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Boosting Blockchain Security with Graph Technology



Dan McGary is Senior Sales Executive for Mid-Market Enterprise East at graph database leader Neo4j


As blockchain-backed cryptocurrencies become an increasing part of the finance mainstream, Neo4j’s Dan McGary explains how graph technology can make sense of transaction patterns, spotting outliers and fraud

Traditional finance is seeing increased competition from blockchain and cryptocurrencies. Individuals and corporations can lend, borrow, swap, trade, and hedge on blockchain. Service providers and sectors such as oil and gas are increasingly trading in global digital currencies, backed by the security of blockchain technology.

The world’s first cryptocurrency, bitcoin, launched in 2009, and since then, almost 19 million bitcoins have been mined. The value of bitcoin and other digital currencies such as Ethereum, Tether, and BNB is based on the trust users have in the system—and that trust is based on blockchain technology. With blockchain, every transaction record is timestamped and visible to every other node in the network.

In simple terms, an anonymous user mines bitcoins and sends them from their wallets as transactions, each with an input and an output address. To support the validity of a transaction, bitcoin uses blockchain to maintain and protect the correct order of transactions in separate blocks. It shares details of each block with every other bitcoin user. The entire dataset–right back to the very first transaction—is available for everyone to see.


Dan McGary

Novel vectors for fraud

In this way, digital currencies are based on the high level of trust that is clearly provided by blockchain. However, despite this, every technological development brings new vectors for fraud. Data analysts are typically on the lookout for both known and unknown types of fraud. Known fraud has been encountered before and, even within billions of transactions, it can be detected with pattern matching tools. Unknown fraud, as the name suggests, has not been encountered before. It is impossible to define rules to detect new types of fraud.

The complex network of connections in the blockchain system might at first appear to obscure full visibility of transactions, leaving financial institutions open to fraud. It is a challenge to spot unusual transactions among the vast number of blocks going through the networks. Visibility is also key to regulatory compliance. Exploiting the blockchain effectively while ticking regulatory boxes is the balancing act facing businesses seeking to mine the benefits of blockchain.

The modern world is a whirlwind in which data is being created at exponential growth rates and data connections appear and dissolve dynamically. Relational databases were built for simpler times when data was stable and structured. Their rigid data models can’t be updated fast enough to meet the new needs of modern organizations. Based on the very latest in data science and software engineering breakthroughs, graph databases offer significant advantages that include:

  • Simple, natural data models that mirror your business reality and let you add as many business entities, relationships, and rules as your application requires
  • Flexibility for evolving data structures that support agile development in today’s turbulent world
  • Real-time updating while users simultaneously access graph data
  • Index-free adjacency
  • Better querying and analytics that provide faster, richer insights by exploiting the connections and context of native graph data.

Graph technology that picks up anomalies and unusual connections is vital here. It is important that organisations can connect data across siloes to get a clear picture of criminal activity. Speed of analysis is key to enabling firms to act quickly on instances of fraud and prevent greater losses.

At the same time, it is critical that banks maintain an in-depth understanding of their financial data. From money laundering to monetising ransomware, buying illegal goods to fraud scams, criminals use cryptocurrency as a secure, low-cost anonymous way to transfer funds quickly and easily.


Analysing bitcoin transactions at scale

Graph technology can support analysis that helps uncover irregularities. At a foundational level, blockchain is a transaction with an input, output, and value. Transactions are either automated, for example, when a cryptocurrency investor uses a trading bot to buy or sell bitcoins at the best price, or manual, when users send bitcoins from one wallet to another in exchange for goods or services.

Crypto currency fraud analysts typically look at huge volumes of historical data spanning long time periods. They focus in on six-second blocks—and this approach does make it challenging to identify whether a transaction is automated or manual. But, it is possible to uncover patterns to help understand what might be happening.

When the same bitcoin moves quickly between addresses, it forms long chains in the data. When it happens inside a short time frame, it’s likely to be a series of automated payments. A closed loop means the same account is involved in multiple transactions.

All that is very simple to encode into a graph database, with its built-in ability to handle nodes and the relationships between them. Graph databases can represent key crypto structures like Blocks, Transactions, and Addresses ready for analysis. For instance, it is possible to follow the path taken by a bitcoin transaction to see if two different addresses are connected.


Guarding against decentralised finance crime in Germany

Graph technology reveals instances of illegal use of decentralised finance. PwC Germany has developed BETA, the Blockchain Explorer and Transaction Analyzer, based on graph technology. With over 300,000 transactions a day on the bitcoin blockchain, and more than a million transactions a day on Ethereum, reporting posed huge challenges. One of the key features of BETA is explainable risk reporting.

BETA integrates existing AML (anti-money laundering) scoring providers, linking local data of a crypto asset service provider, such as order history, KYC records, IP session logs, and other PII data, to create uniform, transparent, transaction-risk scoring levels. In this way, it supports PwC’s crypto asset service by guarding firms against the risk of financial crime, while meeting compliance and regulatory requirements.


Reaping the rewards of crypto currency

Conventional financial services players are in no doubt about the potential rewards that could come from cryptocurrency, but at the same time they are highly cautious. Many are adopting a wait-and-see approach. However, newer challenger banks are already moving ahead to gain competitive advantage from digital currencies. Emerging digital- and customer-centric financial services firms are increasingly offering ways to bank using cryptocurrency to customers—and traditional banks are keen not to be left behind.

For fintechs looking to enter the cryptocurrency market, there is huge potential for graph databases to analyse blockchain and render digital currencies more transparent and secure.




How can businesses boost employee experience for finance professionals?




By Martin Schirmer, President, Enterprise Service Management, IFS

Over the course of the last year, The Great Resignation has seriously impacted organisations across the globe. Staff are quitting in huge numbers, leaving companies unprepared and struggling to fulfil their workloads. In fact, mass departures are happening at all levels of the labour market, as employees attempt to adapt to the hybrid working model and growing socio-economic uncertainty.

In light of this, optimising the employee experience (EX) to attract and retain talent has become a top priority for employers. Organisations have come to understand the necessity of taking immediate steps to drive employee engagement and reshape workplace culture.

The financial services (FS) industry is no exception to this trend. From increasing employee burnout to growing career dissatisfaction, the pandemic has exacerbated the need for transformation across finance teams. This is exemplified by recent data from Spendesk, which found that approximately 40% of finance professionals are willing to leave their roles or already have concrete plans to do so.

Organisations looking to get ahead of the competition must put in extra efforts to retain their existing workforce. The fact is that employee expectations and requirements have irreversibly changed, with more workforces becoming increasingly distributed. Today’s hyper-connected workforce values flexibility and simplicity, and it is organisations which offer these experiences that will succeed in the long term.

As part of this process, finance companies must look towards the power of technology to create seamless user experiences across devices. From automating workflows to improving overall efficiencies, Enterprise Service Management (ESM) can help organisations to boost user satisfaction and go that extra mile for their employees.

How poor EXs are driving finance teams to quit

With over 40% of employees spending a significant proportion of their time carrying out mundane, manual tasks, it is not surprising that poor EXs are having a detrimental impact on job satisfaction. Finance teams in particular have been slower to digitise core processes, leading to a heavy reliance on manual tasks. This not only increases the amount of time spent on each task, but also impacts the engagement levels of finance professionals who cannot focus on more strategic aspects of their roles.

As a result of the pandemic, flexibility has also moved to the forefront of finance teams’ desires. Given the fast-paced nature of this industry, the conversation surrounding work-life balance has increased rapidly. Failure to offer flexible working policies, coupled with a lack of technology to facilitate this flexibility, has led to poor EXs across the board.

Most notably, the overarching move to omnichannel, digital-first approaches has dramatically reset both customer and employee needs. Finance is the third-slowest running corporate function behind legal and IT. Operating in a competitive environment, 73% of finance operations are facing pressures to speed up, improve efficiency, and prioritise automation.

Mitigating the problem using technology

ESM, an offshoot of IT Service management (ITSM), is the cornerstone of smart digital transformation for organisations. It can help finance teams to streamline and automate routine processes, such as monitoring the status of service requests, approving expenses, sending invoices, and tracking payments. In turn, this will free up employees’ time, reducing the burden of manual tasks and enabling them to focus on the more strategic tasks.

Another advantage ESM can offer finance teams is the ability to adapt to each department’s minimum requirements for data privacy. Accounting, for example, needs additional layers of compliance built into the system.

ESM can also facilitate cross-departmental collaboration, helping finance professionals to communicate with the wider business and perform tasks more effectively.  Organisations can use ESM to incorporate all internal services into a single platform, offering employees a well-rounded view of the business and promoting a sense of community across all levels of an organisation. This will boost productivity, whilst enhancing visibility and control.

Ultimately, the current job landscape has brought with it a new set of challenges. Organisations in the FS industry looking to navigate the storm and retain top talent must refocus their efforts on bolstering the EX. Embracing a new era of technological innovation that empowers employees and boosts engagement is a critical step in this process.


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The penny has dropped – the finance sector needs Data Governance-as-a-Service




By Michael Queenan, Co-Founder and CEO at Nephos Technologies


In our data-driven world, the amount of data is growing exponentially and it’s predicted that the amount generated each second in the financial industry will grow 700% this year. Leaders of financial services organisations have realised two things since the start of the pandemic – that data on their customers and services is their greatest asset and that they must embrace technology to make intelligent business decisions to grow successfully and outperform competitors.

Since the financial sector holds arguably the most valuable and sensitive information, organisations must do more than just store this data. They need to ensure its security, integrity, and governance so that it’s useful in improving the brand’s customer experience, innovating products and services or predicting future trends to improve risk management.

Yet without a robust data governance model – a strong set of rules and processes for what data means, and how it is categorised, owned, accessed, stored, and used – data is worthless. Only when an effective data governance model has been established, will data meet regulations and be secure. Data leaders must shift gear in their data processes to avoid hefty compliance penalties and unlock potential value from their data assets.


The data governance challenges faced by financial sector organisations

The barriers for achieving ‘good governance’ are many and varied. Ignorance of the benefits of data governance is a major hurdle for developing a governance strategy. Many financial firms have invested – at significant cost – in data governance tools, but struggle to deliver the benefits they are looking for. Many don’t have the right skills and resources to maximise or set the right metrics to measure the business value. Some are compromised by unoptimised gaps in their approach.

With many different elements to master, data governance is complex – from identifying the right tools to managing the challenges presented by encryption, all whilst ensuring that data quality is sustained and data is managed responsibly.  The negative impact of misplaced investment in ineffective data governance strategies can be significant, for the short and long-term.


Why data governance matters

With the acceleration of digital adoption in the financial services industry, it has become crucial to deliver seamless, intelligent customer experiences. Data governance is the key to managing data flow, ensuring compliance, and scaling up. Proof that data governance matters is evident in the Master Data Management Market growth prediction, from $16.7 billion in 2022 to $34.5 billion by 2027.

Data governance is a comprehensive methodology for ensuring the quality and security of the company’s data. The various benefits of an effective data governance strategy include minimised risk, coherent policies, metrics and processes, and better implementation of compliance and enhanced data value. However, for financial services, there are significant advantages as a result of the following:

  • Data governance saves the company money by increasing efficiency. Precious time can be saved by having good quality data and a single source of truth, with less duplication of data, and less time needed to correct data errors.
  • Good data governance gives the business confidence in having accurate and trustworthy data, the holy grail for delivering outperforming customer experiences.
  • A data-driven culture can also be introduced to your business through good data governance. With the ability to gather critical customer and market insights that can guide the direction of your business, data governance allows financial institutions to drive innovation and gain competitive advantage.


Bridging the governance gap with Data Governance-as-a-Service (DGaaS)

Increasingly organisations are turning to the ‘as-a-Service’ model to bridge the gaps in their data governance capabilities, as well as ensure critical alignment between objectives and results. This dedicated approach aims to minimise the risk of investments and delivers the strategy and proven technologies required to ensure data governance success.

DGaaS can be applied across each major component required to deliver good data governance. First, it uses software tools to scan all data within a typically complex financial services data infrastructure in its data discovery and classification phase. Without this detailed insight, organisations can’t always identify their data assets, any data mishandling and the level of risk generated.

The next part of the process is creation and documentation. This means organisations can drive their governance objectives through to execution, while removing the operational and recruitment overheads, which means they can purely focus on value created from data. In doing so, organisations can convert the raw outputs from the toolsets into meaningful business outputs.

With a holistic approach, DGaaS allows financial services organisations to focus on the transformational potential of data while critically staying compliant.


Reaping the benefits

Data is a vital asset to enable financial sector organisations to build the right capabilities to deliver their services and remain competitive. With a robust data governance model, financial firms can assess risk, predict trends, and seize market opportunities based on data-driven insights. Only data-driven processes, built on high quality and effectively governed data, will enable them to build outstanding customer experiences. It’s essential that leaders realise data governance is a fundamental discipline, not a luxury, and establish an effective model to formalise processes and responsibilities before their data lets them down.

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