Risk technology can shrink big data into more manageable information, so it’s not just insightful, but actionable.

Seeing is believing. That’s why conveying risk data in visual formats can make such an impact. When data is visual, it’s easier for stakeholders to comprehend complex concepts and detect trends. This can lead to more informed and expedient decision making, and ultimately, more proactive risk management.

As businesses continue to harness the power of big data to understand organisational risk, they are realising the need for technology that not only captures vast amounts of information, but also surfaces and visualises that information in ways that convey timely and actionable insights.

High level visibility to corporate objectives under threat, group level view of overdue risk assessments, risk areas with breached indicator tolerance levels.

Data visualisation – the process of transforming text-heavy data into pictorial or graphical formats – is certainly not new. However, now that advanced technology has enabled data visualisation to be comprehensive, dynamic and automatic, its current power is unprecedented.

Risk-minded organisations seeking to surface relevant risk information, and wanting to move away from static, rearview-mirror risk analysis and reports, can actually look to risk management technology to capitalise on the evolution of data visualisation.

The Riskonnect Insights advanced analytics is a significant differentiation of the Riskonnect Integrated Risk Management Platform. This provides the intelligence needed to power effective integrated risk management, by surfacing, connecting and communicating risk information in ways that drive faster, smarter business decisions. The benefits this offers is the ability to access the right information at the right time through a single dashboard. Strategic metrics can be shown graphically, providing data that is easier to read and interpret.

The Trend Towards Interactive Data Visualisation

Data visualisation is being brought to the forefront of risk-minded organisations, in part because of the world’s current preoccupation with big data. However, while big data is significant, it has overshadowed the importance of understanding “small data” – bite sized chunks of information that are easy for people to process and comprehend.

Countless organisations have deployed an abundance of resources to make sense of the large volumes of data inundating their businesses, only to yield disappointing results: The data is there, but the insights are not; or, they’re just too difficult to uncover because they are locked away in spreadsheets with mind-blurring columns, rows, text and numbers.

Data visualisation, on the other hand, provides visuals like infographics, dials and gauges, geographic maps, sparklines, heatmaps, and detailed bar and pie charts, so stakeholders can more easily spot trends or outliers, and make revenue-impacting or risk management decisions at a glance – the main driver for investing in big data initiatives in the first place.

Make no mistake though, pretty data isn’t everything. Even the most eye-catching dashboards, charts and graphs mean nothing if they reflect incomplete or out-of-date information; if they showcase surface-level or static data; or even if they are difficult to produce.

If you want to transform your organisation’s big data into true business intelligence, be wary of solution that merely create beautiful reports in a vacuum instead of illustrating actionable insights.

The Power of Illustrating Risk

The ability to illustrate risk across an entire organisation from a single source of truth – regardless of department, line of business or even the actual risks themselves – not only drive business intelligence, but also drive integrated risk management. As such, data visualisation is an important and practical function within web-based risk management technology.

Risk management technology exists so organisations can consolidate risk and insurance data from across the enterprise; surface relevant information from wherever it’s hiding; connect it with other internal and external data; and then normalise the data so it’s all relatable.

With the right functionality, risk management technology can exploit its deep connection to expansive and critical risk and insurance data to automatically create visuals that take into account the full spectrum of risk. Further, it can make visualising data dynamic – allowing users to instantly manipulate images and drill deeper with more specific queries for any type of information.

Insurance claims and policy data are just two examples of information that can be visualised and analysed from 360 degrees within risk management technology. Related data can be configured and reconfigured visually time and time again, based on what the stakeholder wants to see, or the business problems that specific stakeholders are trying to resolve.

For example, a risk manager may want to see claim severity data from trending, timeline and geographic perspectives to get a handle on incidents; what’s causing them; and how they can be prevented at certain locations. A claims manager, on the other hand, might want to see claim severity data through the lens of how long the most severe claims are open versus less severe claims in order to evolve processes and shorten the claims lifecycle for severe claims.

When it comes to insurance policy data, stakeholders might start out looking at the policies they have in place, but drill down to analyse premium spend versus policy coverage. This could include the types of policies or locations demanding the highest premiums; or the carriers to which premium spend is going, and whether that spend is distributed appropriately to minimise risk.

Regardless of the business problems that need to be solved, or the stakeholders attempting to solve the problem, with just a few clicks, any user can alter their queries and analyse new visualisations to capture an holistic picture of risk, or the more specific components of risk, of which they are in charge.

Not a Data Scientist? Not a Problem

The number of charts, graphs and visuals that can be used to convey risk with a true interactive data visualisation solution are finite. Formerly, users might have had to compromise on the type of data, or type of visual they selected because of limitations with report creation tools.
The comprehensive and drill-down nature of data visualisations within risk management technology, however, solve that challenge. In general, the types of analysis user’s aspire to illustrate using risk management technology, include:

  • Comparative: How different data compares under similar or dissimilar circumstances
  • Relationship Analysis: How different data relates and impacts each other
  • Composition Analysis: How different pieces of data contribute to a broader picture or business problem
  • Trend Analysis: How different data moves up or down, or stagnates

The power to illustrate risks through such a complex and comprehensive lens for business intelligence is not as complicated as it may seem. In fact, with interactive data visualisation solutions, business intelligence can be “self service.”

Self-service business intelligence means users can connect and normalise disparate data sources into a single, unified source of the truth; illustrate the data in meaningful ways that don’t compromise data accuracy or context; and collaborate and share insights with others.

Web-based risk management technology can help facilitate all of this, and users need not have data analytics experience, or advanced training. Nor do they have to rely on technical resources or other IT teams. The analytics and data visualisation tools are designed for risk managers, not data scientists. Therefore, the resulting actionable intelligence is as easy to create, as it is to consume – improving the speed and efficiency of daily operations across the board.

What’s a picture worth?

Data visualisation poses great promise to the risk management and insurance industry – facilitating true integrated risk management, whereby organisations can bring together all areas of risks effectively, and enable insights that have been previously unobtainable.

Ask these questions to ascertain whether your organisations’ current data visualisation techniques truly enable business intelligence:

  • Is your data connected? From Excel spreadsheets and other on-premises software, to data warehouses and cloud-based applications, you likely have dozens of different data sources. Is all your internal and external data normalised and aggregated into a single source of the truth? Can your data sets interact or “talk” to each other – automatically highlighting relationships to allow for more comprehensive and contextual analysis, and additional queries for information in real time.
  • Do you have easy access to advanced analytical tools? Can you drill-down further by any data subset as and when you need? Can you integrate all of the information you have, analyse it against the “bigger picture,” and use the results to make realistic predictions to guide your daily decisions?
  • Is your data analytics DIY? Are you able to filter, segment and analyse data without in-depth technical knowledge? The best data visualisation tools will allow you to efficiently and independently query the information you’re seeking. Further, do you receive customised alerts, outlining what’s happening in your business and when, so you can make timely and informed decisions without having to constantly monitor every indicator for change?

If the data visualisation tools you’re using reflect disconnected data; disallow deeper analysis on the fly; or are too cumbersome to manage efficiently or independently, don’t despair. Don’t automatically assume you need to go on the hunt for one-off software that executes on these things. The right web-based risk management technology can support integrative data visualisation. If you already have such a system in place, or if you’re considering investing in one for the future, ask risk technology vendors about their integrative data visualisation functionality. If a picture is worth a thousand words, the worth of interactive data visualisation is exponential.