Jul 5, 2021

WalkMe: A specialised digital strategy problem solver

WalkMe
Allianz
customerexperience
DigitalTransformation
2 min
Recently featured in our profile on Allianz Malaysia Berhad, we take a closer look at digital strategy specialist WalkMe

Headquartered in San Francisco, California, WalkMe focuses on software-as-a-service (SaaS) offerings for enterprises focused on the next stage of their digital adoption journey.

The company was founded in 2011 and enjoyed steadily accelerating interest from investors in its Series A to G funding rounds. Finally, in June 2021 WalkMe officially launched its IPO and managed to achieve a valuation of US$2.56bn. 

To date, it has over 900 employees, 35 million users spread across 42 countries, and approximately 2,000 customers, representing 31% of the Fortune 500. A selection of its high-profile clients include Red Hat, IBM, Microsoft, Adobe, PwC, and HP.

Maximising digital transformation

Among WalkMe’s most impressive offerings is its Digital Adoption Platform (DAP), a no-code solution capable of both maximising a business’ digital transformation strategy and accelerating ROI on software. 

DAP essentially breaks down digital optimisation into four elements: guidance, engagement, insights, and automation. At its core is the concept of ‘visibility’ - the platform provides users with data and insights to grant full visibility across their tech stack. Features include:

  • Management dashboards
  • Digital Experience Analytics (DXA)
  • Tracked events and funnels: “easily track any meaningful event on your website or business application and use funnels to analyse specific behaviors”
  • Session stream and playback: “recreate user journeys by viewing past user sessions in video or list, to analyze user journeys and points of unintended friction”

WalkMe is crucially aware of how important the user experience is to digitally-focused companies. As such, it facilitates the development of contextual and personalised online interactions across mobile, web, and desktop environments.

Yorck Reuber, Chief IT Officer at Allianz Malaysia, spoke positively of WalkMe’s ability to make the use of any software, website, or app effortless.

“Having a partner that is able to help bridge the knowledge gap when using digital tools in areas that you haven't previously been exploring is really key.

“As an insurance business, our target is not to use technology to keep people away from interacting with us. We simply want to take care of any issues they have in the easiest way possible.

“Digital adoption is difficult and complex, but it doesn’t need to be anymore when there are tools on the market that can do that work in the background. That's the magic of these partnerships,” he said.

Read Allianz Malaysia Berhad’s profile article in InsurTech Digital’s July 2021 edition to find out more

Share article

Jul 18, 2021

Reimagining operational risk management for business value

BroadwayTechnology
riskmanagement
Finance
AI
Tom Ballard, Program Manager, ...
6 min
Tom Ballard sets out a thorough new vision for operation risk management in finance, using advanced AI and analytics technology to drive business value

The events of 2020 and 2021 have fundamentally changed how we do business, upending every industry, including investment banking. Once bustling trading floors went silent as the switch to work from home led traders to disperse locations – and gave rise to new operational risk challenges. 

Today’s dynamic regulatory landscape coupled with ongoing technological innovations have made legacy approaches to operational risk management ill-suited to tackle current challenges and complexity. And while many financial institutions have turned to digital automation and transformation projects to adapt traditional ‘revenue generating’ functions to meet their challenges and help drive growth, they must now do the same with their Operational Risk Management (ORM) functions - or risk being left out in the cold. 

The Basel Committee defines operational risk as the “risk of loss resulting from inadequate or failed internal processes, people and systems or from external events.” Unfortunately, many financial institutions still view ORM as a regulatory and compliance necessity rather than a business function that delivers real value. That means executives and risk management departments must now change their risk approach to ensure they are dynamic and flexible, can guide their organizations through complex situations, and can readily meet the evolving expectations of regulators and their clients. 

Operational Risk Management is still a young field compared to other risk sectors in the financial markets, but it has always been viewed under a broad umbrella that encompasses risks and uncertainties difficult to quantify and manage in traditional manners. ORM has also been the convergence point where corporate governance issues overlap with revenue-generating business activities, causing potential confusion between departments. 

Investment banks have too often placed undue emphasis on creating governance frameworks designed to ensure they meet Basel Committee on Banking Supervision (BCBS) standards instead of recognizing that a sophisticated ORM function can bring quantifiable value. Their desire to merely meet BCBS standards and avoid historic risks has in effect led to an outdated, analogue approach in an increasingly digital world. Savvy investment banks have grasped the value potential of ORM and begun to drive a shift in awareness about the importance of a comprehensive risk identification, measurement, and mitigation program. 

Embracing a data-driven approach

Market players now recognize that adopting a digital strategy will allow them to deploy diverse and agile risk management mechanisms. It will also empower them to develop a strong and dynamic understanding of risks while adding real value to the business. This value goes beyond meeting regulatory and compliance mandates introduced as part of the Standardized Measurement Approach developed under Basel 3. A robust approach to risk allows the ORM functions to provide actionable intelligence to support business decision-making and assume a more commercial role that supports the various business units’ day-to-day activities. And that requires an intelligent, data-driven approach with a mandate to match, one that is championed at all levels of the organization.

This type of aggressive approach and embrace of digital transformation can also strengthen how ORM functions handle ambiguous and/or improbable events, especially as traditional methods of risk analysis prove unable to manage the ever-increasing volume of data. In 2010, the total amount of data created, captured, copied and consumed equaled about two zettabytes, compared to 2018 when volumes reached about 33 zettabytes. This 26% compounded annual growth rate means that if the rate of growth steadily continues by 2024, we can expect 149 zettabytes of data created per annum. 

Available data levels will make it difficult for analogue ORM functions to successfully meet the executive expectations, however organizations that adopt a data-driven approach will find increased data volumes provide them the insights to gain a competitive advantage and ability to proactively manage their risk. 

Leveraging AI and advanced analytics for high impact

Cognitive computing technologies like artificial intelligence (AI), data mining and natural language processing (NLP) can supplement a data-driven approach and help financial institutions confidently automate decisions, optimize processes and provide a deeper insight into available data. These cognitive computing technologies can help reduce or eliminate time-intensive and repetitive tasks, often related to data collection, handling and analysis which are better suited to automation. That in turn can free up critical employees to deploy their experience, knowledge of policies, and powers of assessment to support ORM functions and achieve their goals and focus on high-impact, high-value deliverables. 

Cognitive computing can teach computers to recognise and identify risk, which is especially useful to handle and evaluate unstructured data – the kind of data that doesn’t fit neatly into structured rows and columns on a spreadsheet. Natural language processing (NLP) can analyze text to derive insights and sentiments from unstructured data, which a 2015 study by the International Data Group estimates accounts for 90% of all data generated daily. When combined with the estimated future data volumes, cognitive computing functionality presents an immense opportunity for ORM functions to add additional business value in ways previously impossible. A detection model built on cognitive analytics can manage risk on a near real-time basis and can also unlock organizations’ historic datasets that have been compiled for internal, regulatory, or compliance purposes. These datasets often contain free text descriptions that contain a potential wealth of untapped, institution-specific information and could provide valuable insight into historic operational risk losses, providing data to augment employee’s qualitative experiences.    

Teaching an old dog new tricks

There are certainly challenges to launching digital transformation projects, implementing new data-driven approaches, and introducing cognitive computing technologies, including employee uncertainty and ethical considerations. That means financial institutions must preemptively address and prepare for potential challenges before they adopt a technology-enabled approach to Operational Risk Management. They must also secure employee buy-in to ensure stakeholders use these new technologies to their full potential and to assuage any concerns that technology diminishes employees’ important role in the organization.  

It’s critical that investment banks now shift their Operational Risk Management functions and focus on becoming more adaptive and agile in an increasingly volatile, complex, and uncertain world. Over 66% of banking executives report that adopting new technologies like AI and NLP will be a key driver in IBs development through to 2025. Yet for many investment banks, their ORM functions do not leverage the powerful new tools available to them – including increased computing power, digitization, advanced analytics, and data visualization techniques – much less harness the power of cognitive computing technologies. Until ORM functions leverage these tools, executive leadership cannot allocate resources and solidify ORM’s role in business strategy, performance, and decision-making processes. 

Old habits die hard, but it’s time for ORM functions to keep pace with these new technologies, methodologies, and approaches to position themselves and their organizations for success in today’s ever-changing world. If they do not adapt, there is a real risk they may stifle the wider organization, impede new opportunities and inhibit paths to valuable business growth.

This article was contributed by Tom Ballard, Program Manager, Broadway Technology

Share article