At the recent World Economic Forum (WEF) event, held in Davos, Switzerland, fintech company DANA Indonesia took part in a panel discussion on the role that global fintech plays in fostering resilient and inclusive growth.

The result of a collaboration between WEF and Cambridge Centre for Alternative Finance (CCAF) at the University of Cambridge Judge Business School, the report was based on a survey conducted to 200 global fintech companies in five industry verticals: digital lending, financing, payments, banking and savings, and insurtech in five regions.

It highlighted the role that global fintech industry plays in widening access to financial inclusion for unbanked and underbanked societies–which is dubbed as an “integral part” of the consumer base and total transaction value of fintech services.

In the panel discussion, DANA Indonesia CEO Vince Iswara revealed how fintech services introduced unbanked society to the ease and practicality of transacting and managing their finances.

“We keep on seeing positive growth trends in fintech usage from both individuals and businesses. In fact, the use of fintech services continued to grow and persevere through uncertain times such as the pandemic. DANA noted more than 100 per cent increase in transactions in its platform followed by a 30 per cent increase in the number of DANA Bisnis users compared to the previous year (YoY).

Iswara also revealed that one of the participants’ of the company’s SisBerdaya programme, Dituta, experience a 900 per cent growth with IDR90 million in revenue after taking part in the programme.

Also Read: Understanding the role of fintech, blockchain in transitioning to net zero

Strategies to reach out to underbanked society

During the panel, DANA Indonesia explained the approach taken by fintech companies to reach out to underbanked societies, particularly in accessing insurance and investment products. One of them includes adjusting the limitations to purchase insurance and investment products.

For DANA Indonesia, this can be seen in their micro-scale insurance and investment products DANA Siaga and DANA eMAS.

“Using this approach makes it easier for users to see the advantages of using fintech services and making these instruments an essential part of their daily lives. As a result, this can be an entry gateway for unbanked societies
to become an inclusive and financially healthy society,” Iswara said.

Founded in 2018, DANA Indonesia secured unicorn status in 2022 following a US$554 million funding round.

At WEF, the company spoke at a panel discussion with Bryan Zheng Zhang (Executive Director and Co-Founder, Cambridge Centre for Alternative Finance, Cambridge Judge Business School, University of Cambridge), Drew Propson (Head, Technology and Innovation in Financial Services, World Economic Forum), and John Rwangombwa (Governor of the National Bank of Rwanda), with Naoko Tochibayashi (Japan Communications Lead, World Economic Forum) as a moderator.

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Image Credit: DANA Indonesia

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Breaking barriers in finance: Imagine a world where sending money across borders takes minutes rather than days. Where trade paperwork vanishes, replaced by a secure, digital trail. Welcome to the game-changing world of Distributed Ledger Technology (DLT), poised to revolutionise traditional banking.

What is DLT? Think of it as a shared record book spread across multiple computers instead of just one. Every transaction — a payment, trade deal, or securities transfer — is logged and visible to all authorised users. This transparency and shared responsibility pave the way for a faster, more reliable, and fraud-resistant financial system.

The world of banking stands at a crossroads. Old, manual processes groan under the strain of globalised trade and rapid financial innovation. New technologies, however, promise a smoother, faster, and more inclusive future. Among them, Distributed Ledger Technology (DLT) shines exceptionally bright.

Imagine a database shared seamlessly across institutions, where transactions are verified instantly, costs plummet, and transparency reigns supreme. DLT makes this dream a reality. This decentralised ledger acts as a single source of truth, eliminating the need for multiple intermediaries and their accompanying overhead. The result? Faster, cheaper, and more accessible financial services for everyone.

Cross-border payments, a notorious black hole of time and money, could see transaction times slash from days to minutes and costs tumble by up to 60 per cent. Trade finance, currently bogged down in paperwork and fraud risks, could be streamlined, with document management automated and settlement times plummeting from days to mere minutes. Even securities settlement could undergo a metamorphosis, becoming faster, more efficient, and less prone to human error.

Also Read: Gen AI in banking: How to ensure a successful transformation for an age-old industry

The benefits extend beyond streamlining existing processes. DLT opens the door to entirely new avenues of financial innovation. Once impractical due to high transaction fees, micropayments become viable, paving the way for new business models and revenue streams. Regulatory compliance, too, gets a boost, with KYC/AML processes simplified and data security enhanced.

Concerns about scalability and regulatory clarity remain, but can we afford to ignore the immense potential of DLT? We need to address these challenges head-on and unlock the transformative power of this technology.

Over 80 per cent of Global Financial Blockchain Council members are involved in DLT initiatives, demonstrating a clear shift in industry sentiment. Experts like Kaj Burchardi of BCG Platinion emphasise the technology’s ability to “enhance efficiencies, reduce operating costs, and create new business models”.

The future of transactional banking is no longer a question of whether DLT will be integrated but rather when and how. Traditional financial institutions must seize this opportunity to bridge the gap between antiquated systems and the demands of a rapidly evolving economic landscape. By embracing DLT, they can improve their financial performance and contribute to a more efficient, inclusive, and innovative financial ecosystem.

The World Economic Forum sees DLT streamlining cross-border payments and trade finance, saving billions. Burchardi believes it will pave the way for innovative financial products tailored to specific needs. The Global Financial Blockchain Council reports that over 80 per cent of its members are actively developing DLT solutions.

For traditional banks, embracing DLT is about keeping up and leaping ahead. It’s about offering customers faster, cheaper, and more secure services, driving innovation, and unlocking new avenues for financial performance. Dive into the resources provided, explore DLT’s potential, and join this exciting new banking chapter.

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Building a business from the ground up is not an easy vocation, but entrepreneurship can be empowering and life-changing.  In Asia, there is a growing number of successful women entrepreneurs who have found their “mission in life” and inspiring many others to have an entrepreneur mindset as well.

Some of the key driving factors to take up entrepreneurship include the opportunity to grow a supplementary income, be your own boss and gain a flexible work-life schedule. In fact, providing help for future generations of women entrepreneurs is one of the top motivating factors for women to start their own businesses.

Technological advancements have also levelled the playing field for women by helping advance work-life balance and making it easier for women to enter and succeed in this career choice.

Multiplier effects from women’s empowerment

However, despite economic growth and the increasing education opportunities for girls,  women’s overall labour force participation is just 48 per cent in Asia Pacific. There are strong reasons to push for improvements. Among them is the positive correlation between achieving the full economic potential of women and a more prosperous global business environment, which by some estimates, could give an additional US$12 trillion to annual global output by 2025.

Entrepreneurship can therefore be a way to create opportunities for women and help boost female economic empowerment. Women entrepreneurs have proven multiplier effects on poverty eradication, work productivity and economic growth. Studies have also shown that women’s empowerment leads to healthier families, higher schooling rates, and reduced child mortality.

Also Read: In March, we celebrated women in tech and returned to Myanmar

There are many industries that have stronger growth potential for aspiring entrepreneurs in the longer term. For one, the health and wellness industry offers attractive prospects that are driven by the rising prevalence of chronic diseases globally and consumer trends towards more balanced and healthier lifestyles. This is also an industry that we have typically seen more women gravitate towards, especially in our business.

Addressing challenges

In a Herbalife Women Entrepreneur survey, four in five women in Southeast Asia aspire to be entrepreneurs, but only three in five have taken actual steps to start their own businesses.

Overcoming startup costs

The greatest challenge cited by survey respondents was the high initial cost of starting a business. Here, microfinancing sources are widely used by women entrepreneurs in most Southeast Asia countries. There are also burgeoning initiatives in Malaysia and the Philippines to provide larger funding to businesswomen via bank financing. Lastly, government schemes are another way to help bridge market gaps in the allocation of financing to women-owned enterprises.

On the other hand, not everyone is ready to take up the financial commitment of starting a full-time business. Hence, having the option to keep one’s nine-to-five job while exploring side business opportunities to supplement one’s income is a viable option.

Flexibility is especially important for some women who may be dealing with becoming mothers. As an entrepreneur mum, one of our distributors shared how she enjoys the benefits of being her own boss, such as fixing her own schedules, spending time with her son throughout the day and even bringing him along to her nutrition club activities.

Finding supportive communities

Entrepreneurs face a myriad of hurdles on a day-to-day basis. Some common challenges include upskilling on good business basics and digital literacy and adapting to steep learning curves.

On top of this, female entrepreneurs could also face additional pressures like the lack of social support and financial knowledge, as well as being unsure of the first steps to take. In these situations, having a business network of supportive communities or mentors can be crucial.

There is immense value in being part of a community of like-minded women entrepreneurs that can inspire and motivate each other. More importantly, connecting with women entrepreneur associations can provide leads on business development support programs that are tailored to the challenges that women face.

For instance, studies show that mentorship is important for women entrepreneurs when it comes to enhancing personal and business growth and fostering a transformational leadership style.

Also Read: Women in industry 4.0: How modern startups can equalise the playing field

In Herbalife, our mentorship model aims to provide new distributors with sufficient training and marketing tools to build their businesses. Mentors can help new female entrepreneurs deal with negative responses from customers, as well as share strategies to help them get a “yes” more consistently. Our distributor communities also provide a platform for entrepreneurs to voice out their challenges and overcome them as a team by brainstorming solutions together.

 All eyes ahead

Entrepreneurial aspirations among women are already high in this region, and it’s been shown that women-led businesses can bring a positive impact across families, communities, and nations.

What is needed now is a strengthening drumbeat of awareness and support that will inspire and galvanise female entrepreneurs to be brave and take the first steps towards their goals.

In parallel, we should take a moment to salute the rising number of successful businesswomen in Asia who have shown remarkable passion, resilience, and belief – all bearing hallmarks of an unquenchable entrepreneurial spirit.

It’s time we recognise that the longer-term stability and prosperity of our communities and, indeed, the wider socio-economic environment is deeply intertwined with the success of female entrepreneurs.

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The buildings in which people work, live, and play produce a huge amount of carbon emissions; building operations accounted for 30 per cent of global energy consumption in 2021. The building sector, like so many other economic sectors, is on a journey to become more sustainable.

Singapore, along with many other cities, faces the challenge of reducing its carbon footprint; buildings account for over 20 per cent of carbon emissions. Recognising the urgency of the situation, Singapore has pledged to have at least 80 per cent of its buildings certified green under the Green Mark scheme by 2030. This commitment reflects Singapore’s determination to raise the sustainability bar for buildings.

Achieving significant reductions requires a collective commitment to sustainability, including improved energy efficiency in buildings. This involves building owners, industry professionals, policymakers, and other stakeholders transitioning to the best solutions to enhance building performance.

While many stakeholders are making the transition, the question remains: why aren’t all building owners moving more quickly to adopt sustainable solutions that deliver reduced costs and reduced carbon footprints?

The challenges of operating traditional cooling systems

Buildings play a substantial role in greenhouse gas emissions, accounting for a significant portion of both direct and indirect emissions. In 2021, eight per cent of global CO2 emissions came from the use of fossil fuels in buildings, while six per cent were linked to the manufacturing of construction materials. However, the largest share of emissions, amounting to 19 per cent, resulted from the electricity and heating/cooling used in buildings.

Also Read: Propelling SG businesses towards sustainable future: How to inspire emissions plan creation

Building owners must provide comfortable environments for their tenants. In tropical climates, the solution to that traditionally involves purchasing, installing, and operating cooling systems. This process is complex, requiring multiple consultants, contractors, and operators, and comes with substantial upfront, ongoing costs for maintenance and operations, and inefficiencies that increase carbon output.

It is worth noting that despite advancements in cooling equipment performance and the decreasing carbon intensity of electricity production, indirect CO2 emissions from space cooling have experienced rapid growth. These emissions nearly tripled from 1990 to slightly over 1 Gt CO2 in 2022, with emissions in 2022 surpassing those in 2021 by over two per cent. With global temperatures on the rise, the demand for cooling is expected to escalate further.

For building owners and managers, transitioning to smart and sustainable cooling solutions has become a necessity rather than a choice. Governments worldwide are tightening their carbon policies, and Singapore is no exception. In its latest budget, the government announced progressive increases in the carbon tax, which is anticipated to reach US$50 to US$80 per tonne by 2030. This tax applies to all spaces generating 25,000 tonnes or more of greenhouse gas emissions annually, emphasising the need for sustainable practices in cooling and other areas.

AaS (As-a-Service) models for building operations

Drawing inspiration from subscription models like Netflix and Spotify, As-a-Service (AaS) models provide a pathway to addressing the challenges of sustainable building operations. AaS offers on-demand and customised services to meet the unique needs of businesses.

With AaS, businesses can bypass the need for upfront capital expenditure (CAPEX) costs and save money by accessing services. This allows for scaling operations, enhancing efficiency, and allocating resources more effectively.

Introducing CaaS: Cooling as a Service 

Within the As-a-Service model is Cooling-as-a-Service (CaaS), offering building owners a hassle-free approach to cooling solutions without the burdens of ownership. The advantages of CaaS are extensive, beginning with the elimination of upfront capital investments and ongoing maintenance expenses and, through greater efficiencies, reducing carbon footprints.

Also Read: Alt-food revolution: A look at SEA’s growing demand for sustainable food

With CaaS, building owners outsource a non-core yet vital activity. By closely monitoring and controlling the cooling system in real-time and utilising data and artificial intelligence, CaaS maximises cooling performance, eliminates energy waste, and enhances indoor experiences that adapt to changing building conditions.

Embracing CaaS also enables businesses to reduce their carbon emissions and environmental impact. Building owners can specify their cooling requirements and pay a fixed rate based on actual usage. Through comprehensive data analytics, building owners can gain valuable insights into their environmental footprint and identify areas for improvement.

For example, INSEAD Asia Campus and 1Elpro Park, both working with Kaer, have successfully reduced their carbon footprint with CaaS. They use the latest energy-efficient technologies and are powered by 100 per cent renewable energy. Collectively, Kaer saved its larger client portfolio 25,000 metric tonnes of carbon in 2022.

Transition to a low-carbon economy with CaaS

CaaS presents a golden opportunity to reduce carbon footprints, achieve cost savings, and streamline operations.

This CaaS transition not only accelerates the journey towards carbon neutrality and a climate-resilient future but also enables the handover of operating and maintaining cooling systems to experts. This allows businesses to focus on their core operations while enjoying the financial and environmental advantages associated with the ‘as-a-service’ economy.

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In the world of marketing, especially in the recent situation where brands are often tsunami’d with negative impacts due to morality issues, the golden ticket to success isn’t sugar-coated gimmicks but authenticity. Much like Willy Wonka’s coveted golden tickets, consumers today seek brands offering an authentic experience. In the realm of brand communication morality, the power of authenticity emerges as the sweetest treat in the marketing mix.

Willy Wonka, the eccentric chocolatier from the recent Wonka movie, which originated from Roald Dahl’s classic, Charlie and the Chocolate Factory, understood the allure of authenticity. His magical factory showcased the wonders of genuine passion and creativity intertwined. In the marketing realm, where messages often entice and persuade, the importance of authenticity cannot be overstated.

However, much like the young Wonka, most of us marketers and communications professionals are chock-full of ideas and determined to impress the world one delectable idea at a time – proving that the best way to put our brands out there is through creative storytelling and if we are lucky enough to perform the way the young Wonka would, we might just hit the jackpot.

The everlasting gobstopper of trust

In Wonka’s factory, the Everlasting Gobstopper represented a confectionery marvel — a treat designed to last forever. In the marketing world, trust is the Everlasting Gobstopper, and authenticity is the recipe for crafting it. Brands that consistently communicate their values and stay true to their promises create a foundation of trust that endures over time and potentially gets over tough times with minimal scratches.

Consumers today are more discerning than ever. They can spot a marketing ploy from a mile away, much like the way Charlie Bucket recognised the genuine nature of Wonka’s chocolate. Authenticity in brand communication is about going beyond the glossy exterior and revealing the core values that resonate with the audience.

The Oompa Loompas of ethical framework

Willy Wonka’s Oompa Loompas served as industrious workers behind the scenes, ensuring the seamless operation of the chocolate factory. Similarly, in the realm of marketing morality, it is imperative for a brand to establish a framework that assesses its practices and performance, serving as a guide for the brand to be socially accountable to itself, its stakeholders, and the public. This role acts as the ethical framework’s equivalent of Oompa Loompas for a brand.

Also Read: Barbie-fy your business with the power of PR

Brands that incorporate this framework into their identity demonstrate a dedication to making a positive impact beyond mere profit margins. Much like the Oompa Loompas singing moral lessons in response to misbehaving children, brands with a robust ethical presence utilise their platform to advocate for social and environmental causes. This isn’t merely a philanthropic gesture; it’s a manifestation of a brand’s commitment to being a responsible and conscientious member of society.

Navigating the chocolate river of cultural and religious sensitivity

In Wonka’s factory, the chocolate river was a mesmerising spectacle, but navigating its currents required skill and understanding. Similarly, in the diverse and culturally rich landscape of the market, brands must navigate the chocolate river of cultural or religious sensitivity.

Missteps in this area can lead to a sour taste in consumers’ mouths, and the consequences can be as swift and unpredictable as the currents of Wonka’s river. This has undoubtedly proven true when many brands find themselves associated with groups perpetuating harm to the innocent, facing the repercussions of such affiliations.

Authenticity in brand communication involves more than just crafting messages that resonate; it requires a deep understanding of the cultural nuances and values of the audience. Brands that recognise and celebrate diversity authentically not only avoid the pitfalls of cultural insensitivity but also create a stronger connection with their audience.

The golden goose of transparency

In Charlie and the Chocolate Factory, the Golden Goose laid eggs that held the promise of unimaginable wealth. In the real world, transparency is the Golden Goose that lays the eggs of consumer trust. 

Willy Wonka, with his mysterious persona, understood the allure of keeping an element of surprise. However, in the real world of brand communication, transparency is the key to fostering trust. Brands that are open about their practices acknowledge mistakes and communicate openly with their audience to build a reservoir of goodwill that can withstand challenges.

Also Read: Transforming tech performance: A brain-friendly growth approach

Avoiding the Vermicious Knid of manipulation

Consumers today are savvy and can spot when they’re being manipulated. Brands that prioritise authenticity over manipulative tactics not only build stronger connections with their audience but also avoid the long-term damage to their reputation that can result from deceitful practices.

Finding the golden ticket in authenticity

In the enchanting world of Willy Wonka’s chocolate factory, the journey to find the golden ticket was a metaphorical quest for something rare and extraordinary. In the world of brand communication, the golden ticket to success lies in authenticity.

Brands that weave genuine narratives, embrace ethical practices, navigate cultural sensitivity, prioritise transparency, and eschew manipulative practices find themselves holding the golden ticket to consumer trust and loyalty.

Much like the timeless appeal of Willy Wonka’s chocolate, authenticity in brand communication is the secret ingredient that keeps consumers coming back for more. As we continue navigating the ever-evolving landscape of marketing morality, let us remember the enduring lessons from the world of Wonka — the power of authenticity is not just a fleeting trend; it’s the golden ticket to sweet, everlasting success.

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The Human Managed platform operates on the edges of technology-forward enterprises in the essential services sectors. Some questions at the forefront of every decision-makers’ mind are: 

• How do I get more value from data using AI?   
• How do I empower and scale my team’s decision-making with AI?  
• How do I improve business resiliency with AI?  

These are complex questions to answer. But a great silver lining is that you can solve all these problems and more with distributed and scalable data operations. We pick the three ops decisions with the highest impact and value for businesses of all sizes and industries as we enter the age of AI headfirst.

DataOps: Feeding AI with AI-ready data

In today’s digital world, data directly impacts your organisation’s top and bottom lines. The last few years have seen explosive growth of AI tools and services accessible to players of all sizes and sectors. Within this fast-changing environment, businesses should focus on the value they can generate from data. The faster, more agile and scalable your dataops is, the bigger your AI-powered opportunities are. For enterprises, this means operationalising any data from anywhere. 

Challenges: Now you have the data, what do you do with it?  

Businesses are usually adept at identifying the business problems they want to solve, what data is essential for the problem, and where it will come from. The real challenge comes after.  

For example, say your cyber goal is to control exposures impacting your most critical service, such as a banking app server. Some key sources that generate data related to assets, violations, and vulnerabilities are managed endpoint detection tools, vulnerability management SaaS, and external threat databases. These data sources could be sensors deployed on-premise, in the public cloud, or in your software provider’s cloud. The data from these sources vary in volume, format, schema, integration methods, etc.  

Getting all the relevant data from multiple sources, synthesising them, and processing them through a unified pipeline is infamously challenging to build and scale across numerous use cases. This limits the depth of analysis businesses can run on their data and drives siloed or tool-driven approaches to problem-solving.

Opportunities: Distributed data engineering as input for AI models  

The Human Managed DataOps platform ensures that whatever data you want to analyse is continuously collected, processed, and stored to be AI-ready.  

One of our customers, a leading ASEAN conglomerate, approached us with a widely shared problem in cyber operations: effective prioritisation. They had struggled with siloed asset databases for 20+ years and managing disparate cybersecurity tools across the public cloud, software vendor cloud, and on-premise. This resulted in manual and slow cyber operations, where many issues slipped through. 

Also Read: AI companies raised record US$50B in 2023 globally: data shows

The goal was to automatically contextualise and prioritise our customer’s cybersecurity issues as and when the alerts are generated. The customer’s job was completed when they chose 10 data sources to provide us with the required input (alerts, logs, metrics from SaaS and on-prem systems) and context (asset databases, strategies, and business logic).

The HM platform onboarded the customer’s data for continuous cyber operations in less than a month. We catalogued their assets, controls and attributes and structured their cybersecurity alerts, logs and metrics under one data schema and model. 

Our solution meant that the variable components — the ingredients — for any analysis by any kind of computing, whether rule-based programming or AI/ML models, were ready.

MLOps: Tuning AI models personalised for your business

Although AI, machine learning, and neural networks are not new, what drove the now-familiar explosion of new AI-powered capabilities is the underlying pre-trained models that picked up speed coined in 2021 as foundation models. Foundation models (sometimes called general-purpose AI or GPAI) are AI neural networks trained on massive raw, unstructured data, often with unsupervised learning, that can be adapted to perform a wide range of general tasks without human intervention.   

Foundation model, including generative AI-powered apps beyond our wildest imaginations like ChatGPT, can understand language, generate text and images, and converse in natural language. As AI’s capabilities continue to capture consumers’ hearts and minds, businesses are in a race to decide how best they can adapt AI models in their operations.  

Challenges: Now you have the AI models, how do you make it work for your business context?  

Foundation models are called ‘foundation’ because they act as the base to build apps that solve different problems. Open and commercial AI models are trained on generalised and unlabelled data, such as data scraped from the Internet or untraceable databases.

Generic AI models, no matter how advanced, will not magically produce accurate and precise outputs suited for your unique business context. For machine learning to be operational, AI models must be trained, tuned, and improved with data, logic, and patterns unique to your business.

Opportunities: Decision models combining tribal knowledge and trending knowledge

The Human Managed MLOps platform tunes foundation AI models with a knowledge base that is unique to each customer’s business context and incorporates a human-in-the-loop feedback cycle to continuously improve and measure the performance of the customer’s personalised AI model. This way, our customers get the best of both worlds: trending knowledge that builds foundation models and tribal knowledge that builds their own context models.  

One of the business-critical use cases we apply MLOps for is fraud detection and management for a global banking customer, where we continuously tune AI models with customers’ personalised data to build their own contextualised fraud model that classifies, predicts, or indicates suspicious fraudulent activities.  

Over decades of operations, our customer has amassed tribal knowledge and experiences on their fraud landscape and wanted an automated and scalable solution to increase their detection accuracy and decrease their response time.

Also Read: 2024 cloud trends: AI-powered machine learning, distributed databases, and more

Examples of their tribal knowledge include indicators of different types of fraud (e.g. repeated withdrawals from the same account on the same day), when a detection alert should be triggered (e.g. withdrawal amount is higher than US$50,000), and what needs to be done when there is a detection (e.g. send a critical alert to fraud investigation unit to investigate suspicious transaction). 

All these data points form the unique context of our customer, such as their business logics, prioritised assets, and historical patterns. The Human Managed MLOps platform transforms these data points into structured data and code to form features and labels that tune the customer’s contextualised fraud model.  

Once the input data, AI/ML processes, and desired output are aligned, it’s a virtuous circle of human and machine collaboration because ML models improve with more training and feedback. Our customer continues to add more datasets, rules and conditions while the platform continues to learn from data to improve the accuracy of their ransomware model.

IntelOps: Applying AI for better and faster decisions and actions

In today’s turbulent digital world, where speed and agility have become a necessity rather than an aspiration, leaders should pay attention to how they can make their businesses resilient. Business resiliency is about sustaining during unknown conditions and improving and coming out stronger from VUCA (volatile, uncertain, complex, ambiguous) conditions.

Resiliency, when executed right, can turn challenges into opportunities to protect their assets better, create more revenue, and make customers happier. Achieving business resiliency through data is highly impactful for many reasons, not least to understand the changing environment in which you operate, as well as generate intel to make better and faster decisions and actions.  

Challenges: Now you have the intel, how do you apply it with the right priorities?  

By 2025, it has been predicted that data will be embedded in every decision, interaction, and process (Source: McKinsey, The data-driven enterprise of 2025). 

We’ve seen how context can be built through data and models. DataOps prepares the data to generate valuable intel, and MLOps improves AI models to learn from contextualised data.  

Getting the proper intel consistently is a challenging feat. However, the benefits of the right intel are limited if you do not apply it to the right problem at the right time. How do businesses ensure this? Even with the best intel made available through DataOps and MLOps, if it is not served to the right audience at the right time, the value of that intel is not realised, and the window of opportunity closes. The challenge here is to bring DataOps and MLOps processes together in a consistent and scalable operational cycle across the business, which we call IntelOps.

Opportunities: Data-driven resiliency with I.DE.A. 

Acting with speed and accurate prioritisation is critical to business resiliency. The Human Managed platform services are designed to empower the end-to-end decision-making process, from generating personalised intel to ranked decisions and prescriptive actions. We call this the IDEA Model (Intelligence Decision Action).  

Also Read: Running on empty: What happens when AI models run out of data?

Some of our most subscribed services are data-driven asset management, attack surface management, fraud, and security posture management. For every service, our DataOps platform ensures that all of our customers’ data gets processed and analysed to create contextualised insights, which then act as input for the MLOps platform to continuously tune the AI model for more accurate and precise intel. Finally, our IntelOps platform takes contextualised intel to generate ranked decisions and prescriptive actions based on calculated priorities and impact.    

One of our customers subscribed to our network security posture management service to move the needle on fixing 40,000 violations that have been open and unresolved for over two years. Contextualised intel on the violations — no matter how organised and easy to understand — did not get their operations team to decide on the next steps because the number of issues was so high.  

To make progress on the cyber posture issue, the customer asked for decisions and actions that would have the “biggest bang for the buck”, which is precisely what we delivered. Our IntelOps platform ran computation on 40,000 reported violations on 1000 network segments, protecting around 50,000 assets accessed by 40,000 employees. As an output, we generated four ranked decisions and 16 prescriptive actions that would remove 40 per cent of all violations and improve 100 per cent of customer’s critical assets. The prescriptive actions were delivered through a nudge-based dispatch system to the users who could affect the change.

Get the data right, apply to unique business context, build business resiliency

In conclusion, a business can harness the potential of AI when it has a complete understanding and control of its enterprise data across all sources. Data must be continuously collected, processed and stored to be AI-ready.

For machine learning to be operational, AI models must be trained, tuned, and improved with data, logic, and patterns unique to your business. Finally, applying AI for better and faster decisions means ensuring the company stays resilient against changing VUCA (volatile, uncertain, complex, ambiguous) conditions.  

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Singapore-based customer data platform Meiro has secured US$3 million in an over-subscribed pre-Series A funding round led by Wavemaker Partners.

Several angel investors from Angel Central also joined the round.

Also Read: How to put customer experience at the heart of digital acceleration journey

Meiro, with offices in Central Europe, aims to fast-track its product development, bolster its team, and expand its presence in Europe and Southeast Asia. Additionally, it plans to enter new markets, starting with Dubai in 2024.

“We are gearing up to penetrate the hugely promising Middle Eastern market after launching our initial partnerships and securing our first clients there in late 2023,” said Pavel Bukowski, Chief Product Officer and Co-founder of Meiro.

Evolving data privacy regulations have resulted in the decreased use of third-party cookies that help brands understand customer behaviour and preferences. This trend and soaring marketing costs present a considerable challenge for brands.

Founded in 2018 by Pavel Bulowski, Jana Marlé-Zizková, and Vojtěch Kurka, Meiro’s Customer Data Platform (CDP) empowers brands to better understand customer preferences and behaviours across various touchpoints. Through Meiro, brands can use data to improve customer experience and marketing campaign performance, ultimately maximising customer satisfaction and business profitability.

Also Read: What makes a great customer experience?

Going beyond the traditional boundaries of CRM, Meiro’s platform collects, cleans, and manages data from virtually any source online and offline and provides personalised marketing tools to enhance business ROI.

“In 2024, we plan to complete the integration of additional communication channels and build GenAI use cases into our platform. We will also introduce a brand new product.

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As Artificial Intelligence (AI) becomes even more popular, companies around the world are exploring its implementation in the various aspects of business operations. For Singapore-based Helport, customer service is the area that they are looking at.

In 2018, the company said that Singapore reported four per cent growth in the contact centre outsourcing market, a number that is expected to cross US$77.7 million by 2025. Helport aims to tap into this opportunity by providing AI solutions that can reduce customer-related error rates by 60 per cent and cost efficiencies of up to 17.5 per cent for their clients.

Helport’s main offerings include the AI-Assist, which aims to improve service quality while reducing training and onboarding time. Its Helphub platform utilises AI to help manage customer relationships, business, data, and outbound calls to enable companies to scale globally.

Established in 2020, with a team of over 100 staff globally, the company has a presence in Singapore, the US, the Philippines, and China. This year, Helport has a major plan to expand in the US while maintaining its leading position in Southeast Asia (SEA).

In this interview with Helport CEO Li Guanghai, we find out more about the expansion plan and other details about the company. The following is an edited excerpt of the interview with e27:

How does your company aim to make a difference with your solutions? Why is it better than existing solutions?

Helport distinguishes itself with a three-fold approach:

Empowering Human Talent: Unlike solutions aimed at replacing humans, Helport’s AI contact centre solution focuses on improving the productivity and efficiency of customer representatives by reducing their workload and boosting their sales.

Also Read: How Transparently.AI uses Artificial Intelligence to detect accounting manipulation, fraud

Unique Technological Advantage: Helport’s technology is rooted in over a decade of direct contact centre operational experience and continuous self-improvement in AI and big data applications. This has resulted in a unique blend of over 100 business scenario knowledge bases, algorithm models, and training tools that combine business expertise and scenario know-how with advanced operations research and AI for powerful application outcomes.

This approach significantly surpasses emerging AI tech companies’ stability, applicability, and domain knowledge.

Market-Validated Products and Business Model: Helport is less than three years old but has already achieved continuous profitability and market validation. Its AI assistant product is SaaS-based, allowing for rapid and flexible deployment across various contact centres, typically going live within one to four weeks and showing performance improvements within two to three months.

Currently, nearly ten thousand contact centre agents use Helport’s AI assistant, with rapidly growing user numbers, in contrast to many AI peers still in the investment stage with unproven business models and products.

Can you tell us about your product development process?

Our technology and products originated from the founding team’s decade-plus experience in operating contact centres and their best practices, as well as the accumulation of both hardware and software capabilities development through continuous digital upgrading and exploration of AI and big data applications. After three years of refining and iterating in real customer application scenarios, we have now developed a standardised SaaS product.

Currently, our R&D efforts are driven by two main factors: customer and market needs feedback, and technological advancement. We closely monitor the latest developments in artificial intelligence, communication technology, big data technology, and operations research, invest in related R&D, and integrate these advancements into our products.

What notable milestones have you made recently? What lessons have you got from this?

Recently, we have made significant strides in enhancing our AI software capabilities, particularly in AI speech and real-time monitoring. These advancements have improved service efficiency and reduced the time and resources required for agent training.

Also Read: These Artificial Intelligence startups are proving to be industry game-changers

One key lesson we have learned is the importance of continuous improvement and adaptation to meet evolving market needs and technological advancements.

What do you think will be key to a successful AI implementation across industries in SEA?

Helport firmly believes that, especially in the B2B domain, artificial intelligence technology must be combined with industry experience, domain knowledge, and best business practices to unleash its immense commercial value and truly solve complex business problems. With its large population, diverse scenarios, and varied customer needs, SEA presents unique challenges.

The key to successful AI implementation across SEA industries is customisation and understanding local market nuances. This involves tailoring AI solutions to meet each industry’s specific needs and challenges, taking into account cultural, linguistic, and regulatory differences, and integrating this with global and local business experts. Additionally, building robust partnerships and collaborating with local entities will be crucial for gaining market acceptance and ensuring the practical applicability of AI solutions.

Can you tell us about your expansion plan to the US? How do you plan to achieve this? Any specific strategy to acquire users?

North America is the largest market for contact centre services, and it is also our target market. We have already opened our office in San Diego, California. We will accelerate our market expansion in North America through direct market development, strategic cooperation, and mergers and acquisitions. Currently, all of these are actively progressing.

What is your big plan for 2024?

In 2024, we will accelerate our development in the global market. Our business in mainland China is experiencing rapid growth in scale, and we anticipate fast development in both North America and Southeast Asia.

At the same time, as an AI technology company, we will continue to invest in technology research and development this year. We aim to optimise product features and enhance product competitiveness. Our core R&D directions include knowledge base construction technology, AI speech technology, advanced operations research algorithms, multi-channel communication, AI knowledge base production and training technology based on large language models (LLM), and so on.

Also Read: RevComm’s MiiTel, Cloud IP phone powered by artificial intelligence, is changing how businesses engage customers

One of our key R&D areas is the application of general AI. Over the past few years, the Helport team has closely followed the progress of LLM technology and was among the earliest to apply it in our R&D. We have currently made significant strides in knowledge extraction and knowledge base construction with the LLM.

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Image Credit: Helport

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Recently, the news involving cap table management startup Carta has gone viral in Silicon Valley and perhaps around the world involving the alleged trading of their customers’ shares without consent.

But what is a cap table, and how does it work? Do you need a cap table for your startup? And more importantly, do you need to sign up for a cap table management software for your company? I want to cover these questions in this article, including addressing common mistakes around cap tables that may help you better in managing your company’s equity.

Cap table 101

A capitalisation table  (‘cap table’ in short) is a document that records the ownership of a company. The cap table (usually prepared in an Excel or Google Sheets spreadsheet format)  reveals who owns what based on the equity instruments (e.g. shares, options, etc.) and also determines the value of the company.

The cap table also includes future or indicative share allocation, such as the employee shares option plan (‘ESOP’) and ongoing shareholder activity (usually as and when you complete each new funding round). 

Cap table management 

This is where it may get tricky. If you’re getting started, it may be easy to start with a cap table template online and then build it out for your company, which you can find online with all the necessary information. 

However, as you fundraise in the future, Excel-based cap table templates may not be able to keep up and scale together with your company’s funding growth, which may make managing things more difficult and complicated.  

Consequently, cap table software may help keep track of complicated ownership to keep track of the information and all the ongoing changes. On top of other complementary features that software may offer, like conducting valuation and reporting, etc., software may have other useful features that can help highlight common errors associated with manual entry on spreadsheets. These automated calculations reduce the risk of mistakes in equity distribution, valuation, and dilution calculations.

A well-managed cap table can help you manage how much you want to dilute as and when necessary, such as when you want to offer equity to selected key members or talents that may hopefully incentivise and motivate them to stay in your startup.

Register of members and cap table

As a founder, you need to distinguish the differences between the register of members and the cap table. Register of members is a statutory form kept by the company secretary that records the legal owner of the shares (usually updated subsequent to the issuance or transfer of the new shares). 

Also Read: What founders need to know about creating a cap table

In other words, while the register of members may get constantly updated by the company secretary when there is a change in the shareholding, a cap table tells you a bigger picture about the ownership. It maps out the ownership on a fully diluted basis (i.e. the total number of shares in the company that may be outstanding/issued if all possible sources of conversion (i.e. options, warrants) are exercised by the existing shareholders and other third parties). 

Beware of the misaligned shareholders’ expectations, aka ‘broken’ cap table

In the VC space, the ‘broken’ cap table is the usual phrase used when founders are found to hold a disproportionately lower percentage of ownership in comparison to the startup’s current stage or traction.

If not chosen wisely,  investors may also cause trouble, typically by being greedy and acquiring too much equity (in the 30 per cent to 40 per cent) early on, like a seed stage. It’ll be a ‘red flag’ to find founders not owning a majority stake in a company when they are presumed to bring the most value to the company. What will happen to the founders’ stake down the line as other future investors will want to fulfil their equity needs as well?   

The scenario may indicate wrong incentives or misaligned shareholder interests. It is unlikely for anyone to stay motivated to pursue the business due to the erosion of his or her long-term incentives. 

This perspective isn’t universal among all investors, but this imbalance may likely discourage financial investors like VCs from investing, rendering your startup less attractive for venture investments.  

As an investor, a cap table helps understand the ‘power dynamics’ as the ownership structure will help the investor assess what their future dilution may look like, voting rights, and control dynamics to mitigate investment risks once an investor becomes a shareholder in your company. 

Also Read: The power of financial models for startups: A guide for founders and VCs

Subject to the present shareholders’ agreement, fixing a cap table may be possible by internal restructuring, such as conducting a recapitalisation exercise. Existing shareholders may need to agree to flood the founders with warrants, options, or bonuses until the cap table is back on track. In practice, it may or may not work depending on how extensive the amount of fixing that needs to be done.

Learn the common terminologies 

As a founder, you need to know the common terminologies such as shares, warrants, options, vesting schedule, etc. The specific terms and definitions used in a cap table may vary depending on the funding stage and the funding documents, but they generally work the same irrespective of the company’s domicile. 

If you’re unsure about these terminologies, you may want to schedule a consultation with a startup lawyer to discuss more about your cap table needs. Managing a cap table can be a nightmare for first-timers and may get more complex as the company grows and takes on new investors. 

The bottom line

Deciding whether to use a cap table management software for your startup would depend on several factors: the complexity of the ownership structure (like different share classes and usage of intricate equity instruments like SAFEs and convertible notes), costs, and the expectations of the present shareholders and investors. 

If your startup has a straightforward ownership structure with a small number of shareholders, a simple Excel spreadsheet might suffice for basic cap table management (in fact, most securities lawyers I know use Excel spreadsheets). 

At the time of writing this, it is unclear if  Carta may face an exodus of its customers to other alternatives, but it would be challenging for the company to regain its confidence as a trusted service provider. 

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

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Despite being one of the earliest adopters of Robotic Process Automation (RPA), recent studies on RPA in Banking Finance are reporting interesting findings, particularly in the Asia Pacific (APAC) region. According to Blue Prism, based on their 2022 ‘RPA in the APAC Financial Services Sector‘ Report, RPA adoption in the APAC region’s financial services industry has been disproportionately lower than that of the rest of the world. 

While 78 per cent of financial services organisations in Australia are currently using RPA solutions and technologies, Malaysia and Singapore are far from catching up, with only 44 per cent and 28 per cent of RPA adoption, respectively. As the global Intelligent Document Processing (IDP) market is expected to reach US$6324.38 million by 2028, it becomes imperative to enhance RPA solutions to maintain a competitive edge.

This article aims to uncover the untapped potential of RPA particularly for Malaysian financial institutions and how it can revolutionise business operations in the industry.

What is RPA, and how does it work?

Robotic Process Automation (RPA) is an automation technology that mimics repetitive human tasks using rules-based processes. Unlike Artificial Intelligence (AI), RPA operates based on predefined rules and sequences without learning from data over time. While AI recognises patterns and learns, RPA follows set instructions. 

RPA finds extensive use in the banking and finance sector, where it addresses time-consuming and tedious tasks. Over a third of global RPA use cases are in financial and accounting industries. RPA streamlines processes like customer onboarding and loan processing, saving time and reducing costs. It’s essential to note that RPA has evolved to include AI processes, leading to the emergence of Intelligent Automation (IA).

Solving automation problems in banking efficiently with RPA

RPA offers significant advantages to financial institutions, enhancing their competitive edge by boosting productivity and efficiency. By automating repetitive tasks, RPA allows employees to focus on more complex and impactful responsibilities, reducing human errors in data processing by up to 90 to 100 per cent.

On top of that, RPA improves customer service by automating query resolution, reducing response times and significantly cutting costs in operations. Take the Vietnamese bank, TPBank, for instance. Implementing RPA with the help of akaBot, as seen in the case of TPBank, led to a remarkable 300 per cent return on investment (ROI) within just three years. HSBC, one of the world’s largest banking and financial services organisations, has also invested massively in RPA to streamline over 500 processes across its operations, resulting in over US$2 billion of operational savings. 

In banking and finance, RPA proves highly effective for regulatory compliance. The banking and financial industry is highly regulated with ever-changing compliance standards. The complex nature of the further complicates operational processes and lowers efficiency. In this instance, RPA serves as a valuable tool for banking and financial institutions to streamline and automate their regulatory compliance by performing the following functions:

• Repetitive compliance task automation
• Monitoring compliance in real-time
• Processes for standardising compliance
• Improving the audit trail and documentation
• Improving the accuracy and integrity of data

So why is Malaysia slower to adopt RPA?

Despite these benefits, akaBot’s findings show that 69 per cent of the organisations in the Malaysian market cite implementation costs as the most significant factor that deters them from adopting RPA solutions. Most financial institutions remain sceptical about automation and AI over hesitations on high upfront costs. On top of reservations over how efficient and cost-effective the solutions can be in the long run, these companies are also concerned about how they can accurately evaluate their ROI.

Also Read: Banking’s next chapter: How DLT is taking transactions to the future

Additionally, taking the first steps of RPA adoption comes with its own set of challenges.  As banking and finance deal with sensitive information, implementing automation solutions will need to fit within the strict rules and regulations to ensure data security. One way RPA helps with this aspect of regulatory compliance is by recording every process performed to ensure transparency for future financial audits. Furthermore, RPA solutions can help to ensure an extra layer of security by protecting sensitive financial and personal data.

Other than that, RPA adoption can also be restricted in the early phases by legacy infrastructures and complexities in process standardisation. However, these issues can only be solved by implementing automation. RPA solves the former issue by offering an integration solution to consolidate legacy systems with modern cloud-based applications and APIs. This makes it easier for the company to update its systems in the future while easing the process of data migration and reducing maintenance costs over time. 

Meanwhile, pairing RPA with Process Mining can help to automatically analyse and standardise business processes in an organisation at a fraction of the time required, eliminating another significant hurdle for organisations.

The future of RPA in Malaysia’s banking and finance sector

The RPA market in Malaysia is witnessing a significant trend of migration towards Asian-based RPA platforms.  Nearly 74 per cent of organisations across industries are either actively re-platforming or seriously considering it. This trend is driven by a wave of early adopters, as 26 per cent have already made the switch, with some opting for platform changes within specific business units. 

The reasons are compelling: Asian platforms offer cost advantages, and they come with a deeper understanding of regional nuances, making them more adaptable to local needs. Companies that have yet to implement any RPA solutions should start small and keep the investment to a minimum to avoid burning through a large sum of money in a short period.

On top of that, finding platforms like akaBot with the local workforce, supported by FPT Malaysia, helps to ensure understanding within a local context and satisfactory customer support. Exploring a double-platform approach, where one platform handles front-office tasks and another tackles back-office automation, can further optimise costs and streamline operations. 

Also Read: Gen AI in banking: How to ensure a successful transformation for an age-old industry

While initially focused on automating mundane tasks, the future lies in hybrid RPA, which empowers virtual robots with artificial intelligence (AI). This hybrid RPA, as it’s called, will unlock a new level of capabilities, enabling robots to handle more complex tasks, learn from data, and even make autonomous decisions.

For Malaysian banks, this could mean smarter loan processing, using AI to personalise financial services and more. While the full potential of AI-powered RPA is still being explored, some initial steps can be taken today. Implementing simple AI features like Intelligent Document Processing (IDP) in back-office tasks like invoice processing can significantly improve efficiency and accuracy.

Malaysian banks should approach RPA strategically, utilising process mining to map existing workflows and identify areas for improvement. This ensures automation targets the right processes, eliminating inefficiencies instead of perpetuating them. Remember, RPA is a tool, not a solution. Focus on user experience, designing robots that augment human capabilities rather than replace them. Invest in employee upskilling, data security, and compliance for a successful and sustainable RPA journey.

Leading the way with RPA

In a nutshell, the journey towards revolutionising Malaysia’s banking and finance industry with RPA requires an understanding and commitment to the transformative advantages of modern technology.

The potential rewards in terms of efficiency, time and cost savings, as well as better regulatory compliance, are only a select few of the many benefits of RPA implementation in the banking and finance industry. To find out more about RPA and how it can help your organisation, visit akabot.com for more information.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: Canva

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