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Data continues to grow for banks

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Data continues to grow for banks

By Chris Probert, partner and data practice lead at Capco 

Banks have always held vast amounts of data within their organizations but with the recent exponential growth in data volume, efficient usage and governance of data has become firmly established as a source of competitive advantage for financial institutions.

The ability to identify, monitor, interpret, and extract value from data is something that many organizations have historically struggled to achieve, mostly due to poor tracking of data across the enterprise. Data lineage serves as a tool to track data from its origins, through any transformations it may undergo to its ultimate consumption.

Financial institutions have an opportunity to provide major value to their organizations by using data lineage to provide benefits along three dimensions: regulatory compliance, control optimization and cost reduction.

Why data lineage – stopping Chinese Whispers

To understand how data lineage is useful, it is important to acknowledge the obvious: data in a large organization is not held in a single repository, but rather flows across many systems and databases. During this proliferation there is a risk to data quality, security and availability. For example, as anyone familiar with the game of Chinese whispers knows, despite best intentions an original message can swiftly metamorphize into something completely different as it moves down the chain from person to person.

Information is no different – data can become compromised every time it enters a new system or database. Data lineage offers a solution to this issue, as it allows compromised data to be hunted down efficiently and quickly.

Traditional data lineage and challenges

Data lineage rose to prominence due to requirements in the wake of the financial crisis as regulators sought evidence to substantiate the veracity of stress-test reporting for banks. Since then, regulations such as Markets in Financial Instruments Directive II (MiFID II) and General Data Protection Regulation (GDPR) among others, have required financial institutions to implement data lineage procedures to demonstrate the reliability of their reporting.

However, data lineage is currently underutilized. It largely focuses on the mechanical movement of data and less on its contextual flow; furthermore it is often targeted towards an IT audience, mapping technical data. In falling back on this traditional approach to data lineage, businesses are not tapping its full potential: namely, the insights provided through enhanced clarity around data movement and transformation.

For data lineage to be meaningful beyond mere regulatory compliance, traditional lineage must expand to address the following dimensions: who, what, where, when, why, and how. Establishing industry standards or accepted practices would help provide a structure for capturing these different dimensions and drive business value.

Three ways to make lineage useful

A big challenge facing organizations that want to use data lineage is the lack of standards around its depiction. There are significant differences how lineage is represented, ranging from spaghetti diagrams –which prove overwhelming to a business audience -through to process diagrams that often leave out data and technical representations of architecture and infrastructure that obfuscate the nuances of transformation.

There are three critical guiding principles to make data lineage useful and standardized: make it business friendly; highlight context and ownership of data; and show how data is transformed and used.

Making data lineage more attractive to businesses can be achieved by ensuring the presentation of lineage is easy to read and understand via business-centric nomenclature and easy-to-consume forms and applications. It is also important with data lineage to show only those elements that are critical to the output, or would impact the quality of the output if compromised. These are typically referred to as ‘critical data elements’ (CDEs) or ‘key data elements’ (KDEs).

The next step is understanding the context of the data –  vital to setting up standardized data lineage diagrams. Organizations need to start by determining the connections that show who owns the process, the application, and the data element. Given the size and complexity of financial institutions, this can be a gargantuan undertaking. Once the data ownership structure has been established, the enterprise can begin to align the process and create a visual diagram of data lineage.

Visualizing the process by looking at the connections – application ownership, process ownership, data quality, data usage, access requests and the number of outstanding data issues – can help drive improvements, identify risk, and strengthen process governance.

Once each step is documented and unique data elements identified and validated by the relevant subject matter experts, an organization will have clarity around ownership of each stage of the process and the associated data elements. The enterprise will then be able to leverage process diagrams to better understand what happens to the data, not least how it is transformed and used throughout its lifecycle.

It is essential to know how data is moving, not just where it is coming from and going to. In determining the ‘who, what, when, where and how’ of data flow we can answer questions related to risks, whether they can be mitigated and the efficiency or otherwise of existing data management and processing systems. This leads to a more secure and streamlined data flow.

Cutting costs and boosting efficiency

Using data lineage, financial institutions can easily visualize the flow of data through systems and applications, making it allowing distinct patterns within an organization’s data – be they good or bad -to be identified.

Via data lineage organizations have an opportunity to optimize costs and processes by minimizing repetition and redundancy within their systems. For example, during account set-up an organization can end up with three separate applications performing just one function. Wherever data is handled by multiple applications for the same task that should serve as a red flag. This kind of pattern occurs often in organizations undergoing rapid growth through mergers and acquisitions or the launch of new products and services.

Without data lineage inefficiencies can remain hidden, leading to wastage due to improper data visualization and a lack of insight into applications. Data lineage allows organizations to clearly align“ business area” “process” and “applications” using visual diagrams that create a holistic picture of data management across the enterprise.

Once a redundancy in data processes is discovered, organizations can rapidly eliminate the associated wastage by enhancing one application to handle all closely related functions while retiring the rest.

Patterns for risk management

Determining where to implement controls within a given data supply chain is crucial for maintaining data quality and integrity. Data lineage techniques can quickly identify inefficiencies and risks that arise in common data control methods.

Two types of controls play significant roles in maintaining the quality of data. The first is an accuracy control, which is best implemented at the system of origin (where data is first created or entered). The second is a consistency control, which supports and maintains the accuracy of the data throughout the entire data supply chain. The recommended implementation of the consistency control is in applications downstream from the system of origin.

These two controls, when effectively maintained, will reduce in efficiency and duplicate controls, thereby improving data quality. However, organizations often unnecessarily build multiple accuracy controls into downstream systems. A classic example is a data warehouse or data lake where consistency controls would be the better choice. This leads to data in the warehouse or lake to diverge from the system of origin, creating a maintenance nightmare and leading to cost increases.

Data lineage allow organizations to make the correct choice between which applications require  accuracy controls and which need consistency controls. If controls have been already implemented, it will highlight any redundancy, allowing the organization to optimize on controls and save costs.

As data flows from one application to the next within an organization there is an inherent security risk. The most vulnerable applications are those that are external-facing or vendor-hosted. Data lineage can spotlight such applications and in doing so lift the veil on security risks. Existing data controls can be reassessed and enhanced as necessary, reducing cyber risk and protecting data as it moves across the enterprise.

Conclusion

Data lineage will continue to evolve. At the same time, its power to help organizations think more clearly about their data, control frameworks and process optimization is yet to be fully realized.

Financial institutions that successfully leverage data lineage will drive value through cost reductions arising from the elimination of redundancies and unnecessary manual processing – and hence while simultaneously mitigating risks related to data quality, integrity and security via better controls.

Adopting common standards and injecting contextual content will facilitate the implementation of lineage in a business-friendly fashion and spur adoption. In today’s world of Big Data, data lineage offers organizations quantifiable business value as they move towards harnessing data as a source of competitive advantage.

Banking

How banks can take on Google in the race for AI talent

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How banks can take on Google in the race for AI talent 1

By Nicola Sullivan, solutions director at candidate engagement tech firm Meet & Engage

The events of 2020 have made the battle for AI talent more ferocious than ever. In a volatile landscape where innovation is key, multinational firms are rolling up their sleeves for the inevitable scrum ahead.

For incumbent banks, the stakes are intimidatingly high. In one corner stand the fintech startups: the likes of Revolut and Monzo, who are snapping up AI-literate graduates while laying down pressure for capacity in exactly that area.

In the other corner, we find the Silicon Valley contenders of Amazon, Facebook and Google, who have phenomenal pay packages – not to mention glamour and visibility – on their side. And technologists with a finance background loom firmly in their crosshairs (Facebook employs hundreds of ex-banking recruits).

This unsettling picture is intensified by a chronic tech shortage: in a recent study by AI firm Peltarion, 83 percent of AI decision-makers agreed that a deficit of deep learning skills was seriously hampering their competitiveness. But, with the global impact of AI on financial services companies set to hit $140 billion in productivity gains and cost savings by 2025, banks need to find a way to break ahead and secure the AI talent they need. Here’s how:

Fish from a wider talent pool

We tend to think of AI in relation to a very niche set of qualifications. Yet in reality, it’s a fast-moving sphere that also requires a host of soft transferable skills such as problem-solving, agility, great communication and a sound analytical mind. In short, it’s less about what a candidate knows/does, and more to do with what they could know or do.

It’s worth thinking about whether you are being open-minded enough in your interpretation of tech talent. Do the AI roles you’re looking to fill need specific skills and criteria, or are they better suited to people who are inherently curious, intelligent and quick to learn?

Depending on the answer, you may want to expand your search from the bright young things of MIT or Berkeley to other related careers or older candidates with transferable skills. You may even want to look internally for the next generation of tech talent.

For example, if a bank’s customer-facing roles are declining but AI supply is not keeping up with demand, maybe this is a problem that could fix itself. The bank in question could run a two-week internal virtual AI internship to test interest, with the aim of rechanneling internal talent and avoiding redundancies. If AI is as critical as all forecasts suggest to the future of finance, investing in a more comprehensive approach like this may make a lot of sense.

Then there’s also the question of underrepresented groups. The proportion of black or latino people at major tech companies remains depressingly low, while women make up only a quarter of computing roles.

As well as driving equality, this issue of diversity is also a market gap that could be used for competitive advantage by banks. But doing so requires a deep-seated strategy that addresses the root reasons why candidates from these groups are turning away from tech. Issues such as lack of career development and accessible education need to be solved at ground level from the inside-out; an effort that begins before, or in tandem with, recruitment.

Make your recruitment process personal and transparent

When you’re fighting for top AI candidates who have the world at their fingertips, it’s not enough to bundle them through a generic Applicant Tracking System. You have to actively woo them, and get them on-side with your vision and community. This is especially important for millennials and Gen Z recruits, who are more purpose-driven than their predecessors.

Live online chat sessions hosted by high-profile speakers across the business is one tactic our banking clients have seen great success with here. For example, a shortlisted group of technologists get to meet with a bank’s CTO or Chief Human Resources Officer via a group chat (which they can join anonymously if they want to), to ask questions and find out more about a company’s technology roadmap and cultural ethos.

This is a rare opportunity to give candidates real takeaway value; even if they’re not thinking about leaving their current job, few will turn down the chance of time with the person who runs cybersecurity at a major bank. And this person will invariably be able to communicate a much better sense of culture than a third-party recruiter can.

Visibility is also important here: if you want to attract more BAME or female candidates, you need to have lead BAME or female technicians as a vocal part of the recruitment process, showing what success in your company looks like. If you don’t have people to fulfil these roles, you need to go back and address that rather than making empty statements.

Opening the doors to your company in this way is a winning strategy for tech candidates: it’s a “wrapper” to put around them and make them feel wanted, welcome and motivated – even when a recruitment process lasts a little longer than you’d like.

Talk like yourself but walk like a tech expert

Part of the openness needed to recruit key tech talent is about being authentic, too. There’s a tendency among some finance incumbents to “get down with the kids” and appear more like their disruptive competitors than they truly are. If you are a long-established brand in the banking world, with a good track record of developing careers, that alone is enough to attract AI technologists – you have a lot to offer, and you don’t need to put on a guise.

Equally, if you do have work to do in being more accessible to potential candidates, focus on real progression rather than image. This may mean putting through measures to build awareness and role modelling around recruitment diversity, or enhancing employee wellbeing.

With mental health issues on the rise in the workplace, a co-managed wellness programme of fitness and community events can make the difference between which way a candidate sways in a roomful of enticing options. This is especially true since banks – for all their boardrooms traditions – have a reputation amid technologists for a better, less brutal work-life balance than Silicon Valley.

Lastly, banks need to walk the walk when it comes to tech-enabled recruitment. However hard you try to make it personal, most candidate enrollments will involve a degree of automation at some stage – and it’s important to make that process as quick and slick as possible. For a candidate with consumer-grade tech experience, first impressions count: they want to know that this is a place that will recognise and nurture their skill set. So instead of a long, clunky application process, maybe consider a virtual assessment centre or a sophisticated chat bot, which can capture essential information in a fast, engaging way.

Recruiting the world’s top tech talent isn’t a question of magic or even necessarily a huge pay cheque. Instead you need to weave together these “micro-moments” that signal your bank’s character, integrity and technical ambition. Do this, and you stand a good chance of persuading leading AI candidates to skip the queue and come directly to you.

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Banking

1.4 million customers to stop using bank branches due to COVID

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1.4 million customers to stop using bank branches due to COVID 2

1.4 million customers to stop using bank branches due to COVID 3 8.4 million customers had already stopped visiting branches in person before lockdown

1.4 million customers to stop using bank branches due to COVID 4 However, three quarters (74%) of customers will return to banking in branch after the pandemic

1.4 million customers to stop using bank branches due to COVID 3 Of those who plan to return to branches, over two thirds (69%) will only return when they absolutely need to

1.4 million Brits (3%) don’t intend to go back to a bank branch again after the COVID pandemic, according to a new survey by personal finance comparison site, finder.com

A further 1.6 million (3%) said they don’t have an account with a high-street bank, meaning a total of 3 million Brits don’t have a need for physical branches.

This number may rise, as 8.4 (16%) million Brits had stopped using their bank’s branches before lockdown and are not sure if they will ever return.

However, not everyone has gone completely digital as 3 in 10 British banking customers (29%) have already returned to using their bank’s branches, with an additional 44% of customers planning to return soon.

Of these people who plan to return in the near future, over two thirds (69%) will only return when they absolutely need to and their problem cannot be solved online or over the phone.

While a third of those consumers (31%) are waiting for a COVID vaccine or treatment before they go back to their local branch.

This means that eventually, three-quarters of Brits (74%) will return to banking in-branch the way they did before lockdown.

However, they may face a longer journey than they previously did to find a branch. Data from ONS shows 25% of branches have closed in the UK since 2012 and this decline in branches is likely to continue if people follow through with their plans to avoid branches.

Customers in Northern Ireland will go back to banking in branches more so than those in any other region, with 85% of customers here saying they have already returned or plan to do so soon.

Interestingly, a quarter of customers (25%) in the East Midlands had already stopped banking in branches, making this the area with the most customers who no longer use branches.

Those in the North East are set to follow the same path as residents in the East Midlands, with 5% of customers in the North East saying they will stop using branches in the future.

To see the research in full visit: https://www.finder.com/uk/banking-branch-usage

Commenting on the findings, Jon Ostler, CEO at finder.com said:

“Lockdown has quickly changed many aspects of our lives and our banking behaviour was no different. Not being able to visit bank branches in person meant many consumers had no option but to start using online banking and bank’s mobile apps. These are generally easy to use and intuitive so you would expect some of these new converts to stay away from branches going forward.

“While the digital-only banks excel at their app offering, previous research we carried out found that sentiment towards these banks fell almost three times as much during lockdown than towards high street banks. This could be a sign that the quality of apps and online banking from high street banks is catching up.”

1.4 million customers to stop using bank branches due to COVID 6
Methodology:

Finder commissioned Onepoll on 26 to 28 August 2020 to carry out a nationally representative survey of adults aged 18+. A total of 2,000 people were questioned throughout Great Britain, with representative quotas for gender, age and region.

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Banking

Liquid Assets of a Bank

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Liquid Assets of a Bank 7

Liquid assets are tangible and movable assets which are easily convertible into cash in a crisis situation. Liquid assets are used by lenders to fund their loans. Examples of liquid assets include government bonds and central bank reserves.

To stay alive, financial institutions must have enough liquid funds to pay withdrawals and other immediate financial obligations by depositing holders of checks. But the amount of money they have in liquid form is not enough to cover these short-term obligations and their financial problems will become worse. Liquid assets of the financial institutions should be regularly replenished to make the banking system financially stable. In order to maintain a sufficient amount of money in the economy, the Federal Reserve System will always be in need of additional assets.

There are several ways in which the financial institutions can replenish their liquid assets. One of the ways is by borrowing funds from banks and credit unions. The other way is by issuing debt securities to provide liquidity for the monetary system.

Borrowing from banks and credit unions: Banks can borrow funds from other financial institutions in order to meet their liquidity requirements. However, the rate at which banks borrow funds from other financial institutions is usually very high. This high rate can only be beneficial for the financial institutions because the borrowed funds are used to purchase commercial mortgage-backed securities (CMBS). In return for providing CMBS, the banks can receive interest payments on the principal balance of the loans they have made to other financial institutions.

Issuing debt securities: The assets that a commercial bank or credit union secures as collateral for the loan from other financial institutions can also be used to liquidate its existing liquid assets. Usually, the assets used as collateral to secure loaned funds are Treasury securities, corporate bonds and treasury bills. However, as the value of these securities decreases, the banks’ ability to recover them through the redemption of their treasury bills and the federal income tax on the principal balance of these securities can increase the amount of funds they will have to pay out on short-term debts.

Securing debt securities: As mentioned above, the assets which commercial banks and credit unions can use to liquidate their liquid and non-liquid assets can also be used to secure loans made by them to other financial institutions. But it is important for the banks and credit unions to ensure that the funds they use to secure these loans are not used to purchase more securities. In order to obtain maximum gains from the sale of their assets, they should use a method to redeem the securities before the maturity date of the loan.

In addition to using these methods to secure other financial institutions’ loans, banks and credit unions can also sell their assets in order to raise the funds they need for making short-term payments. For example, if a commercial bank has a large inventory of commercial mortgage-backed securities, it may want to sell some of its assets in order to raise the capital required to make a single payment. If the purchase price of these assets is less than the total loan balance, the bank can sell its securities and cash in order to raise the necessary capital.

Although liquid and non-liquid assets can help the banking system to make its operations more stable, the loss of one type of asset can severely affect the financial condition of a bank or credit union. Therefore, even if there are many types of assets, it is important for the banks and credit unions to maintain a balanced level of liquidity in order to make sure that the economic system is not adversely affected by any one type of loss.

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