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Banking, Regulation and Big Data…Too Big to Change?



matt shaw

By  Matt Shaw, Associate Partner – Crossbridge, the financial markets consultancy

A bitter pill to swallow matt shaw
In 2012 many investment banks find themselves in a situation where profits have been flat or in decline for the last 2 to 3 years and now they must incur mandatory costs for the next 2 to 3 years in order to implement a raft of regulations, compliance with which will reduce their profitability yet further.  Putting issues of timing, extra-territoriality, regulator’ capacity, economic and political diversions (such as the US Presidential Elections and the Euro-crisis) to one side, it is clear that the financial services industry is entering a period of sustained reform.

Jamie Dimon, chief executive of JPMorgan Chase, estimates that Dodd-Frank alone will add an additional $400m-$600m to the firm’s annual cost base.  By some estimates, the return on equity of the banking sector as a whole will fall from about 20 percent to around 12 percent, which does not provide investors with a great deal of compensation for the volatility of the capital-markets.  Already depleted change budgets, for at least the next few years, will mainly be spent on US, European Union and global regulatory reforms.  These variously seek to address some of the systemic stability issues which have come to light during the recent financial crises and combined, they affect almost every area of the financial services industry – the wholesale, retail and insurance markets, from individual and corporate customers, to buy and sell side participants, to trading venues and infrastructure providers.

Under observation
Regulators are starting to put much more emphasis on the quality, richness, volume and transparency of the data they receive from financial institutions and are using this as a proxy to enforce additional and more robust controls, and increased substantiation, that regulated firms are adhering to policy, providing full disclosure and complying with the law.

By mandating the use of the unique Legal Entity Identifier (LEI) on all trades, regulators are effectively forcing firms to clean-up their counterparty data structures and values and the internal linkages with the various front office businesses which enable counterparties to trade.   Over the next few years it seems regulators are moving towards a global single view of counterparties, but exactly how market participants will obtain and register their LEI is not yet finalised.  It is another matter as to which sovereigns, governments, corporates and individuals will accept this scrutiny into their banking transactions and intrusion into their privacy.  There are competing identity schemes being put forward by different regulators (unfortunately), although LEI seems to be approaching a ‘tipping point’ and if it is adopted by one of the major European or Global regulations, it will surely become the industry standard.  LEI could become the ‘passport to trade’ for market participants who fall under the regulations (which is most).

There are similar initiatives to create global identifiers for standardised derivative products and their underlying contracts and this too may become more feasible as regulators force more and more OTC products onto exchanges and through central counterparty clearing.  As with LEI, we could see the formation of centralised securities and contract registries.  What will this do for financial innovation and the creation of new products?  Of course, it remains to be seen how and where the market for specialised bi-lateral contracts and structures (to meet a specific risk profile and market view) will persist in the new environment…but the demand will be met.

In theory at least, improved identification should lead to improved classification and linkage of transactions, counterparties and products and this is what drives many risk and accounting provisions, controls, limits and reports.  Given enough computing and manpower, local and global regulators (and by implication the firms they regulate) should be able to build a more detailed picture of the network of transactions and risk concentrations across different products counterparties, industries and countries, but do regulators really expect to turn top-down surveillance into bottom-up sousveillance?

Where does it hurt?
Underpinning much of this change is data – the information which is used to identify, classify and enrich a firm’s transactions and to consolidate, control and report on its books and records.    At the data level the different regulations (Dodd-Frank, EMIR/MiFID2, FATCA, Basel 2.5/3, Recovery and Resolution Planning, CASS, and IFRS to name a few) often come crashing together.   If we focus instead on the different data domains, we can see common patterns start to emerge.

  • Near real-time (15 minute) derivatives trade reporting, utilising new ‘global’ identifiers. Huge volumes of cross-industry ‘trade repositories’.
Party/Legal Entity
  • More robust identification and more extensive classification schemes will need to be applied.
  • More detailed relationships (e.g. agent, principal) may need to be stored for more granular (fund-level) credit risk calculation and disclosure.
Internal Legal Entity Structure
  • Holding company, subsidiary, special purpose vehicle, and branch ownership structures require clarification for insolvency planning and (potential) segregation of wholesale and retail businesses.
  • More extensive identification and categorisation is needed to support treasury and finance accounting changes; more sophisticated risk analysis.
  • Customer and Ledger accounts will need additional controls putting in place to limit trading and investment activity, segregate collateral and assets, apply new taxes and withholding regimes, and report more off balance sheet assets.
  • Transactions and balances may need migrating (novating) and collateral netting improvements made as OTC trades shift to central counterparties.
Book/Organisation Structure
  • Firms need to understand the impact on lines of business for insolvency and segregation planning.
  • New regulatory capital, funding and liquidity charges may also result in transaction migrations from Trading to Banking books in order to seek more cost efficient booking models.
  • The location of any, or all, of the above data elements may need to be known in order to comply with extra-territoriality clauses and for insolvency planning.

Figure 1 shows some of the data improvements and changes firms might be expected to make.

Whether they have a leading edge service-oriented messaging infrastructure or a dual-key and reconciliation-based information architecture, Crossbridge believes that firms need to review their data lifecycle quality, ownership, standards and flexible storage solutions, and map these onto their book of work, in order to identify where cost-savings can be achieved.  We recommend a consistent approach to the delivery of data solutions, from developing business rules to data and structural enhancements, to BAU process and capture updates, through to data remediation and migration.  Figure 2 shows some of the trade-offs to be considered.

Remediation/Migration Population reduction versus complexity of BAU process updates.
Client Focus Impact on new and existing client lifecycle service from the group, division, line of business and platform perspectives (with regional variations).
Risk Appetite Non-compliance risk assessment (data quality and false positives/negatives).
Cost/Benefit Cost-benefit analysis of data quality (fitness for purpose, not perfection).
Enterprise Solution Buy (vendor), build (in-house/open-source) or partner (externalise).

Delivering coherent and cost effective solutions is made difficult given that data organisations need to support project focused ‘point deliveries’ with fixed compliance deadlines.  The situation is further complicated by inflexible or monolithic data capture, storage and distribution platforms and unclear ownership amongst the many suppliers and consumers of the data.

A miraculous recovery
Some technology start-ups (Google and Facebook included) start with a data model and subsequently develop their business models on top.  Since their business models are under threat, maybe it is time for banks to develop data models to retro-fit to their already well established (but often multi-faceted, multi-vendor) business and operating models?  It is often said that there is no competitive advantage to data.  Maybe, maybe not, but a firm-wide focus on data quality can reduce operating and transaction costs, improve risk aggregation and management, and optimise balance-sheet and inventory utilisation.  More and more firms are starting to view data as an asset and understand the importance of data quality as an enabler not just for regulatory compliance, control and reporting processes, but also for integration, differentiation, reputation and profitability enhancing initiatives.

Complex financial product accounting, risk analytics and valuation models are becoming increasingly commoditised – companies like and OpenGamma already offer highly modular, scalable, fault-tolerant, cloud-based (or ready) accounting and risk management platforms.  Could it be too long before we see the emergence of Microsoft Azure Ledger, Google Financial Risk Analytics, or Amazon Transaction Banking?  If banks overcome their ‘not built here’ syndrome they could begin to work with trusted and proven platform service partners who promise to cut operating costs and ‘not be evil’.   As more OTC products become standardised on exchanges, algorithmic trading and STP will be used to drive down the ‘cost per trade’.  Could a ‘big data strategy’ steal the march on regulators and competitors and allow a firm to refocus on value creation activities, such as trading and hedging strategies, structuring and contract origination, advisory, sales and marketing?

As we have seen above, regulators are beginning to force the issue with more prescriptive identity and classification schemes, which will result in the externalisation of firms’ trade, counterparty and product information in centralised regulatory repositories.  Vendors such as Avox (a commercial subsidiary of the DTCC) are already starting to realise the value in this model as they match, merge, validate and re-distribute counterparty data to and from a number of large banks – they offer a ‘Counterparty in the Cloud’ service (although the matching algorithm is a little more ‘fuzzy’ than for iTunes).  It is not a great leap to envisage them (or a competing vendor or consortium) leverage the standardisation afforded by the LEI and extend their business and data validation teams to provide a shared KYC and client on-boarding service.   Although anti-competition and risk concentration concerns would need to be addressed, the benefits to clients are clear; they will only have to go through the standard regulatory KYC ‘passport application’ process once and then negotiate legal and commercial ‘visas’ with each of the firms with which they wish to trade.  Maybe some aspects of the global markets’ client on-boarding process will be outsourced yet further and delegated back to the governments, regulators and credit ratings agencies that mandate these ‘approved’ classifications, ratings and identities for counterparties and products.  If you are going to demand ID, you have to issue the passports.


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



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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1.4 million customers to stop using bank branches due to COVID



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,

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:

Commenting on the findings, Jon Ostler, CEO at 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

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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Liquid Assets of a Bank



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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