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Technology

As the financial sector embraces cloud technologies what are the critical factors for success?

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As the financial sector embraces cloud technologies what are the critical factors for success?

Written by Roberto Mircoli, CTO, Virtustream

Today in order to maintain competitive advantage, financial institutions need to be increasingly agile and quick in how they respond to fast-changing customer expectations and ultimately beat their competitors.

To this point, last month the EBA – European Banking Authority  published a Report on the Prudential Risks and Opportunities Arising for Institutions from Fintech. The report provides an analysis of the risks and opportunities relating to the adoption of new innovative technologies, providing seven Fintech use cases, one of which is focused on outsourcing core banking and payment systems to the public, hybrid and private cloud.

The report looked at how cloud computing, which is an important enabling technology, is being leveraged by financial institutions to deliver innovative financial products and services.  In particular it highlights that in recent years there has been increasing interest from institutions in working with cloud service providers. And although that interest was initially focused on migrating non-core applications to the cloud, the EBA found that many financial institutions are now exploring how to migrate core mission critical systems to the cloud. The report goes on to talk about how flexibility, scalability and agility are seen as the main benefits of public cloud, but adds that most cloud services have been standardised in order to allow services to be provided to a large number of customers in a highly automated manner on a large scale.

The underlying concern of course is that in such a security‑intensive and highly‑regulated industry, no one size ‘cloud’ fits all. So while it’s key that cloud providers standardise to very high service standards, those who also provide specialised service offerings and keep themselves open to individual use cases and customers’ requirements – e.g., for mission critical workloads ‑ clearly have an edge. This is precisely what Virtustream was built for, combined with a very high level of automation which reduces human intervention in the most complex IT operation processes, increasing efficiency and lowering risk exposure.

The EPA report goes on to outline two main criterion that need to be met to ensure financial institutions are making the move to cloud correctly. These include “choosing the right cloud service partner (CSP) on its journey” and “ensuring the internal organisation can meet the needs for this transformation alongside its CSP partner”.

Choosing the right CSP

Financial institutions must carefully select the CSP that is right and suitable for their needs. This will depend on the project in question, the institution’s overall strategy and the regulatory requirements that the organisation must meet. The organisation must also consider what data is appropriate and necessary to migrate to the cloud; remembering that they don’t necessarily need to take an ‘all or nothing’ approach to cloud services. Likewise any CSP that an institution works with must have a firm understanding of the relevant compliance landscape. It is important to be able to demonstrate that a judgment call can be made when required. For example this involves documenting the reasonable action that has been taken to prevent or mitigate a data breach or loss, creating a full ‘audit trail’ and evidence of the company’s compliance.

This is where the CSP must have the deepest and broadest expertise on what it takes to migrate complex mission critical systems to the cloud, as we know quite well at Virtustream, having undertaken thousands of such migrations including the creation of an L3 extension of our users’ private data centres into our cloud nodes and integrating with their existing system monitoring and management tools via a broad set of APIs.

Likewise it is really important that the CSP is not only experienced but has a robust methodology and operating model. For example, in addition to our advisory services at Virtustream we also take a greatly optimised approach to cloud onboarding, migration and operation that includes:

  • Assessment – Identifying all workloads across the application landscape, in order to analyse system configurations and interdependencies with an estimate of initial cost benefits.
  • Onboarding – Project planning and management, documentation of all applications and workloads, determination of the move sequences and thorough testing in order to identify any risks and issues, in order to finalise a full cutover plan.
  • Migration – The actual migration of production systems, technical checks for data consistency, conversion to production operations. GoLive™ migration checks, handover and transition to steady-state.
  • Managed Services – A range of flexible choices which include infrastructure managed services and application managed services.  We also have expertise in a wide variety of databases, these include physical‑to‑virtual and virtual‑to‑virtual migrations, and database management.

The role of IT teams

The report also went on to outline how the role of IT staff in financial institutions could possibly undergo a significant transformation with increased cloud outsourcing services, whereby roles convert into support and consultation for cloud service selection, engagement and management. This is where the adoption of an enterprise‑class cloud provider with managed public cloud services that deliver private cloud attributes is really important, as this strategically enables a new operating model for IT; one that is based on business outcomes and has close alignment between IT and the business.

What I mean by this is having an operating model in place that delivers the ability to quickly implement new ideas so that the organisation can tap into new revenue streams and acquire new customers; a model that lowers complexity and – with that ‑ also actively improves the risk posture.

Adopting a cloud operating model across all areas of the business is probably the most difficult part of the transformation. The key aspect to remember here is that it means working more closely with the business; it means adopting an IT operating model that is services and software product-oriented, no technology or project-oriented.

Looking to the sky

As cloud services become more integral to the whole organisation, so CSPs are going to quickly become part of the financial/banking infrastructure. However the risks involved in outsourcing data to the cloud carry wider potential consequences for any financial institution. This is why it is so important that regulatory bodies such as the EBA are able to respond to changes in the use of cloud and can continue to place strict compliance requirements on financial institutions and their partners. To their credit many CSPs have started to accept this as part of their ‘joint responsibility’ when they engage with a financial institution, but as cloud adoption continues to grow, financial institutions will need to carefully plan for and monitor their compliance, while CSPs look to provide an adaptable framework – one that is agile and able to flex to meet the ever-evolving needs of the finance industry. If you are interested in reading the full report, you can download it here: Report on the Prudential Risks and Opportunities Arising for Institutions from Fintech.

Technology

VP Bank Selects AxiomSL to Meet Multi-Jurisdictional Risk and Regulatory Reporting Requirements

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VP Bank Selects AxiomSL to Meet Multi-Jurisdictional Risk and Regulatory Reporting Requirements 1

Consolidates bank’s reporting on a single platform for financial/statistical, AnaCredit, and CRR2/Basel-driven mandates including ICAAP and ILAAP, and provides foundation for strategic expansion

AxiomSL,  the industry’s leading provider of risk and regulatory reporting solutions, today announces that VP Bank, one of the largest banks in Liechtenstein,  has selected AxiomSL’s ControllerView® data integrity and control platform, as a foundation for its risk and regulatory compliance across Liechtenstein, Luxembourg, Singapore and Switzerland, – encompassing financial and statistical reporting such as CSSF,  FINMA, AnaCredit for EBA, MAS 610 for Singapore, and CRR2- and BCBS-driven requirements including ICAAP and ILAAP for FMA.

The high-performance, fully integrated, data-driven platform will enable VP Bank to manage an array of risk and regulatory mandates on a single platform, with full transparency across all processes from ingestion, calculation, reconciliation, and validation to submission. VP Bank will use the platform strategically to further data harmonization, streamline processes, enhance automation, bolster internal controls, and strengthen risk and regulatory reporting across the enterprise.

“Selecting AxiomSL will enhance the value of our investment in regulatory technology, optimize efficiency, and deliver business insights,” stated Robert Kilga, Head of Group Financial Management & Reporting, VP Bank. “With AxiomSL’s single platform, we can ingest data in its native format from multiple sources thus creating synergies between capital, liquidity, and other business functions enterprise-wide,” he continued. “AxiomSL’s system provides intuitive, hands-on transparency into all processes from inception to filing, enhancing our confidence in the data integrity and auditability of our reporting, and enabling us to meet ever-changing regulatory requirements”.

“We are thrilled that VP Bank, such a well-respected institution, has joined our esteemed user community in the DACH region and globally,” said Claudia Thurner, EMEA General Manager, AxiomSL. “In these times of global uncertainty, complying with a wide range of regulatory and risk requirements across jurisdictions is more complex, data intensive, and time sensitive than ever. Financial institutions require a reliable technology partner who can provide global coverage while understanding the intricacies of local and regional regulatory demands,” Thurner continued. “Our industry and technical expertise will enable VP Bank to streamline their processes, scale faster, and adapt swiftly and confidently to change. We look forward to a strong and strategic collaboration with VP Bank in support of their vision and growth journey”.

With the upcoming Basel IV-driven expansion, financial institutions like VP Bank are faced with the next generation of capital requirements that can easily overwhelm systems if they lack the data transparency, proper methodologies and controls to perform calculations accurately across all risk types. These calculations may have a profound effect on the banks’ portfolio management and even the entire business model.

To address these challenges, AxiomSL’s Basel Capital Solution incorporates a flexible data dictionary architecture, seamless calculation updates, full drilldown to data and processes, transparency into model calculations, and dynamic data lineage. In addition, AxiomSL’s regulatory experts provide VP Bank with a highly efficient change-management mechanism that enables them to be current with all Basel-driven changes.

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Technology

Uncertain Times for the Financial Sector… Is Open Source the Solution?

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Uncertain Times for the Financial Sector… Is Open Source the Solution? 2

By Kris Sharma, Finance Sector Lead, Canonical

Financial services are an important part of the economy and play a wider role in providing liquidity and capital across the globe. But ongoing political uncertainty and the consequences of the COVID-19 crisis have deep implications for the UK’s financial services sector.

In a post-Brexit world, the industry is facing regulatory uncertainty at a whole different scale, with banking executives having to understand the implications of different scenarios, including no-deal. To reduce the risk of significant disruption, financial services firms require the right technology infrastructure to be agile and responsive to potential changes.

The role of open source

Historically, banks have been hesitant to adopt open source software. But over the course of the last few years, that thinking has begun to change. Organisations like the Open Bank Project and Fintech Open Source Foundation (FINOS) have come about with the aim of pioneering open source adoption by highlighting the benefits of collaboration within the sector. Recent acquisitions of open source companies by large and established corporate technology vendors signal that the technology is maturing into mainstream enterprise play. Banking leaders are adopting open innovation strategies to lower costs and reduce time-to-market for products and services.

Banks must prepare to rapidly implement changes to IT systems in order to comply with new regulations, which may be a costly task if firms are solely relying on traditional commercial applications. Changes to proprietary software and application platforms at short notice often have hidden costs for existing contractual arrangements due to complex licensing. Open source technology and platforms could play a crucial role in helping financial institutions manage the consequences of Brexit and the COVID-19 crisis for their IT and digital functions.

Open source software gives customers the ability to spin up instances far more quickly and respond to rapidly changing scenarios effectively. Container technology has brought about a step-change in virtualisation technology, providing almost equivalent levels of resource isolation as a traditional hypervisor. This in turn offers considerable opportunities to improve agility, efficiency, speed, and manageability within IT environments. In a survey conducted by 451 Research, almost a third of financial services firms see containers and container management as a priority they plan to begin using within the next year.

Containerisation also enables rapid deployment and updating of applications. Kubernetes, or K8s for short, is an open-source container-orchestration system for deploying, monitoring and managing apps and services across clouds. It was originally designed by Google and is now maintained by the Cloud Native Computing Foundation (CNCF). Kubernetes is a shining example of open source, developed by a major tech company, but now maintained by the community for all, including financial institutions, to adopt.

The data dilemma

Kris Sharma

Kris Sharma

The use cases for data and analytics in financial services are endless and offer tangible solutions to the consequences of uncertainty. Massive data assets mean that financial institutions can more accurately gauge the risk of offering a loan to a customer. Banks are already using data analytics to improve efficiency and increase productivity, and going forward, will be able to use their data to train machine learning algorithms that can automate many of their processes.

For data analytics initiatives, banks now have the option of leveraging the best of open source technologies. Databases today can deliver insights and handle any new sources of data. With models flexible enough for rich modern data, a distributed architecture built for cloud scale, and a robust ecosystem of tools, open source platforms can help banks break free from data silos and enable them to scale their innovation.

Open source databases can be deployed and integrated in the environment of choice, whether public or private cloud, on-premise or containers, based on business requirements. These database platforms can be cost effective; projects can begin as prototypes and develop quickly into production deployments. As a result of political uncertainty, financial firms will need to be much more agile. And with no vendor lock-in, they will be able to choose the provider that is best for them at any point in time, enabling this agility while avoiding expensive licensing.

As with any application running at scale, production databases and analytics applications require constant monitoring and maintenance. Engaging enterprise support for open source production databases minimises risk for business and can optimise internal efficiency.

Additionally, AI solutions have the potential to transform how banks deal with regulatory compliance issues, financial fraud and cybercrime. However, banks need to get better at using customer data for greater personalisation, enabling them to offer products and services tailored to individual consumers in real time. As yet, most financial institutions are unsure whether a post-Brexit world will focus on gaining more overseas or UK-based customers. With a data-driven approach, banks can see where the opportunities lie and how best to harness them. The opportunities are vast and, on the journey to deliver cognitive banking, financial institutions have only just scratched the surface of data analytics. But as the consequences of COVID-19 continue and Brexit uncertainty once again moves up the agenda, moving to data-first will become less of a choice and more of a necessity.

The number of data sets and the diversity of data is increasing across financial services, making data integration tasks ever more complex. The cloud offers a huge opportunity to synchronise the enterprise, breaking down operational and data silos across risk, finance, regulatory, customer support and more. Once massive data sets are combined in one place, the organisation can apply advanced analytics for integrated insights.

Uncertainty on the road ahead

Open source technology today is an agile and responsive alternative to traditional technology systems that provides financial institutions with the ability to deal with uncertainty and adapt to a range of potential outcomes.

In these unpredictable times, banking executives need to achieve agility and responsiveness while at the same time ensuring that IT systems are robust, reliable and managed effectively. And with the option to leverage the best of open source technologies, financial institutions can face whatever challenges lie ahead.

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Technology

The end of the cookie and the new era of digital marketing

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The end of the cookie and the new era of digital marketing 3

By Biog Richard Wheaton, UK MD of data company fifty-five

If you are following the current announcements around data governance in digital marketing, you may be forgiven for thinking that digital media performance measurement is coming to an end. Europe’s GDPR and California’s CPA have set out the legal frameworks for new requirements for privacy compliance, and Apple’s ITP safeguards block the use of 3rd party cookies on their devices. Google is committed to following this, with similar blocks for its Chrome browser by 2022.

There are going to be some online targeting tactics that you will not be able to deploy in this new world, and for users with iPhones and Apple Mac computers, those tactics are already significantly curtailed. By 2022 there will be a whole raft of use cases in targeting tools like DMPs (Data Management Platforms) that will be rendered useless on the vast majority of devices.

So, what can you do? Are we set back to the days of purely contextual targeting, in which you bought the “eyeballs” of customers of a specific financial product or a given industrial sector by advertising in their vertical trade journal? Do we just have to send the same ad to everyone, and hope that some of them are in the market for our niche products?

Moving towards the end of 3rd party cookies

For marketers of financial products and services, these are important questions because managing your audiences is important for avoiding waste and for addressing your engaged clients and prospects in targeted and effective ways. The ability to track and remarket to customers has been a mainstay of digital marketing for the past decade. This has all been enabled by the dropping of cookies – files that sit on your PC and record your browsing activity. With moves from regulators and tech companies to protect user anonymity, the cookie while not quite dead, is certainly crumbling.

The upshot is that marketers cannot rely on 3rd party data anymore and should be wary of how any use of 3rd party data will be viewed by the regulator. This renders even the most basic consumer journey starting with a mobile search and ending with a desktop ecommerce transaction hard to measure in many cases. But the use of anonymized 1st party data can still yield critical insights, and this is where we need to focus our efforts.

From individual to anonymized data

So, what has fundamentally changed in digital measurement? The overarching shift is from a world where brands could access the log-file data of each individual user to a world of anonymized user behaviour, based on vast pools of data.

The ownership of these data pools and the ability to collect and model it sits with the brand that has the direct contact with the consumer. For large banks, insurance and pension companies, this is a resource for efficient and effective digital marketing, based on aggregated insights. For the adtech giants – Google, Amazon, Facebook – this will provide increased levels of targeting options within their tools.

The adtech identity graph

Google are in some ways the most advanced in delivering a scalable solution, which is worth examining. Google uses an undisclosed, supposedly huge sample of users for which they have collected the right consent first. They can accurately track across publishers, devices and even offline channels. From this they extrapolate to the entire population, applying machine learning or more traditional online polling. The end report is always aggregated and only available above a certain volume threshold. Facebook and Amazon are constantly developing similar aggregated audiences for targeting with their inventory.

These audience aggregation capabilities may appear to be similar to Nielsen’s panel-based measurement model. But this really is digital marketing on rocket fuel. It allows brands to leverage the tech brands’ enormous identity graphs and universal app tracking capabilities. And because their identity graphs are vast and data collection in real-time, the final estimate is not only accurate, but most of all, granular and actionable – the two main limitations of traditional panel-based systems.

Google launches machine-learning managed ad frequency
Practical applications of these tools are valuable to marketers. For examples, Google has recently announced the launch of a new machine-learning powered feature to manage ad frequency across its Google Ad Manager platform. It will predict how many times a user was exposed to an ad for reach and frequency analysis, based on its undisclosed sample of users who Google can track with full certainty.

This announcement comes after some similar releases across the entire stack. ‘Cross-environment estimated conversions’ will show you when customers convert on the same device, as well as when customers click a search ad on one device or browser but convert in a different environment. These are rich insights enabling you to optimize any campaigns.

Integrating the new reports into decision-making

Financial marketers will use these new features as they become available in the Google Marketing Platform, but it is also vital for these decision-makers to have their own measures of effectiveness and performance. Most of the features above are still in Beta, rarely compatible with third party systems and often difficult to export. While many media agencies are judged on ‘cost per acquisition’, this is far more difficult in a world where the conversion is estimated and therefore not auditable. This makes it absolutely essential for brand marketers to undertake their own measurement frameworks and integrate insights into their own sales and demand trackers.

The secret lies in your 1st party data given the fact that it is comparatively less impacted than 3rd party data, with the one-day notice in Safari and as-yet unaffected in Chrome. There is still a scope for projects that focus on maximizing how you capture and use your first person data, both to employ smarter segmentation of your media activation, and to obtain insights by separating out your Chrome from your ITP lines to tailor your campaign activation and measurement.

Richard Wheaton

Richard Wheaton

It will also be valuable for marketers in finance sectors to use their own data to build better targeting capabilities, and to monitor and validate the information they are getting from the large tech companies, whose insights are otherwise largely unauditable.

There is also a time-limit to the availability of these measurable insights, because when Google removes open-ended access to your 1st party cookies, the ability of brands to obtain these insights will reduced to almost zero.

A measurement mindset

While people might mourn the loss of the present system, in truth very few brands have had the genuine discipline or technical knowledge to make their measurement truly insightful. And in reality, even for brands that made the effort to obtain genuinely robust data, the figures in their analyses were not 100% accurate, with data discrepancies and ad fraud skewing the findings providing a false picture. Some will also be uncomfortable with the aggregation of power within the big tech companies, but the options will be increasingly few to work outside their platforms.

In the post-cookie world, what is really required is a change of mindset when measuring performance, which will be as important to you as the tools and technology that you use. We are in a new era and those who are prepared to adapt their thinking are best placed to succeed.

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