What are people really trying to say on social media?

Felix Liao
Felix Liao|December 14, 2011

In using social media, I must admit I'm actually a late-comer. I've always wondered what can actually be said in 140 characters on Twitter. However, as I started using social media and embracing it, I've come to realise the power of social media as a communication platform and what the future holds as the technology becomes more mainstream.

As I slowly move up the social media learning curve (and it can be a steep one!) and move beyond tweeting from Twitter and updating my status from Facebook, I've also realised the flexibility such open platforms offer. The huge amount of innovation around social media means that there are now countless ways of working and interacting with social media platforms. In addition, new (and sometimes crazy!) ways of using social media platforms are being discovered and invented every day.

An example of the flexibility and options I am talking about played out as I was trying to send a social media message to my HUGE group of loyal followers across all the different social media platforms a few days ago. I was amazed (and troubled) by the number of considerations I had to make:

  • Who should I share it with? All, work related, family and friends, customers, specific subset of people, should I exclude certain people?
  • Do I make it public or private? Do I want to whole world to know about my message?
  • What platform should I use? Twitter, Linkedin, Google+, Facebook?
  • What tags (or hashtag) should I use with the message? If and what keywords do I want to emphasise in my message?
  • What account should I use to share it? Should I tweet as myself or use our corporate Twitter account?
  • What tools should I use to send the message? At last count, I have at least 20 tools/apps (across the different devices) I can use to send a tweet as I sit at my desk.
  • When should I share it? Let's face it, power tweeters don't stay up 24 hours tweeting to you! There are tonnes of tools to help you schedule or buffer your social media message to get your message across throughout the day!
  • Should I geo-tag the message? Do I want people to know where I am sending the message from?

Granted, not everyone goes through this many considerations when they are trying to tell the world what they had for breakfast, but as more people use social media platforms for content sharing and exerting influence, I think it will be the norm to go through many of the considerations I went through.

So what does that mean for organisations or brands who are trying to use Social Media to better understand their customers or prospects?

Simply put, every single one of the above factors is an important variable that reveals more about my intentions, influence and level of engagement beyond the 140 text characters in the message itself. If there is one thing I learnt about statistics, it's that it’s always good to capture as much information as you can! The ability to mine and better understand your customers increases as you take into consideration more of these signals.

Next time you read another 140 character Twitter or Facebook message, see what else you can work out about the author or the message itself!


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Coping with uncertainty

Evan Stubbs
Evan Stubbs|December 7, 2011

Dealing with the unknown isn't easy. One of the most frustrating things about doing home renovations is that no matter how much you think you may know, reality's more than happy to disagree. Bugs are bugs, and anything that's living in your wood is bad, right? Apparently not - while the difference between termites and ants is pretty obvious (assuming you already knew that one's white and one's black - chalk one up for my stunning ignorance), what's not so obvious is that some termites are apparently happy to stay in one spot while others are happy to colonise your entire house. There's good termites and bad termites. So now you know, and knowing's half the battle ...

Managing a renovation takes a staggeringly large set of skills. Landscapers can't necessarily build the brick retaining walls you need. The bricklayers can't necessarily move the drainage that's in line with their walls. The plumbers can't necessarily fix the tiles they cracked. The tilers can't necessarily re-build the steps that weren't built correctly in the first place. And the builders can't necessarily do any of that - apparently they do something else. Or so they tell me, anyway.

At the end of it all, you deal it with it. You take a deep breath, attempt to reach a point of zen, and move on. The alternative's to start climbing the walls, gibbering and throwing anything handy at the people doing work.

Now, put yourself in the shoes of the person who gave the go-ahead to kick off an analytics project.

Segmentation, predictive modelling, six sigma and quality control, design of experiments, forecasting, optimisation; it's confusing. Making it worse is that while there's often a high-level blueprint, the details are more often than not totally undefined at the start of the project. While the target outcomes may be well understood, the path to get there can seem totally arbitrary to someone not familiar with how analytics works. One of the key challenges analysts usually face is not knowing what the answer is ahead of time - most of the time spent in any analytics project is simply to work out what works!

One of the hallmarks of a good analyst is their ability to happily jump into the unknown based on nothing more than first principles; some of the most innovative solutions stemmed from successfully attempting the impossible! However, that's not the entirety of the picture - one of the hallmarks of a great analyst is their ability to reduce the unknown.

The most transformational analytics almost inevitably involves a leap into the unknowable - if it were easy, someone else would have already done it. The best analysts understand how to reduce this uncertainty for those who aren't "in the know", so to speak. There's nothing worse than an expert that can't build confidence and unfortunately, far too often, we drop the ball in building that confidence.

So how do you build that trust in the unknown? Some of the things to consider include:

  • Break your activities down into a series of milestones. It helps tremendously to understand what you'll be getting when as well as having the option to down tools if insufficient progress is made, regardless of how likely that is to happen.
  • Focus on outcomes, not execution. If your audience doesn't understand the details of non-linear goal-seeking, explaining the technical details is probably just going to scare them. Instead, let them know what they'll be getting - a rough breakdown of recommended campaigns to maximise revenue sounds a lot better than getting a list of constraints and goal-seeking criteria!
  • Devote time to building relationships, not just building models. Trust is easier when they trust you. Trust me on this one ...
  • Leave enough flexibility to try different approaches. Creating a prescriptive project plan seems like a good idea until the approach you've been advocating fails. That doesn't necessarily mean the problem's impossible, it might just be that your preferred approach doesn't work. If you've tied your success to a particular approach, it's almost always impossible to rebuild that breach of trust.

The difference between effectively managing uncertainty and letting fears build is like the difference between night and day. What's worked for you?

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What is analytics?

Evan Stubbs
Evan Stubbs|December 2, 2011

We're having work done on our house at the moment. It's an older place that hasn't had as much maintenance as it should and so while it's not a full rebuild, it's still enough that there's a regular procession of tradespeople ("tradies", to most Australians) around the place. And, if there's one thing I've learned, it's that everyone does a bad job.

Don't get me wrong - most of the time, I can't even see anything out of place! Apart, that is, from our crooked steps that have been rebuilt three times now, but let's not go there ...

Every time anyone looks at work someone else did, we've inevitably heard about how badly it's been done, how they would have done it differently, and how they'd sack their labourers if they did such a dodgy job. At some stage you just have to laugh.

Analytics is the same, even if it seems unrelated. Everyone has a different definition of what "analytics" really means. To some, it's optimising SQL. To others, it's playing with data in Excel. Artificial intelligence, rules engines, statistical analysis, time series analysis, operations research ... if you get ten people in a room, you'll almost inevitably get ten different answers. It's no wonder that people get confused!

Cutting through this Gordian knot is simple - to me, they're all "analytics". Analytics is fundamentally about extracting insight from data, regardless of how that happens. It may be as simple as joining a series of tables to create a single view of customer or it may be as complex as doing integer-based non-linear optimisation to work out optimal shipping paths. Regardless of how sophisticated the analysis may be, they're all about transforming data into information.

The mind-blowing thing is that when you look at it like that, analytics is probably one of the largest technical domains in the world. We're all analysts in some way - the only thing that varies is the level of sophistication that we use. Much like my tiles, actually - I'm sophisticated enough to know a good outcome when I see it, even if I need someone's help to get there in the first place.

For a somewhat distracting (and hopefully entertaining) Friday activity, have a look around your life and count the number of applications of analytics you can find. Trying to optimise your path through the supermarket for Friday night's dinner? Analytics. Counting up Q4 sales and measuring against target? Analytics. Setting up an office pool and making sure everyone has an equal chance to win? Analytics.

It's pervasive. And, that's a good thing - analytics helps us make better decisions. It doesn't replace intuition, but it helps us understand what we do and don't know. It helps us discover those impossible situations that our data suggests exist but, on analysis, quite simply can't. It makes our lives less unsure, every day of the week.

We're all analysts now, even if we didn't realise it.

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Quality, governance and the trustworthiness of data

Felix Liao
Felix Liao|September 19, 2011

imageFor the many years that I have been involved in the area of enterprise information management, I have seen organisations struggle with the issue of data quality over and over again. I have seen the IT departments struggling with the delivery of so called “Data Quality” projects, and I have also seen businesses struggling and complaining about not being able to get access to “Quality Data”.

Seeing that Data Quality technologies have matured over the years and SI’s have become reasonably good at delivering data quality projects, what exactly is the problem?

Among many different factors, I believe the two main reasons that organisations are still struggling with trusted data today are:

“Data Quality technology is not the only component needed to build and deliver trusted data at an enterprise level.

In order to gain trusted data, Business needs to be more involved in the Process along with IT”

That’s where Data Governance comes to the rescue. What data governance provides organisations is a more holistic view and framework in how they manage, control and leverage their data assets so their value can be maximised. It is the missing layer that links the necessary underlying data quality technology to the ultimate goal of trusted data. Specifically the layer that data governance inserts includes the people and process aspects that have been missing in the IT driven, pure data quality projects of the past.

What organisations have come to realise is that Trusted data depends on having a robust data governance framework and that a robust data governance framework will need a flexible, proven set of data quality tools to enforce the processes and rules. You can not have one without the other as they are intrinsically linked to each other.

There is no question that the detail of such undertakings and initiatives can be complex and extensive. If we just focused on the people aspects, things that organisations needs to come to grip now with include:

  • The right level of executive/board level support
  • The right organisational structure to support the initiatives
  • The identification and assignments of data stewards

As a starting point for anyone in charge of delivering any data governance initiatives, the people element is perhaps the most critical and important one to even get the projects off ground. Here are a couple of whitepapers that goes into more detail to help you get started.

I believe that the shift from data quality to data governance is a positive one. It has elevated the discussion to the executive level and is allowing organisations to think about important elements that were missing in previous discussions or projects.

With the right foundational components and the involvement of business through the appropriate process, I believe organisations will be one step closer to delivering trusted data throughout the enterprise.

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Dude, where's my laptop?

Patrick Spedding
Patrick Spedding|September 14, 2011

Right of the Date Line...

So this is the first overseas trip in recent memory where I do not have a laptop with me. It feels strange. You might say, a bit of a gamble...
No laptop? Bit of a gamble...

It doesn't seem so long ago that "Mobile BI" was realistically BI running on a laptop and the early attempts at BI on smartphones really little more than a gimmick. Security was typically the first objection raised (either "I don't want corporate data stored on a mobile device" or "I don't want my corporate data stored offshore" such as in Canada ... ).

Adoption rates of mobile devices are far outpacing previously observed adoption rates of Internet or desktop-based technologies. In fact, Gartner predicts 1/3 of BI content will be consumed on mobile devices by 2013.

So why the rapid adoption? First and perhaps most importantly, the increased "form factor". Smart phones were really too small for interfaces of much sophistication but with the advent of the iPad and other tablet devices, we now have an interface large enough for "real" applications. Secondly, improvements made around security (more if this in a moment). Add in the potential for improved productivity (faster time to decisions, end-user self-service) and we are finally starting to see the "democratization" (is that a word?) of BI.

One critical area for BI vendors to get right right is the UI itself. My 4 year old son is already a proficient iPad user and if an iPad App doesn't work the way he expects (ie natively, supporting gestures like pinch and zoom), then he exits out in disgust and declares, "It's broken!". So treating mobile devices like "just another interface" or 'supporting' mobile devices via the browser rather than a native App has the potential to create user dissatisfaction. As Lalitha Chikkatur recently wrote: “The important thing to remember ... is that mobile BI is not just a mobile version of traditional BI; it is a mistake to overlook the unique considerations required for implementation.’’ (“10 Mistakes to Avoid in Mobile BI Delivery”, Information Management).

A key challenge in the past has been security. Mobile device vendors are finally starting to address these concerns, reducing the barriers to adoption from corporate IT. Seven device policies are currently supported:

  1. Require email session encryption.
  2. Wipe devices if they are lost or stolen.
  3. Protect devices with a passcode lock.
  4. Autolock devices after periods of inactivity.
  5. Autowipe devices after failed unlock attempts.
  6. Protect the configuration profile.
  7. Continuously refresh policies.

With Enterprise Security improved, reduced cost (compared to, for example, laptops), improved/unlimited data plans (in some countries at least!), and an improved form factor enabling business applicability, it is easy to see why analysts are predicting such a huge uptake in Mobile BI over the next few years:

“Forrester predicts that this future generation of mobile devices will eclipse the use of traditional laptops for mobile BI applications within three to five years”
(Boris Evelson - A Practical How-To Approach To Mobile BI, March 2011)

Here in the US, I'm finding that WiFi is available, for free, in many places eg malls, shops, hotels - thus enabling me to avoid the need to activate my iPad SIM (and incur very expensive Australian data roaming charges).

Free WIFI
Here in the US, I'm finding that WIFI is available, for free, in many places eg malls, shops, hotels - thus enabling me to avoid the need to activate my iPad SIM (and incur very expensive Australian data roaming charges).

With VPN, secure 'Cloud' data solutions like Dropbox and iDisk, and Office-compatible and other related business Apps on my iPad (including Roambi ES for SAS!!), I hope to find that I'm not missing my laptop too much. Let's see how that goes ...

Update:

Here are some things that I've noticed after a week or so with only my iPad and iPhone....

  • WiFi is not always reliable. While some may advocate a WiFi-only infrastructure strategy as 'good enough', I have found it at times frustrating to not be able to 'plug in' to broadband via Ethernet (wired) where available. In fact, in some hotels wired Ethernet is the only option. Pro-tip: Travel with a small wireless router such as the Apple Airport Express for such situations!
  • No ability to save-as or print to PDF. It makes it difficult to do things like saving online invoices, confirmations, sharing reports, and so on.
  • No access to Flash-based web apps or online Flash content. While this may become less of an issue as HTML5 matures, for right now it's an inconvenience.
  • Spreadsheet functionality is limited. I have a spreadsheet App installed on my iPad, but it does not offer full spreadsheet functionality. With spreadsheet use still so prevalent within organisations, I could see such limitations being an issue for some business users. In fact, In my recent survey of over 200 Australian managers and executives, I found that 90% still use spreadsheets for their reporting needs. This may be somewhat due to limitations with traditional BI solutions; newer BI capabilities such as SAS Add-in for Microsoft Office (AMO) now offer much tighter integration with Office components such as Excel, so I would expect to see this rate reduce over time.

Overall, I have found that I've missed my laptop for some of the reasons above. This leads me to wonder whether the estimates of Gartner/Forrester and others predicting such high adoption of BI on mobile devices within relatively short timeframes to be perhaps optimistic? While this could be possible in countries with extensive (free) WiFi for mobile business users, in other countries where WiFi connectivity is patchy or expensive, it may be that Mobile BI adoption could be somewhat slower.

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Oceans 10.9

Brendon Smyth
Brendon Smyth|August 29, 2011

PEP BoysLast week’s announcement of the $US10.9m levied on Miami-based Ocean Bank for violations US anti-money laundering (AML) laws and regulations highlights the risks associated with doing business with high risk geographies and politically exposed persons (PEPs).

According to a recent report by My Private Banking, twenty five of the most well-known PEPs (including former Tunisian president Zine El Abidene Ben Ali, Libyan leader Muammar Gadhafi and former Egyptian President Hosni Mubarak) allegedly hold $140 billion in assets but only 5% of these assets have been frozen.

Proposed changes to current PEP provisions
The United Nations, World Bank and Financial Action Task Force (FATF) are seeking adoption of a broader definition of "politically exposed persons" under the United Nations Convention Against Corruption (UNCAC). This definition extends the definition to a PEP to include both foreign and domestic figures and any individuals or companies "clearly related" to them.

In addition, the three organisations are seeking changes to AML controls in relation to PEPs currently implemented by financial institutions including eliminating the distinction between foreign and domestic PEPs; annual review of PEP bank accounts; and sharing suspicious activity reports on the accounts of foreign politically-tied figures with their home country.

Impact on financial institutions
The proposed changes will place a greater regulatory burden on financial institutions in monitoring PEP accounts and require a rethink of the typical minimalist approach to technology investment for AML/Economic Trade Sanctions compliance. Increasing staffing costs arising from existing inefficient AML/Sanctions processes and controls will be compounded by the complexity of the proposed PEP changes.

To reduce the cost of AML/Sanctions compliance, financial intuitions need to take an integrated approach to compliance supported and enabled by a technology platform that offers the following capabilities:

  • Captures and organizes all customer activity across disparate data sources.
  • Monitors that activity against multiple rules, scenarios and risk factors.
  • Uses analytically derived indicators of risk, not just simple rules and matches.
  • Accurately alerts compliance staff to potentially suspicious activity.
  • Provides a structured environment for investigating and documenting alerts.
  • Generates required regulatory reports and supporting documentation

A risk-based monitoring and investigation system is a vital component of an effective, efficient, integrated and compliant AML/Sanctions program.

Will the proposed changes be effective?

Does your organisation take an integrated approach to AML/Sanctions compliance?

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Guess who is rated number one in Data Quality again?

Felix Liao
Felix Liao|August 25, 2011

DataFlux_Logo According to the latest Gartner Magic Quadrant for Data Quality, DataFlux (a wholly owned subsidiary of SAS) continues to be the market leader when it comes to Data Quality. I say “Continue” because DataFlux has been in that same leadership position for the last 3 years!

Why is this important and what does it mean for our customers? Well, to say that Data Quality is the foundation of everything BI or Analytics related is more or less a given and old news these days. The challenges around delivering trusted data to downstream reporting or analytical processes have always been there and are becoming more critical as the need for more accurate reporting and timely insight intensifies. What’s more, many organisations are also undertaking new initiatives that all needs to be built on the foundation of sound Data Quality processes and capabilities.

1. Data Governance

Organisations that recognise the importance of data as a strategic asset and a key competitive advantage almost inevitably kick off “Data Governance” projects or initiatives. Sometimes it's because off the back of good, proactive executive leadership, sometimes off the back of looming regulatory and compliance needs. While a sound data governance program should involved the combination of people, process, methodology, and technology, Data Quality should form the foundational component of any technology discussion. A good, robust  data governance framework is critical for overall long-term success but should also deliver at least some key outcomes in the form of specific Data Quality metrics that data stewards can work with.

2. Customer Centricity

As industries and markets mature, the ability to win, keep and profit from your existing customers becomes more important than ever. Customer centricity is often quoted as the number 1 strategic initiatives by CIOs today. It doesn’t take a genius to work out that customer centricity requires an organisation to obtain a single consolidated view of their customer across multiple business and product lines. Are some organisations there? Yes, but dare I say most organisations are not. Data Quality and the ability to consolidate entities are the foundation to customer centricity, a key reason why they often form the foundation of any Master Data Management solutions.

3. Application migration/consolidation

This one is often forced upon the IT team, but unfortunately it is more than likely happening in your organisation as we speak. The fact that the these projects often have an absolute deadline that can not be moved means they're often high risk. All too often, the systems that need to be moved or consolidated often have little documentation (that is if there are still people who know the system at all!). Managing risk requires the organisation to understand what information is actually in these systems. Data Quality offers a way to automate the process of cleansing the data to be loaded; not only does only correct data get loaded but projects can also be delivered on time.

At SAS, we believe that Data Quality is critical in helping our customers solve complex problems and challenges such as the ones mentioned above. It's one of the reasons why it's a foundation piece of our extensive data management portfolio. It's great that Gartner agrees that we have the best tool in the market, but it's about more than that. We also have the right people with the right know-how, something that's critical in helping customers solve their most complex business problems.

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How much is happiness worth?

Evan Stubbs
Evan Stubbs|August 24, 2011

Just because every sector can benefit from Business Analytics doesn't mean that it's easy. I always find applying analytics in the public sector a fascinating challenge - in the commercial sector, it's normally fairly easy to identify the value being created. Revenue uplifts, deferred investments, cost reductions; these are all well understood and with sufficient consideration, are normally pretty easy to quantify.

In the public sector though? It's hard. Sometimes really hard. How much is happiness worth? Or a human life?

Regardless of whether you believe in big or small government, the public sector has the opportunity to play a role in eliminating market failure and increasing public aggregate utility. How it does that in an efficient and effective manner is a never-ending  political (and normative) debate, one that's of less relevance in this context. And, frankly, one I'm less interested in - pragmatically speaking, I help solve problems, not run governments!

No matter your political leanings, the public sector exists, we pay tax, and for everyone out there working for a government department, analytics offers a path to delivering better outcomes given the same budget. Where things get fuzzy though is how you measure "better" outcomes. One really interesting example involves trying to make everyone better off, something which few would disagree with were it a policy objective.

Not surprisingly, there's a rich set of material out there to help guide policy-makers. There's a concept in welfare economics known as 'Pareto optimality' - it's the point where no-one could be made better off without making someone else worse off. In isolation, that sounds like a decent goal - make everyone happier!

Needless to say, there's a few problems with this. The biggest is that utility is subjective. Is my happiness worth more than yours? Does giving us the same amount as a baby bonus create differing amounts of utility if one of us is wealthier than the other? If so, what's the relationship between utility and wealth? Does the utility change if I already have kids?

If that weren't enough, utility is generally considered to be ordinal, not cardinal. In layman's terms, it means that it can't be quantified, only ordered. I can't say how happy my 50" plasma makes me, but I can sure say that it made me (and my back) a lot happier than my old 36" CRT.

Despite such a rich set of theoretical and structured literature, that simple goal of making people happy rapidly becomes very difficult to quantify. For those working in policy development, these are very real challenges. Justifying the use of analytics based on the creation of value often requires different approaches to those used in the private sector. And, from my perspective, they often represent some of the most innovative applications of measuring value around.

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A/NZ Business Intelligence survey 2011

Patrick Spedding
Patrick Spedding|August 22, 2011

Last week, I attended the announcement of the Longhaus Pulse Research on BI and Analytics for 2011. Longhaus Pulse is the most comprehensive and regionally focused assessment of the Business Intelligence and Analytics market in Australia.

One area I found interesting was Longhaus Managing Director Peter Carr's observations around the evolution of the Business Intelligence market. Having worked in the BI industry for almost 20 years, this is something I can definitely relate to. Peter compared the current exciting trends around "Next Generation BI" to the prevalent trends of the 1980's, 1990's and 2000's. Right now, Peter observed, trends around "Cloud" and Social Media are "putting the power back into the hands of the knowledge workers". It's certainly interesting that the "Next Generation BI" trends are all around Data Visualization, End User Self-Service, and Mobility (Mobile access to information). In other words, empowering the business user. (Funny, I thought we already had that in the 90's...). Unfortunately, the 2000s became about "BI Standardization", Portals and the like which were all heavily IT-centric. In the process, BI vendors perhaps lost sight of what BI was all about. Enabling users to get access to the Right Information, at the Right Time, to make Better Decisions. Longhaus talk about the "Digital Divide", with BI technology outpacing end-user capability/need (just how many 'Studios' do I actually need to get access to my information???)

The consequence? Spreadsheets. And more spreadsheets. Spreadsheets everywhere.

The problem with this? Disparate data silos. Poor data integrity. Lack of an audit trail. Lost productivity. Inability to make timely, fact-based decisions.

Which brings me to my recent survey of BI trends in A/NZ. Covering all industries and geographies across A/NZ, I received 230 responses (7% response rate). What became clear from the results was that BI, although assumed to be mature and pervasive, had not solved the Reporting problem in most organisations. For example:

  • Disparate Systems and Poor Data Quality are still views as the biggest challenged faced when relying on data to drive performance.

  • 90% of respondents state that spreadsheets are still being used as part of the query & reporting process

  • More than 1 in 4 spend 5 or more days each month preparing regular reports (ie one week of every month)

  • Over 60% rely on others or have no ability to create their own ad-hoc reports

    • Most surprising of all, 40% are currently evaluating (or re-evaluating) their BI vendors, with a further 26% planning to do so within the next 12 months.

    Good news for SAS, named by Longhaus as the No.1 BI Vendor in Australia for 2011 ("Longhaus names SAS institute BI as No 1 vendor"), as we heed the message of frustrated users, and focus on empowering the Knowledge Workers to solve complex business problems. Intuitively. And fast.

    For anyone interested in my full survey results report, I can be contacted at pjs@sas.com

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    Comprehensive credit reporting - are you ready?

    Suren De Silva
    Suren De Silva|August 16, 2011

    Comprehensive credit reporting is expected to be introduced into Australia within the next 12 to 18 months. This new regime will enable credit providers (banks, building societies, credit unions, telecommunication companies, etc.) to significantly change how they assess credit risk and target new customers. The time is now to complete planning for changes to policies, processes and systems.

    Are you ready to use the next 12 to 18 months wisely?

    Impact for credit providers:

    Adapting existing processes and systems to comprehensive credit reporting regime will require significant investment by credit providers but the business case is strong.

    Some of the changes required include:

    Credit risk assessment approach

    Current retail credit application scorecards used by Australian credit providers assess risk based upon negative information. Current limitations result in selection of some bad borrowers (i.e. potential loan defaulters) while ignoring some “good customers” who could have been profitable customers.

    Credit providers will need to changes existing credit assessment processes and decisioning models in order to effectively utilise the positive credit information to extract a competitive advantage.

    Compliance with National Consumer Credit Protection laws

    Access to information about existing lines of credit, credit balances and actual payment history will make it easier to credit providers to comply with the responsible lending conduct requirements. In particular, the additional data can be used to help validate whether the consumer has the capacity to repay.

    Data management

    Under the current credit reporting regime, credit providers can only obtain information about where an individual or organisation has applied for credit and details of derogatory incidents that may have occurred over a 5 to 10 year period.

    Under a comprehensive credit reporting regime credit reporting agencies (like Veda and Dunn and Bradstreet) and credit providers will be able to collect and share individual information about existing lines of credit, exposure levels and actual payment history.

    Credit providers will need to provide credit reporting agencies with updated credit balances on active credit accounts and payment details at periodic intervals. Credit providers will need to make significant change to existing processes and systems in order to collect, share and utilise this additional pieces of data.

    Targeted marketing campaigns

    Changes to existing marketing processes and systems should be made to take advantage of the new data. Credit providers will have access to data on existing credit products individuals or organisations have with other credit providers. This new data can be used to structure more targeted marketing campaigns and offers to existing customers and for new customers to change credit providers.

    The time to prepare is now not when the legislation is finally enacted. First movers will gain significant advantage. Are you ready?

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    • About this blog

      In many ways, Australia and New Zealand are unique - we live a day in the future, our birds walk and our mammals lay eggs. However, one thing we have in common with the rest of the world is the need to be globally competitive while staying local. On this blog, Evan Stubbs and his colleagues provide a uniquely ANZ perspective on doing business, using analytics to be more effective, and life in the antipodes in general.

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