Contributed by Simon Spring, Account Director, WhereScape
The banking industry is ripe for disruption – new start-up banks are challenging the traditional monolithic high street institutions to find more agile ways of working, to do more, smarter, with less. Al can be an attractive prospect, but deploying such an advanced technology is not a plug-and-play scenario.
The reality of the situation is that, for many banks, we’re still at an interim stage when it comes to Al. There are examples of incredibly sophisticated systems being used in fraud detection and loan authentication, but it would be a push to say this was the norm.
So why should banks be making the move to AI a strategic priority? And what steps can a bank take now to ensure success with AI systems further down the line?
Regulatory pushes and consumer pulls
The short answer is that AI is becoming a matter of necessity – from all sorts of perspectives – cost, risk, and market competitiveness forming just some.
A new generation of consumers expects services to be available 24/7, to be intuitive, instantaneous, and catered to them. For banks, this means providing services that cater to an individual’s spending patterns, device preferences, and current life situation. It’s a tall order for businesses to provide manually, but all the data on customers is there to provide those kinds of services – banks just need to find a way to access it.
Successfully accessing, and then analysing, data will lead to more streamlined services for customers and quicker time to insights for businesses means quicker service delivery to customers. Banks can also capitalise on their insights around customer spending patterns to provide tailored recommendations on financial wellbeing to clients – boosting their customer experience.
At the same time, legislation changes are adding additional complexity. As part of the shift towards these hyper-personalised services, the Second Payment Services Directive (PSD2) mandates that customers are able to request that third party providers can access their banking data to provide new services for the customer. The upshot of this is that banks will need to find a way to categorise, group and structure that data so that other services can plug in on request. Achieving this requires automation of the data structure to pull together, and analytics to determine which information is relevant for the required service.
And then there is the need for compliance with legislations like the IFRS 9 and GDPR. Both of these require the creation of “single points of truth;” the first on financial assets and liabilities, and the second on customer personal data. Both of these are exceptionally onerous tasks, if not outright impossible, to complete manually, and banks need some sort of system that can intelligently pull together all the insights into one, clearly representative, report of compliance.
Stepping stones to AI
If AI is a necessity for consumer personalisation and legal compliance, why aren’t banks everywhere simply investing and deploying it? It has emerged that, while there is great appetite for more analytics, more AI and more insight in general, all of these require banks to overcome significant legacy infrastructure hurdles. You can’t plug Al into an old system like a USB drive and expect it to churn out the results you want; instead, you need to get your data into a more searchable, agile framework before you can add AI over the top.
To do this, banks need to ensure they are predominantly focusing on stepping stone technologies – such as data warehouse automation. Data warehouse automation can provide a vital bridge between the legacy infrastructure that is holding many organisations back, and the future of cloud-based, data agility, by automating a lot of the manual, time consuming migration tasks.
This is particularly useful for traditional banks, who have substantial legacy infrastructure environments. These banks tend to have a very large number of old mainframe systems, with little or no modern analytics capabilities – something that they are, or should be, seeking to change as quickly as possible. The more diverse the IT infrastructure landscape, and the more sprawling the legacy and modern systems, the greater the need is to find a way to streamline all this and deploy more sophisticated, quicker, analytics capabilities.
Data warehouse automation can help with this – streamlining and accelerating the migration process. In addition, correctly deployed automation can reduce many of the different potential risks that come alongside modernisation: risk of error, risk of doing things slowly, risk of human oversights. And, in addition, the cost savings of automating data ingestion processes with data warehouse automation can allow banks to be more competitive, and more innovative. In the greater scheme of things, where the monolithic high street banks are feeling the push from newer challenger upstarts, it’s never been more important to find ways to become more agile with data and insight technologies.
IT infrastructure, and particularly analytics and AI capabilities, are going to evolve significantly in the next few years. At the same time legal requirements like the GDPR, PSD2 and IFRS 9 change frequently –and will continue to do so. In order to keep pace with these changes, banks will require increasingly comprehensive data ingestion, ways to manage their data landscape, and faster, cheaper time to insight/value systems. During this transition, data warehouse automation will be a critical stepping stone between current legacy environments, and a bank’s AI-driven future.
How banks can take on Google in the race for AI talent
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.
1.4 million customers to stop using bank branches due to COVID
8.4 million customers had already stopped visiting branches in person before lockdown
However, three quarters (74%) of customers will return to banking in branch after the pandemic
Of those who plan to return to branches, over two thirds (69%) will only return when they absolutely need to
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.”
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.
Liquid Assets of a Bank
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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