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SO YOU THINK YOU KNOW ANALYTICS?

Oletta Stewart is a marketing specialist at MHR Analytics

 

With all of the talk about the importance of analytics for finance professionals, by now you probably understand its significance.

The million dollar question is: are you actually taking full advantage of it?

In reality, ticking the analytics knowledge box or even having an analytics system in place is just the beginning of the story.

There are many core capabilities that are often left untapped which lead to missed opportunities and many financial professionals only partially fulfilling their potential.

We’ve put together a list of the top analytics capabilities that are often neglected, but if carried out correctly, can provide a whole new level of insight that can work as a long-term strategic asset.

 

1.    Syncing data across the organisation

Having an analytics system isn’t just about optimising financial processes.

To get a full picture of the financial state of your organisation, it’s essential to take a holistic view, and to do this, data from across your organisation must be synced and coordinated.

Often, what rather tends to be the case is that teams across the organisation record and analyse their data using their own individual methods. This ultimately leads to mismatched and inconsistent financial data.

Analytics can be used to store all of your organisational data in one centralised place. Using a data warehouse, it’s possible to even collaborate business processes in real-time so that you can see how changes in other areas of the organisation will directly impact the financials.

 

2.    Understanding key value drivers

Knowing your organisations’ key value drivers is key to financial growth. Unfortunately, many rely on rough estimates to determine what these key drivers are.

For instance, it’s easy to assume that core factors like product pricing have a direct impact on revenue, when in fact, this is nothing more than an assumption until proven otherwise.

If you fall into the above category, analytics can be used to “see what the data says” so that you can base this understanding on facts rather than mere theory.

Having this capability will allow you to work directly with your organisation to employ a smart, data-driven strategy that will significantly increase the chances of realising your goals.

 

3.    Visibility of cash flow

Cash flow is the lifeblood of your organisation and it’s your job to oversee this.

Understanding exactly what’s going into your organisation, what’s leaving it, and precisely when and how this is happening, is a crucial part of avoiding financial issues later down the line.

Analytics can be used to get a multi-dimensional view of your cash flow – looking not just retrospectively, but in real-time, and even to predict what future cash flow will look like.

Using this information and tools like scenario planning, you can plan and prepare in advance and ensure that cash is constantly being allocated to the right place at the right time.

 

4.    Automating financial processes

Are you still relying on manual methods to carry out your financial reporting? If your answer to this question is “yes”, then you’re seriously limiting your potential for growth.

Research shows that 80% of spreadsheets contain errors, and reliance on these manual processes alone leave you at risk of non-compliance, not to mention taking up a good portion of your time.

Instead of relying on manually inputting data into spreadsheets, analytics can be used to automate repetitive, low-value tasks; giving you peace of mind that your financial data is accurate and up to par.

Another added benefit is that by freeing yourself from tedious tasks, you’ll have more time to spend on activities that fully utilise your skills so that you can provide greater value in your everyday role.

 

5.    Insight into profitability

Analytics can be used to drill-down to understand where profit is being generated and how much, as well as revealing areas of the business that are dwindling.

It helps you to answer questions like: What product generated the most revenue for the business within a given time period? What is each customers’ lifetime value? And which areas of the business need extra support to reach revenue goals?

These insights can be fed back to teams in other areas of the business so that the approach can be refined to promote activity that will increase the profitability of your organisation over time.

 

6.    Predicting sales in advance

Getting your budgeting and forecasting process to a point where you know your estimates are accurate isn’t an easy task – especially when this is left down to manual observation.

Using historical data and a range of predictive techniques, it’s possible to present sales figures in digestible visualisations so that you can easily forecast and make accurate predictions about what future sales figures may look like.

This also allows you to identify patterns and seasonal trends that may impact your organisations’ sales revenue, so that you can plan ahead and ensure that you have enough budget set aside to prevent any cash flow issues.

Analytics is certainly gaining momentum in the conversation of how to be a more effective finance professional, but many are still in the early days of implementation.

To compete in the ever-changing finance space, it’s important to equip yourself with an understanding of how you can use the latest technologies to increase your personal impact and value.

 

You can learn more about your own level of analytics capability by taking MHR Analytics’ Data Maturity quiz.

 

 

References:

https://www.ey.com/Publication/vwLUAssets/ey-how-can-your-finance-function-benefit-from-data-analytics/$File/ey-how-can-your-finance-function-benefit-from-data-analytics.pdf

https://www.educba.com/financial-analytics/

https://www.forbes.com/sites/bernardmarr/2016/04/07/6-key-financial-analytics-every-manager-should-know/#3b58600c55de

https://www.pwc.com/id/en/publications/Actuarial/data-analytics-financial-services.pdf

https://www.pwc.com/us/en/financial-services/research-institute/assets/pwc-fsi-top-issues-2018.pdf

Bersin by Deloitte, 2017: https://www2.deloitte.com/content/dam/Deloitte/ca/Documents/audit/ca-audit-abm-scotia-high-impact_analytics.pdf

 

 

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REACHING THE NOT-SO DIGITAL NATIVES

DIGITAL

By Garry Hamilton, Group Business Development Director, Equator

 

It’s 2020. There’s no denying that banks and financial institutions have found themselves in a war against the tech giants in recent years. But can they win? Can consumers ever be truly satisfied? Or will institutions in this space stick with what they know regardless of how well it is working? In the digital-first now, FS companies have moved into an uneasy but rewarding landscape. Just as with consumer goods, they find themselves in a space where they no longer innovate ahead of consumer aspiration and demand, instead finding themselves increasingly under pressure to catch up.

 

The experiences consumers have with global giants such as Google, Amazon, Facebook and Apple (GAFA) define their expectations for all digital experiences. To stay up to speed, FS companies need to understand the shift in consumer demand as well as the multitude of threats to a business model that’s seen as traditional and staid. In short, they need to prepare.

 

DIGITAL

Garry Hamilton

The paltry, taped-together digital offerings from the incumbent financial service brands no longer stand. However, these brands still go to market with products and services defined by internal processes and limitations, giving little consideration to true service design principles or customer experience.

 

Thankfully this is changing, in part by credible (and incredible) upstart fintech companies, chipping away at the monoliths. At Equator, we work with several brands in this space, including Santander and Virgin Money, all of whom have realised the tides are changing. Major finance brands are no longer looking for the sharks in the water that come after all they do, instead realising that it’s a multitude of piranhas that pose the most significant threat.

 

Case in point: TransferWise has demonstrated that something as mundane as foreign exchange can be made fresh; Atom Bank has shown that a lean approach to savings and loans can drive solid business without being so reliant on rate, and Starling Bank has demonstrated that a serious focus on making the tech work can yield excellent results. Consumer choice for financial services has never been greater.

 

The hidden threats that GAFA may pose on traditional finance brands are, as yet, not fully realised. Apple has already demonstrated its ambition in the US with its digital credit card offering. Amazon has Amazon Pay and shown interest in the insurance market. Facebook is out there with its (stumbling) cryptocurrency effort, and Google’s feature-creep into aggregation (and payments) indicates a genuine and poorly understood threat from some of the wealthiest and most capitalised tech companies in the world. It’s hard to imagine a reality where consumers reject financial services from these brands.

 

But for incumbent brands in this space, the opportunity to maintain success lies in two key areas. Firstly, data. While it’s commonly understood that this is the currency that enriches the GAFA businesses, consumers’ financial behaviours are still broadly out of reach. Banks and financial institutions with historically loyal customers are sitting on a gold mine of data that can be turned into actionable insights. Insights that could deepen loyalty, increase relevance and make historically uninteresting and stuffy institutions appear modern and relevant.

 

Secondly, these organisations have significant human knowledge capital. These people know how the wheels turn, how to negotiate regulation and compliance, and how to manage risk. When you look to the most successful start-ups, their success is less borne of wealth, but more of knowledge and how financial systems operate. That cannot be underestimated. Banks and financial institutions need to strive to keep their staff loyal – not just the traders with their extreme bonuses. They’re not the ones that tech businesses would come after.

 

Getting a financial service off the ground isn’t cheap, but that’s not something GAFA worry about. Instead, it’s the complexity of negotiating the regulations and marketplace. What FS brands need to watch out for is that the fintech piranhas do not become sharks – not necessarily through growth but through acquisition and consolidation. Acquiring TransferWise, Monzo or Starling Bank is still pocket change to these organisations. And they DO have the technical wherewithal to bring autonomous platforms together and make a success of it, something high street banks and insurance companies have proven incapable to see through.

 

To survive and thrive, financial brands should take advantage of the one thing they’re historically good at – assessing and mitigating risk, with the critical difference being that keeping it the same as it’s always been is no longer the safe option. At Equator, we’ve already seen clients, such as AXA and Lloyds, acquire or partner with fintech start-ups. There’s a real effort from the high street banks to deliver a Monzo-esque functionality to their customer base. And we see real innovation in everything from insurance to loans and savings.

 

But there is still a long way to go. Regulation in the UK has been reasonably balanced between control and competition since 2007. However, technology continues to outpace the law, and we need to keep the pressure on the regulators to allow for new customer engagement models, new ownership models and new ways to deliver financial products and services.

 

In the last few years at Equator, we’ve assisted many major financial institutions take on tomorrow by helping them innovate and bring new products and services to life. We’ve helped Virgin Money bring their innovative B banking service to life, pioneered original service design in the most mundane of places for Tesco Bank and a lot more besides. We know that there are many enthusiastic brands out there looking to take on tomorrow and bring digitally-enabled services to life. But the sector still has some growing up to do. Crucially, it needs to accept that the disruption that came after the 2007 financial crash has nothing on what is around the corner

 

We’re still only really getting off the ground with the second payment services directive. Open banking is creeping in. We’ve yet to see the promised liberation of the payments sector (which should be huge), and it’s fair to say we should expect more niche disruptors to emerge, as money continues to pour into the sector. And that’s not even covering off the effect that machine learning and automation will continue to have in the industry over the coming years. If you ever dared to think finance was dull, get ready for a disruptive and exciting time.

 

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RISK VS REWARD: IS AI TAKING OVER?

AI

Xavier Fernandes, Analytics Director at Metapraxis

A study by Oxford University academics into “The Future of Employment” in 2013 prompted apocalyptic headlines which stated that in the future 40% of jobs will be automated thanks to advancing technology.

The researchers subsequently claimed that the truth was in fact a little more prosaic; rather than facing complete automation, the research found that 40% of jobs faced some aspect of automation in their activity. So with new ‘AI processes a likely reality for almost half us, what does that mean for our current roles and should we be worried?

 

The fourth revolution?

The first industrial revolution saw machines replacing muscle, both human and animal. The second and third saw electrical power, mass production and computerisation revolutionise the job market. Now, with daily headlines of AI as an employment superpower, there is some concern that AI is bringing a fourth revolution, and with it, unknown circumstances.

This ‘fourth industrial revolution’ is defined by replacing brain power with machines. Our thinking capacity is what inherently sets us apart from other species, so it’s not surprising that any encroachment on it triggers some existential angst.

 

AI

Xavier Fernandes

Evolve to reap the rewards

While many businesses still don’t fully understand the capabilities of AI, those who fear its development are, instead of embracing it, missing all the benefits that it can bring to the workplace. Businesses that utilise AI appropriately are seeing vast improvements across their entire value chain; better customer experience, reduced costs, and more insightful analysis to support management decisions.

AI is particularly useful for supporting tasks with repetitive activity, for example, performing financial checks and assessing large sets of data within financial services firms. AI performs particularly well within this context, spotting outliers before a human expert would notice them, allowing impending problems to be flagged and avoiding costly mistakes.

There is also an increasing focus on maximising customer lifetime value through the use of AI. Being able to predict existing customers’ needs as well as track trends in their financial circumstances is supercharging the old cross-selling approach with testable, predictable outcomes.

With potential benefits like these on offer, management teams of innovative financial services are increasingly relying on AI to help them with some of the heavy-lifting of analysis. Using advanced data capabilities and learned behaviours, AI analyses market trends to provide predictions of future performance. This insight is invaluable and allows management teams to change direction and correct any problems accordingly. This offers a huge advantage over those that have not adopted such tools.

 

Supporting the workplace

Algorithms and AI are typically ‘smart’ at doing one, tightly-constrained task, but they can be less helpful with many of the activities that humans find straightforward. In most white-collar jobs, automation tends to replace certain tasks in the job, rather than the role in its entirety, as the need for human intelligence is still highly necessary. In particular, we still need human input to first challenge, and then synthesise, this information before taking action. Employees should therefore work with the business to proactively identify what areas of their role could be automated, so that they can focus on the areas that add real value to the business’ commercial goals.

Challenging AI is certainly still important. We know that algorithms can be much better than humans on certain, bounded tasks. However, many algorithms rely on existing data sets to build their understanding. As a result, when a business unit has ‘symptoms’ that fall outside of that body of knowledge, the algorithm may suggest the wrong course of action with costly results.

Indeed, even with plenty of data, algorithms will reflect any biases the data set contains. We’re seeing this with some legal sentencing algorithms where there is evidence that they are treating disadvantaged people more harshly. Getting the answers to why and how far we should trust our algorithms should therefore become an everyday part of any job affected by AI.

Rather than depending entirely on AI for all decisions, workers should be taking all these new, AI-generated insights and using them to complement the human decision-making process. No manager of a complex business ever has enough time to sieve through all the analysis available, but with AI driven algorithms able to flag up any issues and indicate where action needs to be taken, we may find that we have some AI ’colleagues’ who will cover our backs and suggest innovative options. Yes, there will be times when the algorithms get it wrong, but as long as we’re watching out for those, the future is bright.

 

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