activated when necessary as well as short video clips to show customer how to use all features • Color coding on command window and keypad • Audio cues to give warning/aid • Proper lighting of the ATM • Glare-free screen • Light attached to ATM for camera use • Group common transactions

41. Questions?

42. References • Adams, A. S., and Thieben, K.A., (1991), “Automatic Teller Machines and the Older Population”, Applied Ergonomics, 22, 85-90. • Burford, B. C., and Stanton, N. A., (1993), “ A User-centered Evaluation of a Simulated Adaptive Autoteller”, Contemporary Ergonomics, London, UK: Taylor and Francis Ltd, 117-122. • Chan, F. Y., and Khalid, H. M., (2003), “Is Talking to an Automated Teller Machine Natural and Fun?”, Ergonomics, 46, 1386-1407. • Mankze, J. M., Egan, D., H., Felix, D., and Krueger, H., (1998), “What Makes an Automated Teller Usable by Blind Users?”, Ergonomics, 41, 982-999. • Norman, D. A., (1998), “The Design of Everyday Things”, Now York, Doubleday.