Source: Finance Derivative
By Rinesh Patel, Global Head of Financial Services, Snowflake
Financial organisations are caught in the middle of an ever-evolving landscape caused, in part, by emergent fintechs, shifting consumer expectations and increased regulatory change. Businesses are therefore turning to their data, re-imagining how they collect, process and analyse it, to drive growth and opportunity.
Despite this intention though, firms can often find themselves overwhelmed with the amount of data at their fingertips. Data tends to reside in individual departments that have no secure, efficient way of sharing it with other teams, creating silos of information. When teams need to collaborate, organisations are faced with additional costs and complexities in the movement of that data. The current infrastructure used by many financial institutions is not able to support the changing requirements of the industry, where data is the lifeblood.
Firms looking to harness their data should leave behind their outdated legacy architecture and implement an enterprise data strategy with a cloud-native platform. They can reposition themselves to accelerate time to market and value, with differentiated products and improved client offerings to gain a critical competitive advantage. Here are three ways that financial services are using better technology and enhanced data management to add business value.
Adhering to regulatory requirements
The volume of global regulations and reporting obligations has risen exponentially in the past decade, creating greater complexity and security challenges for firms capturing and processing data. Many of these regulations were taken by supervisors to ensure financial stability after the financial crisis of 2008. Regulators have greater expectations of firms with the aim of risk mitigation and transparency. With advanced technologies facilitating data capture, storage and analysis now available, supervisory bodies are also keen in part, to ask for additional disclosures because it’s now possible to demand more documentation and seek greater transparency.
The landscape of differing interpretations, overlapping regulatory requirements across asset classes and geographies and strict, even unrealistic deadlines for implementation have forced customers to take tactical quick-fix solutions, elevating operational risk and the chance of regulatory fines. Compliance departments have therefore been spending years building reporting processes, managing inconsistent data sets, maintaining ageing data stores and importantly overseeing differing levels of governance, adding more cost and complexity to the task at hand. For a large multi-segment global bank or asset manager this fragmented and manual approach to data management and analysis is not sustainable given the scale of processes and multi-geographic considerations that they have to comply with.
As regulators continue to push the long-term structural change agenda, financial services must now ready themselves to meet more robust reporting requirements to comply with the ever-changing regulatory landscape. The objective is to simplify and better manage data across teams with the governance and security provided by technological capabilities now offered through modern cloud capabilities to drive needed reporting. This will allow firms to replace old and inconsistent data with a centralised data architecture, providing a single source of truth. The time and cost reduction from data sourcing, ingestion, and the normalisation of data for analysis, can shrink to significantly streamline reporting processes.
Customer 360 experience
Consumers provide financial institutions with a vast amount of information, ranging from their banking habits to their behavioural preferences. Financial organisations have traditionally been slow to tap into the totality of this information to provide a better experience for customers.
The quest to provide greater visibility and a 360-degree view of customer behaviour is at the core of financial services organisations’ priorities. Customers want smooth, easy digital experiences that can speak to their desire for ease of use and convenience. This is seen in the ways virtual banking consumers have opted for technologies that are simple to interact with, self-directed and frictionless when it comes to carrying out digital transactions. New regulations, such as PSD2 and rules around open banking have also primed customers to expect more.
The challenge for legacy institutions is to bring the ease and usability of digital-first platforms with the sophistication of a major, global provider. Tapping into the full spectrum of data created by consumers is central to a successful transition.
Wealth advisory, investment management professionals are increasingly looking at data capabilities to support ongoing relationship management with their clients. Using data to understand customers in this way helps banks to successfully move customers up the wealth value chain. Wealth management organisations can digitise the investment process – from finding customers to managing accounts, and offering bespoke plans. Effective use of data in this sector can free up time for advisors, helping to retain key customers and charge higher commission levels thanks to a new level of personalised service.
Developing an effective ESG strategy
Environmental, social and corporate governance (ESG) considerations have grown in significance with increasing stakeholder pressures, driving a response by firms to prioritise their sustainability agenda. To understand, evaluate the problem and take action, firms need access to technology providing holistic ESG data capabilities and solutions, with performance and scale.
Financial firms are amassing large data sets from the public sector, including government reports, scientific bodies and private sector reports, to understand and address the climate challenge. Businesses are moving with urgency to acquire robust data sets, to meet ESG criteria and sustainability metrics needed to evaluate impact and make progress against their own commitments. There are several pervasive business use cases for teams experiencing ESG data challenges, including portfolio construction, financial planning and regulatory reporting that will require an effective ESG data management strategy.
Ever present challenges in the ingestion, standardisation, and sharing of ESG data will be at the forefront of every organisation – as they process the magnitude of the challenge and transform their operations to address the issue. With cloud-native solutions, firms can use ready-to-use query data across established marketplace data sets. They can then share that data across teams in a secure, governed way – with greater speed to market. Organisations can meet the need for scalable analytics, and access a data ecosystem to build their own proprietary ESG applications for different user and workflow requirements.
A business fit for the future
With data cloud solutions, businesses can effectively analyse the vast amounts of data available to them, equipping them to meet the ever-changing financial landscape. Leaving behind legacy systems will open up a multitude of opportunities and benefits that will drive business growth. This includes developing a 360 view of the customer, improved data governance and the opportunity to use data to support an effective ESG strategy. Without the ability to harness data through the cloud, companies will get left behind the competition and struggle to meet the standards that modern consumers expect.
How will regulations effect the open banking sector?
Source: Finance Derivative
Martin Hartley – Group CCO of emagine Consulting
Comments on the future of the open banking sector and how it will affect the UK market.
“The UK Open Banking Sector is still primarily driven by regulation. In my view, two of the major current regulations will remain at the forefront moving forward, namely the CMA (Competition and Markets Authority), which mandated the major banks to provide open banking access to authorised third-party providers, and PSD2 (Second Payment Services Directive), which set the standards for secure data sharing. Cybersecurity regulations will only increase in importance, as will Brexit-related changes as any divergence between UK and EU standards could impact open banking.
“Over the upcoming months, increased data sharing through open banking will add crucial pressures to cybersecurity, likely creating a surge in the sector once again.
“I expect ongoing scrutiny and efforts to enhance data protection measures, potentially leading to more stringent cybersecurity regulations being adopted by businesses. I expect to see more partnerships between traditional banks and FinTechs or consultancy firms as they collaborate to enhance cybersecurity or offer innovative services to plug the gap. Conversely, there could be consolidation within the FinTech industry as companies merge to gain market share.
“When it comes to the size of the business and how it is affected, history has shown us that there are certainly positives and negatives of being an SMB when responding to new regulations. On the positive side, they can leverage their agility and they will have a more personal relationship with their customers, potentially leading to a higher level of trust. However, SMBs may face challenges due to their limited budgets and resources. The larger firms will have much larger budgets, allowing them to have more advanced IT systems and IT security, making it easier for them to integrate APIs and develop the necessary infrastructure.
“The benefits of open banking are endless, and the UK Government is showing their forward-thinking mentality in exploring the idea of implementing the technology to streamline wider services. But, much like anything, there are always pros and cons.
“Open banking would simplify payments for public services, making transactions quicker and more convenient for everyone. As it relies on APIs and authentication protocols, open banking would make payments more secure for the public and it would allow access to digital payments for members of the public who have smartphones but possibly no bank accounts. For any digital implementation, it goes without saying that we need to be aware of the risk of cyber attacks and data breaches. These, combined with the exclusion of non-tech savvy individuals, could mean that certain members of the public may not embrace the change, which poses a risk. There is also the additional cost of providing the infrastructure and this will have to be managed carefully to avoid burdening the taxpayer.
“We have already seen digital transformations in areas such as the GOV.UK Pay System and there are two main indicators of the success of any digital implementation; adoption rates and incidents. There haven’t been any high profile incidents that have hit the headlines in recent times so that to me is a huge positive and provides a level of confidence. It would be interesting to see how many government departments and agencies have adopted GOV.UK Pay for their payment processing needs to understand the system’s usefulness and acceptance within the government. The government must be committed to continuous improvement and to ensure that the system continues to comply with regulations and consciously drives the adoption rate to hit at least 90% of government departments and agencies.
“A favourable regulatory environment will encourage more banks and third-party providers to participate in open banking initiatives, leading to growth in the UK market and positioning the nation as industry leaders.”
Advancing green mobility for a sustainable future
Accelerating decarbonisation, the transition to SDVs and reshaping urban ecosystems, are helping revolutionise the global automotive industry
By Amit Chadha, CEO & Managing Director, L&T Technology Services
The world is changing. There is an urgent need for a transition toward sustainable practices to combat the threat of climate change. As global temperatures rise and weather patterns evolve, achieving net-zero emissions by 2050 could still help prevent irreversible damage to our planet.
With global carbon emission levels continuing to rise at an accelerated rate, there is a growing momentum toward addressing the scenario on war footing. As the most visible source of emissions, the automotive industry, and, consequently, the future of mobility, is in focus. By helping accelerate decarbonisation, reshape evolving urban ecosystems, and redefine the global automotive industry – we can help reverse the trend and preserve our shared future.
Green mobility has emerged as a major enabler in this direction. Leading stakeholders are becoming increasingly invested in developing a deeper understanding of the multifaceted realm of green mobility and its potential to shape a sustainable future.
Accelerating decarbonisation: A global mandate
Decarbonising the transportation sector is crucial to mitigate the harmful effects of climate change. Fossil fuel-based vehicles are responsible for a substantial portion of carbon dioxide emissions, exacerbating the greenhouse effect. To accelerate decarbonisation, governments and businesses today need to prioritise the adoption of clean, renewable energy sources, such as electricity and hydrogen, for powering vehicles and other modes of public transportation.
Automakers, recovering from the impact of the pandemic and global supply chain disruptions, are therefore exploring new avenues to meet the rising demand for electric mobility. Electric vehicles (EVs), by eliminating the need for fossil fuel-powered engines, play a vital role in improving overall air quality and have emerged as a promising solution for reducing carbon emission levels. They are capable of meeting the diverse needs of all kinds of drivers and offer affordable mobility and maintenance options. Recent advancements in battery technology, including the growing availability of charging infrastructure and incentives for adoption, have led to a significant rise in the EVs popularity.
However, to achieve widespread adoption of electric vehicles, there is a need to address key issues such as battery disposal, supply chain sustainability, and equitable access to EV technology.
Reshaping urban ecosystems: Driving the frontiers of change
Urban areas are central to the momentum around green mobility transformation. As growing global populations gravitate towards cities – congestion, pollution, and limited availability of green spaces have emerged as major challenges. As a result, cities must increasingly reinvent themselves to promote sustainable mobility and improve the quality of life for their residents.
Smart technologies and vertical green systems can contribute to a reduction in the energy demands of buildings by providing shade and insulation, mitigating urban heat islands, and cooling down public spaces. They also enable carbon sequestration, a reduction in pollution levels, and improvements in biodiversity.
Implementing efficient transportation systems, such as buses and trains powered by clean energy, can further reduce individual vehicle usage, traffic congestion, and emissions. Pedestrian-friendly infrastructures, cycling lanes, and micro-mobility solutions like e-scooters and bike-sharing programs can further help promote eco-friendly transportation choices. At a macro-infra level, smart city technologies and data-driven urban planning practices are helping optimise traffic flow, reduce idling times, and minimise fuel consumption.
Integrating green mobility into urban ecosystems is therefore a win-win proposition – fostering cleaner air, enhanced mobility options, and healthier communities.
From a public health perspective, improved air quality can drive a decline in respiratory and cardiovascular diseases linked to air pollution. Healthier citizens translate to a more productive workforce and reduced healthcare costs, further strengthening the growing impetus for vehicle electrification. The shift towards vehicle electrification offers significant economic benefits, including greater job creation, enhanced research and development, and greater investments in sustainable innovations. A consequent reduction in the demand for fossil fuels, scarce in terms of availability and mostly imported, in turn, helps enhance energy security and stabilise fuel prices.
Software Defined Vehicles: Pioneering the change
The global automotive industry is at the core of driving the emerging frontiers of green mobility. Traditional automakers and new entrants are racing to produce eco-friendly vehicles, and this competitive spirit, in turn, is transforming the industry landscape.
Automakers worldwide need to embrace sustainable practices by reducing their carbon footprint during the production process and implementing circular economy principles. Moreover, investing in research and development of alternative materials and manufacturing processes can lead to lighter, more energy-efficient vehicles. The rise of autonomous vehicles presents an opportunity to optimise transportation networks, enhance traffic flow, and reduce accidents. Leveraging this technology, in combination with electric and shared mobility solutions, can lead to a more sustainable and efficient future for transportation.
Software would play a key role in this direction, delivering a streamlined passenger and driver experience paradigm while ensuring conformity with the evolving regulatory standards. With Software Defined Vehicles (SDVs) increasingly constituting a focus area for major automakers worldwide, the future would witness a greater demand for digital engineering services to unlock new value streams.
The importance of ecosystem partnerships
Automotive industry stakeholders are already working with ER&D partners who can deliver across the value chain and understand each of the key parameters in the EV/SDV ecosystem. However, approaching separate vendors for product conceptualisation, design and development, testing, maintenance, manufacturing and after-sales support can increase costs and complexities.
An ER&D partner, equipped with multi-industry expertise, digital engineering capabilities, and a co-innovation commitment, can help drive transformation initiatives for transportation enterprises, overcoming technology constraints with cross-vertical learnings. Leveraging global delivery capabilities, the partner can also provide computing models that consume less energy, boost performance, and optimise data-led algorithms. In addition, they can enable scalable software stacks that leverage sensors and physical components to provide the safety and performance that electric vehicles need.
ER&D companies are also increasingly being called upon to help redefine focus areas with software, ensuring third-party integration, driving feature deployment, enabling CloudOps and fast over-the-air updates. The rising complexities within the connected car landscape further call for adopting software-defined designs that can overcome multi-layered challenges – ranging from development to subsequent deployment, maintenance, and updates.
A multi-stakeholder approach
Achieving the goal of green mobility demands collaboration among various stakeholders. Governments play a crucial role in enacting policies and regulations that incentivise the adoption of sustainable practices and technologies. Subsidies for EVs, emission standards, and urban planning regulations are some of the ways governments can drive the transition towards greener mobility.
Private sector involvement is equally critical. Corporate sustainability initiatives, investment in research and development, and partnerships for innovative mobility solutions can accelerate the transformation. Additionally, consumer awareness and support for eco-friendly practices are essential in shaping market demands and influencing business decisions.
Advancing green mobility is a pivotal step towards a sustainable future. By accelerating decarbonisation, embracing the transition to SDvs, reshaping urban ecosystems, and revolutionsing the automotive industry, this can combat climate change on a significant battleground. The collective efforts of governments, industries, and individuals are crucial in driving this transformation.
Embracing green mobility is therefore not just about reducing emissions, but rather, about fostering a healthier, cleaner, and more resilient world. It is about our common future –striving together toward a prosperous, inclusive, and sustainable tomorrow.
How Turning Your Core Data into a Product Drives Business Impact
By Venki Subramanian, SVP of Product Management at Reltio
Data drives efficiencies, improves customer experience, enables companies to identify and manage risks, and helps everyone from human resources to sales make informed decisions. It is the lifeblood of most organisations today. Sometime during the last few years, however, organisations turned a corner from embracing data to fearing it as the volume spiralled out of control. By 2025, for example, it is estimated that the world will produce 463 exabytes of data daily compared to 3 exabytes a decade ago.
Too much enterprise data is locked up, inaccessible, and tucked away inside monolithic, centralised data lakes, lake houses, and warehouses. Since almost every aspect of a business relies on data to make decisions, accessing high-quality data promptly and consistently is crucial for success. But finding it and putting it to use is often easier said than done.
That’s why many organisations are turning to “distributed data” and creating “data products” to solve these challenges, especially for core data, which is any business’s most valuable data asset. Core data or master data refers to the foundational datasets that are used by most business processes and fall into four major categories – organisations, people (individuals), locations, and products. A data product is a reusable dataset used by analysts or business users for specific needs. Most organisations are undergoing massive digital and cloud transformations. Putting high-quality core data at the centre of these transformations—and treating it as a product can yield a significant return on investment.
Customer data is one example of core or master data that firms rely on to generate outstanding customer experiences and accelerate growth by providing better products and services to consumers. However, leveraging core customer data becomes extremely challenging without timely, efficient access. The data is often trapped inside monolithic, centralised data storage systems. This can result in incomplete, inaccurate, or duplicative information. Once hailed as the saviour to the data storage and management challenge, monolithic systems escalate these problems as the volume of data expands and the urgent need for making data-driven decisions rises.
The traditional approaches for addressing data challenges entail extracting the data from the system of records and moving it to different data platforms, such as operational data stores, data lakes, or data warehouses, before generating use case-specific views or data sets. In addition, because of the creation of use case-specific data sets that are subsequently exploited by use case-specific technologies, the overall inefficiency of this process increases.
One inefficiency arises from the complexity of such a landscape, which involves the movement of data from many sources to various data platforms, the creation of use case-specific data sets, and the use of multiple technologies for consumption. Core data for each domain, such as customer, is duplicated and reworked or repackaged for almost every use case instead of producing a consistent representation of the data used across various use cases and consumption models – analytical, operational, and real-time.
There’s also a disconnect between data ownership and the subject matter experts that need it for decision-making. Data stewards and scientists understand how to access data, move it around and create models. But they’re often unfamiliar with the specific use cases in the business. In other words, they’re experts in data modelling, not finance, human resources, sales, product management, or marketing. They’re not domain experts and may not understand the information needed for specific use cases, leading to frustration and data going unused. It’s estimated, for example, that 20% or fewer of data models created by data scientists are deployed.
Distributed Data Architecture – An Elegant Solution to a Messy Problem
The broken promises of monolithic, centralised data storage have led to the emergence of a new approach called “distributed” data architectures, such as data fabric and data mesh. A data mesh can create a pipeline of domain-specific data sets, including core data, and deliver it promptly from its source to consuming systems, subject matter experts, and end users.
These data architectures have arisen as a viable solution for the issues created by inaccessible data locked away in siloed systems or rigid monolithic data architectures of the past. Data fabric decentralises the management and governance of data sets. It follows four core principles – domain ownership of data, treating data as a product and applying product principles to data, enabling a self-serve data infrastructure, and ensuring federated governance. These help data product owners create data products based on the needs of various data consumers and for data consumers to learn what data products are available and how to access and use these. Data quality, observability, and self-service capabilities for discovering data and metadata are built into these data products.
The rise of the concept of data products is helpful for analytics/artificial intelligence, and general business uses. The concept for either case is the same – the dataset can be reused without a major investment in time or resources. It can dramatically reduce the amount of time spent finding and fixing data. Data products can also be updated regularly, keeping them fresh and relevant. Some legacy companies have reported increased revenues or cost savings of over $100 million.
Data product owners have to create data products for core data to enable its activation for key initiatives and support various consumption models in a self-serve manner. The typical pattern that all these data pipelines enable can be summarised into the following three stages – collect, unify, and activate.
The process starts with identifying the core data sets – data domains like customer or product – and defining a unified data model for these. Then, data product owners need to identify the first-party data sources and the critical third-party data sets used to enrich the data. This data is assembled, unified, enriched, and provided to various consumers via APIs so that the data can be activated for various initiatives. Product principles such as the ability to consume these data products in a self-service manner, customise the base product for various usage scenarios, and deliver regular enhancements to the data are built into such data products.
Data product owners can use this framework to map out key company initiatives, identify the most critical data domains, identify the features (data attributes, relationships, etc.) and the sources of data – first and third party that needs to be assembled – to create a roadmap of data products and align them to business impact and value delivered.
With data coming from potentially hundreds of applications and the constantly evolving requirements of data consumers, poor quality data and slow and rigid architecture can cost companies in many ways, from lost business opportunities to regulatory fines to reputational risk from poor customer experience. That’s why organisations of all sizes and types need a modern, cloud-based master data management approach that can enable the creation of core data as products. A cloud-based MDM can reconcile data from hundreds of first and third-party sources and create a single trusted source of truth for an entire organisation. Treating core data as a product can help businesses drive value by treating it as a strategic asset and unlocking its immense potential to drive business impact.