Data Management (submission) Flashcards
1
Q
Talk me through how you created a new job file for your valuation in Berwick, and how this ensured the data was stored accurately and efficiently.
A
- Collected information from client – client name, asset address, type of instruction (e.g. Val/L and T etc.)
- Collated information – created unique job number identifier for instruction which was connected to instruction information
- Label and Store – added new entry to password protected Excel Instruction Record database (searchable fields for sorting/searching purposes) and created new physical file for storage in office secure locked cabinet filing system and digital file (instruction type -> area -> sub-area -> titled with address and surveyor initials), which matches client information (job number, client name, property address, surveyor assigned, instruction type, DATE),
- Retrieve and Share – searchable fields in Instruction Record allows for retrieving of physical/digital files at later date due to filing system organisation.
2
Q
Talk me through the external data systems you used for your Berwick instruction, and how you ensured security.
A
- Planning history and listing status from the Local Authority planning portal and Historic England – provided details of the enquiries I had undertaken and the results in the report. (in Conservation Area, in retail zone, Grade II listed)
- Flood risk from the Environmental Agency – Flood Zone 1
- Business rates from the Valuation Office Agency – not much to say really, stated current entry from 2017 listing in report.
- EGI, EIG and the Land Registry to obtain rental and sales evidence, seeking verification from the agents involved to ensure data accuracy –
o Used filtering systems on EGI and EIG to find most recent transactions within Berwick town centre for retail.
o I call agents when gaining information from secondary sources such as EGi, and where possible cross check with the Land Registry sales/lease records for verification. Where information cannot be verified I placed appropriate risk and caveats on the use of these (within the report). - Stored electronically on our password protected valuation instruction file system.
- Inspection information – converted electronically – scanned inspection notes and uploaded photographs to system, clearly labelled.
- Electronic file is accessible to only the valuation department, and sensitive documents (i.e. confidential client information) are password protected.
- Paper files were kept in a locked filing cabinet whenever I was not actively working on the instruction.
3
Q
Talk me through how the data was presented for your Berwick instruction.
A
- The comparable evidence was presented in a client friendly table format incorporating my analysis and comments.
- Headings included: address, date, description, size, price/rent/psf/yield, comments
- Comments provided brief analysis of comparable compatibility with subject property, and any other notable features of the property or transaction
- Included source of all information used
- This allowed my client to understand the market/evidence, how it relates to the subject property and the limitations of the information gathered.
4
Q
Washington – why did you advise that an AVM would produce inaccurate results?
A
- An AVM uses mathematical modelling to produce a valuation figure.
- Client was considering use of HomeTrack, leading AVM in UK often used by lenders for residential property.
- Benefits include speed and cost, but:
o Limited by data inputs – in this instance there are a variety of characteristics that an AVM would not take into account properly – garden sizes, internal specification (most variable and of value for new build properties), locational differences, and differences between second hand and new build premiums.
o Speed and cost – useful for large portfolios of simple valuations where variations typically even out – in this instance the scenario is reversed – client had specific focus on multiples of several house models, and therefore required logical thinking of a human to consider the market differences, and why certain property sizes/models do not perform as well/are not comparable with properties that seem to be similar at face value nearby.
5
Q
Washington – talk me through the Excel workbook you created/what data was inputted?
A
- Tabs for each house model.
- Collated comparable data including prices, sizes, property features and marketing durations from the Land Registry, EPC Register and Rightmove Plus:
o Address
o Date
o Internal features – internal order quality, bedrooms/bathrooms/reception rooms etc.
o Size – sq m from EPC, or from marketing particulars
o External features – garden size, driveway, garage
o Tenure – freehold or long leasehold, and terms
o Price paid and marketing history – can be used to estimate length of marketing period, in years/months. - Verified data with agents where possible.
- Each tab included schedules for new build and ‘second-hand’ sales – ascertained from LR sales history, allowed comparison of difference, to establish difference in new build premium.
- The spreadsheet calculated both the average and lowest/highest prices psf and marketing durations for each house model:
o Used SUM and AVERAGE functions to calculate.
o This enabled me to clearly present the differences in selling prospects for each housing type, and advise on which appeared to be the best choices for an end value perspective, developer could then decide:
• Which housing types provide the highest profit margin and selling period, and the certainty of the figures/potential variance for their own development appraisal purposes and sensitivity analysis.
6
Q
Washington – how did you analyse the market conditions and advise your client?
A
- Analysed the market conditions in my report:
o Map of comparable schemes and comparing average sales per week: each competing scheme clearly labelled in appended map, with commentary on differences in average sales per week, location, and mix of housing models/how that effected the average sales per week.
o Additionally I provided commentary on how the different housing models would perform, taking into account the performance of other schemes/housing types they offered and more broadly how competing nearby locations performed generally, and how that would broadly compare to the subject location/purchasers preferences in house types between the areas.
o This enabled me to clearly present my advice on which models should perform best and how the scheme could be improved.
7
Q
Washington – how did you ensure security?
A
- Data was stored in password protected Excel and Word report – provided client with password
- Market data was publicly available, however the clients plans for development were highly confidential and therefore password protection was important.
8
Q
Affluent suburbs Newcastle – talk me though why you advised a colleague to create a database and what you included in the database.
A
- Valuation department regularly receive instructions from a retained lender to value houses in the most affluent suburbs of Newcastle:
o Darras Hall, Gosforth, Jesmond - The client typically requests additional market commentary as changes in purchaser activity can have a significant impact on marketing periods and house prices:
o Typically under 10 sales per year, and very limited number of buyers in the market. Buyer needs at this level also change often, sometimes want very large houses, or a pool, or large landscaped grounds. At other times these features are lower priority, particularly as they have a significant impact on the running and maintenance costs of the property. - Filtered and extracted data from a number of datasets including the Land Registry, EPC Register and Rightmove Plus to collate every property sold or marketed above £1,250,000 since 2015:
o Chose 1.25m as below this level there are typically more sales, a wider range of purchasers, and fewer unique features, and therefore more predictable market with more rational values, less uncertainty in value of additional features.
o Chose 2015 for two reasons:
• Market activity prior to that arguably of no particular relevance, too far back in time.
• Retained lender rarely requests revaluations more than 5 years prior. - The data includes asking and achieved sale prices, floor areas, internal and external features, and marketing durations:
o Included areas as additional field – Gosforth, Jesmond, Darras Hall – enabled benchmarking of average price psf/marketing durations/number of sales by year.
o Asking and achieved prices/marketing durations: enables me to benchmark differences between – in this market often current properties OTM have asking prices that are far above Market Value. Can use this data to help demonstrate this difference to client.
o Floor areas: EPC areas, or from agents (preferable).
o Plot size: from LR title plan.
o External features: garage, landscaped gardens, driveway etc.
o Internal features: modern or period, high quality or not.
o Capital rates = calculated from size and price
o Used SUM and AVERAGE functions to calculate differences by year, and by area.
o Includes SORT function fields if want to isolate specific features etc. (USEFUL FOR OTHER FIRM SURVEYORS FOR REPORTING)
• Provides ability to drill down into specific features – could look for houses in Gosforth of a certain size, or properties in all 3 areas that had sold above a certain level over a specific time period, for example. - Verified data with agents, and included source of information and any limitations within the Excel database.
- Database is password protected with access limited to valuation team – updated monthly by myself and provides useful reference for other firm surveyors (comparable evidence and market analysis).
9
Q
Affluent suburbs Newcastle – how did you advise your client within recent Darras Hall report?
A
- I made reference to the database within a recent Darras Hall valuation report (something Runnymede road) in order to clearly communicate why the Market Value was now lower than previously reported in 2015.
o Included commentary on how market had performed over 5 year period, with marketing periods of under 1 year in 2015, up to 2+ years in 2020.
o Highlighted certain sales/features of properties – to show client that modern larger houses like subject with extensive external features (big garage/driveway, pool) have fallen in value and demand much more than smaller period properties with mature trees etc.
o Additionally (in table format) was able to show that sales in Gosforth/Jesmond can be misleading evidence for Darras Hall, mainly due to DH being a less established location, and a drop in popularity of larger modern houses v smaller period houses.
o This also enabled me to demonstrate that current asking prices for similar houses were not congruent with marketing history of similar properties in previous years, many of which either sold significantly below asking, or were removed from the market after 1-2 years, or had remained on market for even longer. - I advised that capital rates and demand for properties in this size range had fallen significantly, with marketing periods of over 2 years and fewer completed sales.
10
Q
CM – how does it monitor mailshot engagement?
A
- States % opened/DL’d full particulars/unopened, can be monitored over time and against other properties (useful for client feedback on how property being received).
11
Q
Agency file notes – how do you verify this information, and keep it confidential?
A
- Discuss with client and obtain permission. Also advise client that if they wish to make any alterations I should be contacted. I then require client permission to disclose information when I receive an enquiry.
- Password protected Word doc (File – Protect Document – Encrypt with Password), limited to agency team who are aware of the data protection compliance requirements.
12
Q
CM - How long can you use personal data for?
A
For no longer than is necessary for the purposes for which it is being processed.
Or until the person requests erasure
13
Q
CM - Why is it important that you included an unsubscribe link?
A
Under GDPR – require consent, consent must be able to be withdrawn at any time. Allows clear and simple opt-out.
14
Q
Mailshot list: demonstrate how you met the principles of GDPR/how does CM comply with GDPR?
A
- Processed lawfully and fairly & 2. Purpose of the data collection is specified, explicit and legitimate:
a. The sign up form for the mailing lists is granular, with positive opt in tickboxes for each mailing list
b. The form also notifies users of how their data will be used (solely for marketing particulars, stored securely and not shared with any other businesses) – inc. link to JT privacy policy - Data processed must be adequate, relevant and not excessive for the purpose it is held:
- Requested full name and email address in order to send details of and discuss the opportunity. Did not require any further information, although users have option to provide phone no. if needed. - Accurate and up to date & 5. Held no longer than necessary:
- CM mailshots have embedded links to allow recipients to unsubscribe and alter contact details.
- CM notifies when users have unsub’d/bounced, allowing me to securely delete all info we hold that is no longer necessary.
- Right to retrieval/rectification embedded in CM – support contact form embedded into emails – from their users can follow process - Ensure appropriate security of personal data: CM is GDPR compliant cloud service, database is password protected, and securely held by 3rd party, with no sharing with other services etc.
15
Q
How does JT ensure the security on confidential/sensitive information?
A
Defence in depth strategy - multiple layers of security controls, if one fails the next kicks in.
- Web proxy/filters
- Antivirus solution for all company devices
- Email filtering (blocks malicious emails and attachments/links)
- Firewalls - inspect internet traffic and block malicious network pack
- Vulnerability management tools - identify vulnerabilities in software/operating system so they can be patched.
- Advanced threat detection tools - identify advanced persistent threats.
