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How Big Data is Transforming Bilateral Trading

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By Stuart Smith, Co-Head Business Development – Data & Risk at Acadia

 

Since its inception, Big Data has been an important part of how firms have identified and constructed quantitative trading strategies with hedge funds depending more on quant strategies which rely heavily on big data driven analytics.

As big data technology continues to move from being a specialised technical capability to being a commoditised capability available on a range of easily consumed technology platforms, its use within the financial derivatives will continue to increase beyond the initial quantitative driven capabilities.

At the same time, the number and range of available data sources is increasing rapidly. Whether it’s the increase in alternative data sets or new technology enabling firms to simply keep more of the data they have been creating, the volume of data available is increasing dramatically.

 

Big Data in Risk Management

Risk Management has always had requirements which have driven a close collaboration between business and technology to make available risk analytics useful for the business to make better decisions. As technology becomes more advanced, the metrics available continue to improve as well. This is typically because many risk metrics require high numbers of scenarios and valuations to correctly identify risks in multiple scenarios. To maintain flexibility, this has led to an explosion of data to manage. Firms are increasingly keeping all this data available which can run into many Terabytes (TBs), much of which needs to be ‘In Memory’ to make it accessible to analysts.

Stuart Smith

To achieve this big-data, technology is critical to allow firms to move large volumes of data quickly and easily from affordable long-term storage into high performance in-memory analytics. Big Data technology is ideal for this type of problem to enable large volumes of data to be recalled from across multiple stores and appropriately aggregated or filtered based on the analysis which users are requesting. Whereas in the past, analysts would have to accept that data outside of the last 3-5 days is only available in a summarised format, they can now expect that the data can be re-hydrated quickly and easily from cloud data stores and available to them in an easy-to-consume web interface.

This can enable much more dynamic types of analysis, for example where a new risk is identified, through analysis of a recent data set it’s now possible to find a long history of that risk, whereas previously it would have been lost through summarisation and fixed reporting processes.

 

Collaborative Data Sets

More big data stores are being created as the industry becomes more collaborative and uses increasing numbers of fintech solutions and platforms. With this change come new ways to analyse data and provide new insights.

For instance, through the automation of collateral exchange, an historical store of margin calls, payments and disputes has been created. This history provides a resource for banks to understand their performance in accurately issuing and making margin calls based on derivatives and compare their performance to that of the industry as a whole. The example below shows how a firm can be benchmarked while holding other institutions data private.

These types of analysis are new and could not be delivered without the centralised collaborative data model. It can prove to be instrumental in improving firms’ overall operational efficiency and client service.

It also provides an opportunity for Machine Learning techniques, based on big data sets, to analyse and predict payments requests which are likely to be disputed and potentially identify causes before an actual dispute is even raised. This type of ‘self-healing’ process can only be enabled by a large history of data through which algorithms can be trained.

In the case of Initial Margin (IM) calculated by ISDA SIMM* a new set of challenges have been introduced through having a two-sided risk calculation as part of the process of deriving payment information. This adds another level of complexity to the resolving of disputes; however, the potential offered by having large volumes of data opens up new options on how this challenge could be solved. The long history of Common Risk Interchange Format (CRIF)** data provides a long-term view of the sensitivities for most OTC derivatives, which can enable firms to identify basic issues like stale market data day over day. However, as with most detailed analysis differences in models, they can also be identified through looking at differences over long periods of time. Identification of these types of model discrepancies can help firms to be more proactive about reviewing their modelling deficiencies to ensure that differences don’t lead to disputes.

 

Looking ahead

The sheer volume of data can be an industry-wide challenge with firms having to manage disparate, needlessly duplicated and ultimately overwhelming information. Creation of an industry standard for reporting and analytics is, therefore, crucial to enable firms get clarity and valuable insights from the masses of data and centralise the information as a single data layer. Acadia has designed Data Exploration (DX) suite to be one-of-its-kind big data analytics platform to help sell-side, buy-side and fund administrators see its market positioning, trends and analysis of industrywide metrics.

The impact of big data will only grow and the industry is left with no choice than to evolve the use of technology, whether that is to drive quant strategies for hedge funds, more dynamic forms of risk management or larger shared industry data sets. All of these applications rely on underlying big data technology platforms to provide distributed analysis capabilities. As these capabilities continue to develop so will the types of analysis which are available to firms.

*The ISDA Standard Initial Margin Model (ISDA SIMM™) is a common methodology for calculating initial margin for non-centrally cleared derivatives, developed as part of ISDA’s Working Group on Margin Requirements (WGMR) to help market participants meet the BCBS-IOSCO margin framework for non-cleared derivatives.

** The CRIF file (Common Risk Interchange Format) is the industry template used to hold and exchange sensitivity data. ISDA’s calculation specifications are used to produce Delta, Vega and Curvature sensitivity numbers at Risk Factor-level

 

 

 

 

 

 

 

 

 

 

 

 

Business

Accounting Automation in the Future

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Accounting automation is the process of streamlining repetitive tasks in financial processes. For example, some processes like invoicing are time-consuming and repetitive. Automation can reduce manual labor and save businesses both time and money. Also, it helps improve accuracy, reduces errors, and provides more accurate financial reporting.

Accounting automation in the future will be increasingly important for businesses to stay competitive. But every new change comes with both advantages and challenges. Let’s dive in to get ready for this future trend.

 

Potential Future Benefits of Accounting Automation

Increased Efficiency and Cost Savings

Accounting automation is a great way to increase efficiency and cost savings. For example, AI bookkeeping uses advanced algorithms to automate many accounting tasks. So, companies can track expenses, prepare financial reports, and more using AI.

It reduces the time needed for manual entry. So, businesses can spend fewer labor hours on tedious processes. They can increase efficiency by freeing up resources for more strategic work. It also helps reduce errors and inconsistencies associated with manual processes. So, the cost of compliance is lower because of greater accuracy.

 

Improved Accuracy and Reliability

Accounting automation can improve accuracy and reliability in accounting processes. For example, Automating bank reconciliation is less prone to errors from human mistakes or miscalculations. You can automate the process to identify discrepancies between the bank statement and accounting records. It helps to ensure that financial reports remain accurate and reliable. So businesses can take corrective action faster than processing data manually.

 

Streamlined Business Processes

Streamlined business processes involve eliminating unnecessary steps, reducing paperwork, and automating repetitive tasks. This allows businesses to focus on higher-value activities, such as developing new products, improving customer service, and developing strategic plans for the future.

 

Making a Better Decision

Accounting automation can enhance decision-making in 3 ways.

1. It enables businesses to access real-time information from multiple systems. So they can identify trends for better decision-making.
2. Automated accounting also helps with forecasting, budgeting, and auditing tasks. It enables businesses to be more proactive in their decision-making processes.
3. Also, automated accounting tools can integrate with enterprise resource planning (ERP) systems. They can manage data across the enterprise and make concise decisions that are favorable to the company as a whole.

 

Increase Customer Satisfaction

Accounting automation can help businesses increase customer satisfaction by streamlining their processes and providing a more efficient customer experience. For example:
4. Automated accounting systems can automate tedious manual tasks such as invoicing, data entry, and payroll processing. This allows businesses to focus on other aspects of their operations that are more important for customer service.
5. Automated accounting systems can also provide customers with more accurate and timely financial information. The information can help them make better decisions about their finances.
6. Also, accounting automation enables businesses to respond quickly to customer inquiries. It helps reduce wait times and improve the overall customer experience. So, you can build better relationships with their customers.

 

Improved Accessibility

Accounting automation takes place online or comes with cloud-based solutions. So, you can access your information and do your job from anywhere instead of being confined to one spot.

 

Challenges to Implementing Accounting Automation in the Future

Cost of Technology Infrastructure Upgrades

Automating an accounting system often requires businesses to invest in new hardware and software, such as servers and other associated equipment. These upgrades come with a hefty price tag that may be difficult for small businesses to afford.

There are also extra costs, such as installation fees, setup charges, software licensing fees, cloud storage costs, and maintenance fees.

 

Training Requirements for Staff Members

Accounting automation involves using advanced technology to automate certain processes. So, it creates a need for trained staff members who can handle the new technology. Training requirements vary depending on the type of software used.

Some common training includes record-keeping procedures, software applications, and troubleshooting skills.

 

Regulatory Compliance Issues

Accounting automation can be a time-saver, but it also requires firms to be aware of the applicable rules and regulations. Companies must ensure that their automated systems are compliant with relevant laws and regulations such as Generally Accepted Accounting Principles (GAAP), International Financial Reporting Standards (IFRS), and other applicable accounting standards.

Besides, they must also comply with legal requirements related to taxes, financial statements, and other reporting obligations.

So, businesses must consider the complexities of regulatory compliance when automating accounting.

 

Security and Data Protection Concerns

As businesses move their accounting processes to the cloud, they are exposed to a wide range of potential security risks. Data breaches can cause significant damage to the business’s financial and reputational integrity. Besides, the complexity of automated accounting systems can make it difficult to identify and detect suspicious activities or errors in the system.

To ensure data is kept secure, businesses must have strong measures in place to protect against unauthorized access, encryption, and regular backups of data.

Furthermore, companies must train their staff on the proper use of the system. It helps staff to know how to protect confidential information from being accessed or misused by unauthorized personnel.

Businesses may also need an experienced IT team to monitor and maintain the system to keep up with any changes or updates for optimal performance.

 

Final thoughts

Accounting automation has come a long way in the past few decades. It is likely to continue to advance in the future. As technology continues to evolve, more businesses will likely begin taking advantage of automation in their accounting processes. So, businesses should be aware of the potential challenges and prepare to stay competitive.

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Banking

How banks can help customers during the cost of living crisis

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 Lavanya Kaul Head of BFSI, UK & Ireland, LTI Mindtree

 

Surging energy and food prices are significantly driving up household expenditure, which means living standards in the UK will fall to 2.2% this year, according to the Office for Budget Responsibility. This is the biggest drop in any single financial year since the records began in 1956-57.

It’s a tough situation for many consumers who are still struggling with financial hardship following redundancies and pay freezes from the pandemic. According to TSB’s Money Confidence Barometer, 82% of people have experienced an increase in the day-to-day cost of living. This resulted in almost a quarter of them using their savings, while one in five changed their usual spending habits and behaviours.

As the financial situation worsens, consumers are increasingly relying on their banks for help and support. But, while banks can’t control inflation, energy or food prices, they can play a more supportive role by adapting their services to offer stronger customer service, better tools for financial management and be more flexible with loan repayments.

 

Strengthen customer service with intuitive AI solutions

Since the pandemic, consumers have changed the way they bank, using more mobile apps for primary banking rather than going into physical branches. This provided an opportunity for banks to accelerate their investment in digital services including automation and offer customers more support during the cost of living crisis.

Lavanya Kaul

Effective tools include AI-powered chatbots which respond intelligently to customer enquiries to quickly help troubleshoot problems and provide useful advice. But to be successful, you need to ensure you strike the right balance between an efficient and convenient process and creating a personalised experience. Customers need to feel like you understand and care about their problems and are here to help, rather than just fobbing them off with a monosyllabic bot. To avoid this, banks need to embrace intuitive AI solutions to ensure that empathy comes across in all automated interactions with customers. While doing that, messaging is key. In times of stress, we don’t function as well and financial struggles are a huge stressor. The clearer the message and the simpler the instructions, the better.

Financial education, when combined with technology solutions such as open banking, can offer more long-term solutions for people to navigate their finances. This can help put more information into the hands of the consumer to help them grasp their financial situation better. Some banks have cracked this with innovative solutions like HSBC’s Financial fitness score tool that can analyse your money habits and signpost you towards ways to improve your financial health. This may include joining one of the financial education webinars run by the bank or having a ‘financial health check’ with a member of staff.

 

Launch money management features & apps

Introducing money management features and apps to increase the visibility of a customer’s financial situation, empowers them with the information they need to make smarter choices.

TSB offers Spend & Save and Spend & Save Plus current accounts which include a savings pot that enables customers to put extra money aside when they can and an auto-balancer feature that automatically transfers money from the savings pot into their current account if their balance falls below a certain level. This allows them to start building up savings and protects them from unnecessary overdraft charges.

Personal financial management (PFM) apps also help customers get a better understanding of their finances. These connect with a customer’s bank account and enable them to keep a close eye on their spending habits and track upcoming bill payments. An example is Prism, a PFM app which allows customers to manage bill payments by sending them reminders about due dates. It also provides a summary of their income, account balance and monthly expenses at a glance, therefore consolidating all their financial information in one place and saving time on bill payments.

Lloyd’s Banking Group and HSBC launched a subscription management tool for all customers on mobile, allowing them to see and cancel recurring card payments for things like TV subscription services. HSBC says that during the first quarter of the year, it led to customers dumping around 200,000 subscriptions.

 

Introduce payment holidays

While improved customer service and financial management tools are important support tactics, they might not be enough for more vulnerable customers. For example, those who are about to default on mortgage payments or loans due to redundancy or periods of ill health need banks to do more, like offering payment holidays. Banks relaxed the rules for payment holidays during the pandemic, so they should consider doing it again to help more vulnerable customers through the crisis. Customers need to understand that they are not alone when experiencing financial difficulties and that help is available

 

Ride out the crisis together

As inflation reaches a 30-year high, customers are now more reliant than ever on banks for guidance and support. But to provide the right level of service, they need to move away from their traditional ways and behave more like technology companies by embracing automated solutions to create the right products and services for customers. Then layer on top of that the need for more personalised and empathetic customer interactions, as well as consider additional support for more vulnerable customers.

While we don’t know how long the cost of living crisis will last, what we do know is that the pressure on household finances is likely to get worse before it gets better. Therefore, banks need to step up, be the supportive partner and do whatever they can to help customers. After all, the only way we can ride out the crisis is by supporting each other and working together.

 

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