The new productivity tools

With every new app I download, install or have to use, I keep asking myself: “Do I feel more productive than I did before I downloaded it?” Comparing notes with a business associate the other week, I realised that the arsenal of daily tools I use continues to expand since I last blogged about this topic. At times, I feel like Charlie Chaplin in “Modern Times” trying to keep on top of this digital production line.

Image sourced from Wikimedia Commons

In particular, the number of communication tools (instant messaging and conferencing) keeps growing; document and file management continues to be a battle largely between operating systems; and most collaboration tools struggle to make the UI as seamless as it should be – so that the UX is all about the “process” for creating, updating and maintaining projects, and not the quality of outcomes.

So, as an update to my previous blog, here’s a few thoughts on recent experiences:

Meetings/Chat

Added to my regular list are Telegram, WeChat, UberConference, BlueJean and RingCentral. Meanwhile, Microsoft (Skype), Google (Hangouts) and Apple (FaceTime) all compete for our communications. (Even Amazon has its own conferencing app, Chime.) One of the biggest challenges I find is browser compatibility (when using via a desktop or laptop) – presumably because vendors want to tie you into their proprietary software eco-systems.

Project Management/Collaboration

Still looking for the perfect solution…. Products are either so hard-coded that they are inflexible, or so customisable that they can lack structure. I suspect that part of the problem is projects are still seen as linear (which makes sense from a progress and completion perspective), but we collaborate at multiple levels and tasks (with corresponding inter-dependencies), which don’t fit into a neat project timeline.

Document/File Management

I seem to spend most of my day in Google Drive (largely thanks to Gmail and Drive) and Dropbox (which continues to improve). I find Dropbox more robust than Google Drive for file management and document sharing, and it continues to expand the types of files it supports and other functionality. Whereas, with Drive, version control is a bit clunky, unless the document was first created in Google Docs.

Productivity

Overall, Google Docs is still not as good as MS Office (but does anyone use OneDrive, let alone iCloud/iWorks, for document sharing or collaboration?)

One thing I have noticed is that my use of native iOS productivity tools has dropped off completely – if anything, I am now using more MS Office iOS apps (e.g., Lens, OneNote), and some Google Docs apps for iOS. Plus the DropboxPaper iOS app.

CRM

I’m starting to use Zoho (having outgrown Streak) – and I’ve heard that there is even a Zoho plug-in that connects with LinkedIn, which I shall soon be exploring. But as with Collaboration tools, getting the right balance between rigidity and flexibility is not easy.

Next week: The first of three musical interludes….

 

Big Data – Panacea or Pandemic?

You’ve probably heard that “data is the new oil” (but you just need to know where to drill?). Or alternatively, that the growing lakes of “Big Data” hold all the answers, but they don’t necessarily tell us which questions to ask. It feels like Big Data is the cure for everything, yet far from solving our problems, it is simply adding to our confusion.

Cartoon by Thierry Gregorious (Sourced from Flickr under Creative Commons – Some Rights Reserved)

There’s no doubt that customer, transaction, behavioral, geographic and demographic data points can be valuable for analysis and forecasting. When used appropriately, and in conjunction with relevant tools, this data can even throw up new insights. And when combined with contextual and psychometric analysis can give rise to whole new data-driven businesses.

Of course, we often use simple trend analysis to reveal underlying patterns and changes in behaviour. (“If you can’t measure it, you can’t manage it”). But the core issue is, what is this data actually telling us? For example, if the busiest time for online banking is during commuting hourswhat opportunities does this present? (Rather than, “how much more data can we generate from even more frequent data capture….”)

I get that companies want to know more about their customers so they can “understand” them, and anticipate their needs. Companies are putting more and more effort into analysing the data they already have, as well as tapping into even more sources of data, to create even more granular data models, all with the goal of improving customer experience. It’s just a shame that few companies have a really good single view of their customers, because often, data still sits in siloed operations and legacy business information systems.

There is also a risk, that by trying to enhance and further personalise the user experience, companies are raising their customers’ expectations to a level that cannot be fulfilled. Full customisation would ultimately mean creating products with a customer base of one. Plus customers will expect companies to really “know” them, to treat them as unique individuals with their own specific needs and preferences. Totally unrealistic, of course, because such solutions are mostly impossible to scale, and are largely unsustainable.

Next week: Startup Governance

 

Spaghetti in the Cloud

The combo of Cloud+Wireless+Mobile has transformed the way I work. For one thing, storing, accessing and sharing documents is now so much easier than having to send everything as bulky e-mail attachments tethered to a hard drive. However, as an independent consultant, with every new project, business or client I work with, I find I need to use different collaboration tools to be compatible with their workflow, IT systems or platform preferences. Great as all these collaborative apps are, the fact that many don’t talk to one another makes it feel like I am being sucked into a mess of virtual cables that don’t interconnect. Sort of “Spaghetti in the Cloud”.

Image sourced from Flickr

It feels like all my apps are unconnected yet tangled up in the Cloud (Image sourced from Flickr)

There is definitely a battle to dominate enterprise collaboration, with Facebook’s recent launch of Workplace to compete with the likes of Slack, the anticipated revamp of Microsoft’s Office 365 Groups when Yammer is decommissioned in early 2017, and Atlassian’s own HipChat. But aside from enterprise social media and chat, there is now competition across multiple collaboration tools. Here is a list of just a few of the productivity apps I have been exposed to across the various projects I work on:

Meetings/Chat

  • Skype for Business (formerly Lync)
  • Google Hangouts
  • Zoom
  • Cisco WebEx for iOS
  • GoToMeeting
  • Fuze
  • Join.Me
  • WhatsApp

Project Management

  • Samepage
  • Mightybell
  • Basecamp
  • Trello
  • Smartsheet

Document/File Management

  • Dropbox
  • OneDrive
  • Google Drive
  • FileApp (iOS)
  • FileManager Pro (iOS)
  • Docs To Go (iOS)

Productivity

  • Google Docs
  • Apple iWork
  • Microsoft Office 365
  • SlideShark

CRM

  • SalesForce
  • Insightly
  • Streak

And this list doesn’t include single-purpose apps like POP, Simplist and Ideament that allow some project sharing; the entire suite of creative, social media, blogging and CMS tools that organisations increasingly embrace as enterprise solutions; and the growing number of apps that support text, photo and video editing on mobile devices.

While some of these tools support content, file, document and even project sharing from within the app, a lot of functionality is native, and therefore embedded, and is not transferable. So I end up having to learn (and unlearn) the features, quirks and limitations of each one, project by project, client by client.

As I have written before, based on my experience of creating digital music (plus using and beta-testing iOS apps), an app like Audiobus set the standard for product compatibility and content integration. So much so, that Apple ended up supporting Inter-App Audio as a new standard for iOS. Since Audiobus, similar apps have emerged that allow audio and MIDI apps to run together on a single device, and to share/stream content between different mobile devices and desktop DAWs (Digital Audio Workstations): Midiflow, musicIO, AudioShare, AudioCopy, Audreio, studiomux etc.

If only enterprise software and productivity app developers would have a similar approach to product design and collaboration….

Next week: StartupVic’s Pitch Night for October

 

Assessing Counterparty Risk post-GFC – some lessons for #FinTech

At the height of the GFC, banks, governments, regulators, investors and corporations were all struggling to assess the amount of credit risk that Lehman Brothers represented to global capital markets and financial systems. One of the key lessons learnt from the Lehman collapse was the need to take a very different approach to identifying, understanding and managing counterparty risk – a lesson which fintech startups would be well-advised to heed, but one which should also present new opportunities.

In Lehman’s case, the credit risk was not confined to the investment bank’s ability to meet its immediate and direct financial obligations. It extended to transactions, deals and businesses where Lehman and its myriad of subsidiaries in multiple jurisdictions provided a range of financial services – from liquidity support to asset management; from brokerage to clearing and settlement; from commodities trading to securities lending. The contagion risk represented by Lehman was therefore not just the value of debt and other obligations it issued in its own name, but also the exposures represented by the extensive network of transactions where Lehman was a counterparty – such as acting as guarantor, underwriter, credit insurer, collateral provider or reference entity.

Before the GFC

Counterparty risk was seen purely as a form of bilateral risk. It related to single transactions or exposures. It was mainly limited to hedging and derivative positions. It was confined to banks, brokers and OTC market participants. In particular, the use of credit default swaps (CDS) to insure against the risk of an obiligor (borrower or bond issuer) failing to meet its obligations in full and on time.

The problem is that there is no limit to the amount of credit “protection” policies that can be written against a single default, much like the value of stock futures and options contracts being written in the derivatives markets can outstrip the value of the underlying equities. This results in what is euphemistically called market “overhang”, where the total face value of derivative instruments trading in the market far exceeds the value of the underlying securities.

As a consequence of the GFC, global markets and regulators undertook a delicate process of “compression”, to unwind the outstanding CDS positions back to their core underlying obligations, thereby averting a further credit squeeze as liquidity is released back into the market.

Post-GFC

Counterparty risk is now multi-dimensional. Exposures are complex and inter-related. It can apply to any credit-related obligation (loans, stored value cards, trade finance, supply chains etc.). It is not just a problem for banks, brokers and intermediaries. Corporate treasurers and CFOs are having to develop counterparty risk policies and procedures (e.g., managing individual bank lines of credit or reconciling supplier/customer trading terms).

It has also drawn attention to other factors for determining counterparty credit risk, beyond the nature and amount of the financial exposure, including:

  • Bank counterparty risk – borrowers and depositors both need to be reassured that their banks can continue to operate if there is any sort of credit event or market disruption. (During the GFC, some customers distributed their deposits among several banks – to diversify their bank risk, and to bring individual deposits within the scope of government-backed deposit guarantees)
  • Shareholder risk – companies like to diversify their share registry, by having a broad investor base; but, if stock markets are volatile, some shareholders are more likely to sell off their shares (e.g., overseas investors and retail investors) which impacts the market cap value when share prices fall
  • Concentration risk – in the past, concentration risk was mostly viewed from a portfolio perspective, and with reference to single name or sector exposures. Now, concentration risk has to be managed across a combination of attributes (geographic, industry, supply chain etc.)

Implications for Counterparty Risk Management

Since the GFC, market participants need to have better access to more appropriate data, and the ability to interrogate and interpret the data, for “hidden” or indirect exposures. For example, if your company is exporting to, say Greece, and you are relying on your customers’ local banks to provide credit guarantees, how confidant are you that the overseas bank will be able to step in if your client defaults on the payment?

Counterparty data is not always configured to easily uncover potential or actual risks, because the data is held in silos (by transactions, products, clients etc.) and not organized holistically (e.g., a single view of a customer by accounts, products and transactions, and their related parties such as subsidiaries, parent companies or even their banks).

Business transformation projects designed to improve processes and reduce risk tend to be led by IT or Change Management teams, where data is often an afterthought. Even where there is a focus on data management, the data governance is not rigorous and lacks structure, standards, stewardship and QA.

Typical vendor solutions for managing counterparty risk tend to be disproportionately expensive or take an “all or nothing” approach (i.e., enterprise solutions that favour a one-size-fits-all solution). Opportunities to secure incremental improvements are overlooked in favour of “big bang” outcomes.

Finally, solutions may already exist in-house, but it requires better deployment of available data and systems to realize the benefits (e.g., by getting the CRM to “talk to” the loan portfolio).

Opportunities for Fintech

The key lesson for fintech in managing counterparty risk is that more data, and more transparent data, should make it easier to identify potential problems. Since many fintech startups are taking advantage of better access to, and improved availability of, customer and transactional data to develop their risk-calculation algorithms, this should help them flag issues such as possible credit events before they arise.

Fintech startups are less hamstrung by legacy systems (e.g., some banks still run COBOL on their core systems), and can develop more flexible solutions that are better suited to the way customers interact with their banks. As an example, the proportion of customers who only transact via mobile banking is rapidly growing, which places different demands on banking infrastructure. More customers are expected to conduct all their other financial business (insurance, investing, financial planning, wealth management, superannuation) via mobile solutions that give them a consolidated view of their finances within a single point of access.

However, while all the additional “big data” coming from e-commerce, mobile banking, payment apps and digital wallets represents a valuable resource, if not used wisely, it’s just another data lake that is hard to fathom. The transactional and customer data still needs to be structured, tagged and identified so that it can be interpreted and analysed effectively.

The role of Legal Entity Identifiers in Counterparty Risk

In the case of Lehman Brothers, the challenge in working out which subsidiary was responsible for a specific debt in a particular jurisdiction was mainly due to the lack of formal identification of each legal entity that was party to a transaction. Simply knowing the counterparty was “Lehman” was not precise or accurate enough.

As a result of the GFC, financial markets and regulators agreed on the need for a standard system of unique identifiers for each and every market participant, regardless of their market roles. Hence the assignment of Legal Entity Identifiers (LEI) to all entities that engage in financial transactions, especially cross-border.

To date, nearly 400,000 LEIs have been issued globally by the national and regional Local Operating Units (LOU – for Australia, this is APIR). There is still a long way to go to assign LEIs to every legal entity that conducts any sort of financial transaction, because the use of LEIs has not yet been universally mandated, and is only a requirement for certain financial reporting purposes (for example, in Australia, in theory the identifier would be extended to all self-managed superannuation funds because they buy and sell securities, and they are subject to regulation and reporting requirements by the ATO).

The irony is that while LEIs are not yet universal, financial institutions are having to conduct more intensive and more frequent KYC, AML and CTF checks – something that would no doubt be a lot easier and a lot cheaper by reference to a standard counterparty identifier such as the LEI. Hopefully, an enterprising fintech startup is on the case.

Next week: Sharing the love – tips from #startup founders