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How established financial organisations can break down the barriers to innovation

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By Tim FitzGerald, EMEA Financial Services Sales Manager, InterSystems

 

Often perceived as more agile and innovative than traditional banking institutions, fintechs have grown rapidly by offering new services and high levels of personalisation. Such is the fintechs’ sophistication and quality of customer experience, the incumbent financial institutions can see how they must emulate them or seek their collaboration. As far back as 2017, 82% of global financial services firms said they expected to increase fintech partnerships, with 88% concerned they would lose revenue to innovators.

Established banks have become sophisticated in their use of data to create new services and customer-facing phone-based applications, for example. Yet they sometimes struggle when it comes to the innovation and deep levels of personalisation that increase revenues from existing customers and attract new ones. Institutions with a long heritage have masses of customer data but it is often in highly disparate systems built up over time and difficult to bring together. This is where the fintechs sometimes have specialist expertise. They know how to use all kinds of data to provide the slick interfaces, and highly personalised and innovative products and services that customers want.

Tim FitzGerald

If they are to match the creativity and agility of fintechs, large financial organizations need to enable their business teams to extract more meaningful insights from the masses of data in their grasp. They can only do that if they have the technology to break down their internal silos, improve data quality and provide quick access to analytical insights.

 

Research shows the data challenges facing incumbent financial organizations

InterSystems-sponsored research by FIMA in the US and Canada reveals why so many financial organisations find breaking down these siloes so difficult. FIMA asked 250 financial leaders from retail and investment banks, insurance and wealth management companies how they make actionable insights available to their business teams.

More than half of all respondents (54%) said siloed data was one of the biggest barriers to innovation in their business. Nearly seven-in-ten (68%) said creating a single and consistent representation of data by removing the silos was a challenge. But culture and conservatism also have an effect. Almost half (49%) said there was a lack of understanding or buy-in more widely within their organisation, illustrating the difference in mindset between larger, multi-faceted financial institutions and newer, smaller organisations with fewer lines of business.

It’s not surprising that bringing the data together meaningfully is such a challenge for banks. Large financial institutions have many different interactions with their customers, ranging from business and current accounts to mortgages, loans, insurance and investments. It is often difficult to obtain a 360-degreee view of each customer, their requirements and patterns of behavior when data is in different formats and systems.

To deliver high-quality customer experiences, financial institutions must be capable of collating and analysing all this data in near-real time. Only then can they produce the insights that meet the heightened fulfilment and expectations of customers and clients used to the customer experience of online retailers.

In other words, financial organsations need a holistic view of their clients, whether institutional, business or consumer, so they deliver more effectively. Their business teams need fast access to the critical insights for the creation and execution of more effective customer strategies.

Institutions can achieve this by using a more innovative architecture, such as the smart data fabric. This helps democratise insights by providing accurate visibility across the entire business. Smart data fabrics connect data inside and outside the organization, ensuring it is accurate and current, incorporating real-time event and transactional data with historical information and inline analytics capabilities.

 

Recognition of the need for new priority-setting in data management

What is encouraging from the FIMA research is that significantly more than half of all organizations recognise they must democratise the use of data internally. More than six-in-ten respondents (62%) said improving access to siloed data was at or near the top of their list of priorities for the next 12 months. Employing data in strategic decision-making is also a top-three priority for many.

One statistic helps explain why democratisation of data is a priority – in nearly nine-in-ten organisations surveyed (85%), IT employees have to spend between a quarter and half their time helping their colleagues find the data they want and then extract the insights from it. This is a substantial amount of time (and cost) that the smart data fabric can address. By embedding analytics capabilities, including data exploration, business intelligence, natural language processing, and machine learning, the smart fabric makes it faster and easier for line-of-business managers to gain new insights on which to build new services and deliver an entirely new level of personalisation.

 

Integrating fintech applications

The research also highlighted how organisations now realise they currently lack the technology to achieve their goal of becoming a data-driven business. More than half of them (55%) plan to implement new data management solutions.

Integrated data management solutions will certainly help establish standards for data governance across the organisation and help remove the internal barriers to the flow of data. But in the face of fintech innovation, what institutions also need is the ability to integrate cloud-native fintech solutions to work seamlessly with their own applications and data sources. The banks must be fully capable of incorporating these fintech applications into their production environments to help them innovate faster on a wider range of business initiatives.

Some organisations still undertake such integration manually, coding point-to-point between solutions, which is costly and time-consuming. It is also error-prone and difficult to extend. A real-time bi-directional gateway solution will enable them to overcome these obstacles and difficulties, connecting and integrating cloud-native fintech applications and data stores much faster, with a much simpler architecture than would otherwise be possible. It provides real-time, bi-directional, consistent and secure data-sharing between the fintech application and the incumbent’s production applications, wherever the production data may be.

This is one of the increasing number of ways that banks and institutions can employ more advanced smart data management technologies to overcome the challenges they face when seeking greater innovation, efficiency and new levels of personalization and ease-of-use for customers.

 

The 360-degree view of data is a necessity

The FIMA research has shown the scale of the challenge and pointed to an appetite for change and new approaches. By implementing a holistic, 360-degree view of all their data and embedding analytics in a seamless fabric, established institutions that sense they must innovate, will move quickly towards these goals. They will increase their time-to-value, acquire far greater organizational creativity and agility and introduce significant new efficiencies.

This will enable them to compete and collaborate with fintechs in a more competitive world where the ability to manage and analyse data and share insights rapidly, will be critical.

Business

Unlocking the Power of Data: Revolutionising Business Success in the Financial Services Sector

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Suki Dhuphar, Head of EMEA, Tamr

 

The financial services (FS) sector operates within an immensely data-abundant landscape. But it’s well-known that many organisations in the sector struggle to make data-driven decisions because they lack access to the right data to make decisions at the right time.

As the sector strives for a data-driven approach, companies focus on democratising data, granting non-technical users the ability to work with and leverage data for informed decision-making. However, dirty data, riddled with errors and inconsistencies, can lead to flawed analytics and decision-making. Siloed data across departments like Marketing, Sales, Operations, or R&D exacerbates this issue. Breaking down these barriers is essential for effective data democratisation and achieving accurate insights for decision-making.

An antidote to dirty, disconnected data

Overcoming the challenges presented by dirty, disconnected data is not a new problem. But, there are new solutions – such as shifting strategies to focus on data products – which are proven to deliver great results. But, what is a data product?

Data products are high-quality, accessible datasets that organisations use to solve business challenges. Data products are comprehensive, clean, and continuously updated. They make data tangible to serve specific purposes defined by consumers and provide value because they are easy to find and use. For example, an investment firm can benefit from data products to gain insights into market trends and attract more capital. These offer a scalable solution for connecting alternative data sources, providing accurate and continuously updated views of portfolio companies. Using machine learning (ML) based technology enables the data product to adapt to new data sources, giving a firm’s partners confidence in their investment decisions.

Suki Dhuphar

But, before companies can reap the benefits of data products, the development of a robust data product strategy is a must.

Where to begin?

Prior to embarking on a data product strategy, it is imperative to establish clear-cut objectives that align with your organisation’s overarching business goals. Taking an incremental approach enables you to make a real impact against a specific objective – such as streamlining operations to enhance cost efficiency or reshaping business portfolios to drive growth – by starting with a more manageable goal and then building upon it as the use case is proved. For companies that find themselves uncertain about where to begin their move to data products, tackling your customer data is a good place to start for some quick wins to increase the success of the customer experience programmes.

Getting a good grasp on data

Once an objective is in place, it’s time for an organisation to assess its capabilities for executing the data product strategy. To do this, you need to dig into the nitty-gritty details like where the data is, how accurate and complete it is, how often it gets updated, and how well it’s integrated across different departments. This will give a solid grasp of the actual quality of the data and help allocate resources more efficiently. At this stage, you should also think about which stakeholders from across the business from leadership to IT will need to be involved in the process and how.

Once that’s covered, you can start putting together a skilled team and assigning responsibilities to kick-off the creation and management of a comprehensive data platform that spans all relevant departments. This process also helps spot any gaps early on, so you can focus on targeted initiatives.

Identifying the problem you will solve

Now let’s move on to the next step in our data product strategy. Here we need to identify a specific problem or challenge that is commonly faced in your organisation. It’s likely that leaders in different departments, like R&D or procurement, encounter obstacles that hinder their objectives that could be overcome with better insight and information. By defining a clear use case, you will build a real solution to a challenge they are facing rather than a data product for the sake of having data. This will be an impactful case study for your entire organisation to understand the potential benefits of data products and increase appetite for future projects.

Getting buy-in from the business

Once you have identified the problem you want to solve, you need to secure the funding, support, and resources to move the project ahead. To do that, you must present a practical roadmap that shows how you will quickly deliver value. You should also showcase how to improve it over time once the initial use case is proven.

The plan should map how you will measure success effectively with specific indicators (such as KPIs) that are closely tied to business goals. These indicators will give you a benchmark of what success looks like so you can clearly show when you’ve delivered it.

Getting the most out of your data product

Once you’ve got the green light – and the funds – it’s time to put your plan into action by creating a basic version of your data product, also known as a minimum viable data product (MVDP). By starting small and gradually enhancing with each new release you are putting yourself in the best stead to encourage adoption and also (coming back to our iterative approach) help you secure more resources and funding down the line.

To make the most of your data product, it’s essential to tap into the knowledge and experience of business partners as they know how to make the most of the data product and integrate it into existing workflows. Additionally, collecting feedback and using it to improve future releases will bring even more value to end users in the business and, in turn, your customers.

Unlocking the power of data (products)

It’s crucial for companies in FS to make the most of the huge amount of data they have at their disposal. It simply doesn’t make sense to leave this data tapped and not use it to solve real challenges for end users in the business and, in turn, improve the customer experience! By adopting effective strategies for data products, FS organisations can start to maximise the incredible value of their data.

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Business

Making the Maths Work: Addressing Inflation Challenges through Measuring and Managing Risk

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By

Matt Clementson, Head of Enterprise UK&I

Persistent inflation is highly troublesome for every business – with or without a recession. In addition to causing unexpected expenses, it complicates decision-making around stabilising wages, setting product prices, and investing in new areas for growth. Meanwhile, stock and bond prices plummet when alarming inflation data arrives and interest rates increase. It’s time to run leaner, making the reassessment of the strategic objectives highly urgent.

With a seat in the boardroom, CFOs can guide thoughtful discussions covering everything from procurement, resource allocation, and manufacturing to the alignment of business purpose with operational tactics and goals. CFOs must also rethink how their business measure and mitigate risk. Understanding the business’ vulnerability, they can add considerable value to their business by identifying risks early and making organisations accountable for mitigating them.

When the economy becomes uncomfortable, the mathematics behind business operations no longer work seamlessly. During more comfortable times businesses have the luxury to accept some degree of inefficiency and low productivity – but in times like these that’s no longer the case.

So now it’s more important that ever for CFOs to use the right tools and technology to manage and mitigate risk and build business resilience.

Enhancing visibility to measure and manage risk:

To navigate through periods of high inflation, CFOs need technologies that provide comprehensive visibility, and enable informed decision-making, in order to optimising cash flow, minimise     costs and manage risk in a transparent and efficient way.

1. Simplify confusing processes to gain moments of clarity

Effective risk management starts with integrating data from various sources within the organisation. By consolidating data from finance, operations, procurement, and sales, CFOs can gain a holistic view of the business landscape. This integration enables them to identify potential risks associated with inflation, such as rising costs, supply chain disruptions, or changes in customer demand patterns. With access to comprehensive and real-time data, CFOs can make informed decisions that mitigate the impact of inflation on the organisation.

A good first step is to unify travel, expense, and invoice solutions, so that finance teams can integrate and streamline operations and scale spend processes without adding additional resources.

2. Make spending decisions with data-driven accuracy

Once data is integrated, CFOs can leverage advanced analytics techniques to identify patterns, trends, and potential risks. Predictive analytics can help identify inflationary pressures, allowing businesses to proactively adjust pricing strategies or negotiate favourable terms with suppliers. Additionally, scenario modelling can simulate the impact of different inflation rates on the organisation’s financials, enabling CFOs to devise appropriate strategies for managing risk. By harnessing the power of analytics, CFOs can navigate inflation challenges with greater confidence and precision.

3.Driving business agility through automation

Facing a myriad of disruptors, companies in every industry are making strategic decisions aimed at remaining competitive in the market and with their people. Digitisation, standardisation, and automation will be critical as businesses focus on solving problems for their customers in innovative, lasting ways

AI technologies, such as machine learning algorithms, can analyse vast amounts of data to uncover hidden insights and patterns. And with automated, customisable controls, CFOs can keep their firm agile – re-adjusting spend controls to match the corporate travel and expense (T&E) policy whenever their business needs to adapt or pivot. Only then will spending insights allow them to review how policies impact business performance and continue to optimise cash management.

Making the maths work

In a business environment plagued by persistent inflation, CFOs play a crucial role in addressing the associated challenges. By rethinking how their organisations measure and manage risk, CFOs can enhance their decision-making capabilities and add significant value. The integration of data, advanced analytics, and AI technologies enables CFOs to build resilience, standardise processes, ensure compliance, and deliver insights to the entire enterprise. By making the maths work in the face of inflation, businesses can navigate uncertain economic times with confidence and stay on the path of sustainable growth.

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