Our first blog examined why commercial banks should introduce cashflow management tools for small- and medium-sized enterprises (SMEs) as part of an overdue drive towards fully digital banking. Our second blog looked at the impact of COVID-19. Our third and fourth blogs examine how data-driven banking can help the people at the very heart of the commercial bank – the relationship managers.

A Data-Driven World

In our previous blogs we saw that commercial banks differ from their retail cousins in two important ways: firstly, commercial banks are far behind when it comes to digitisation; and, secondly, the relationship manager (RM) takes on a much more important role than is seen in a retail bank.

Indeed, the RM is arguably more important today than ever before – and SMEs know this: the great majority of SME customers say they would not give up their RM for a digital-only offering even if doing so would save them money.[1]

In short, RMs are in demand and will remain so. Their biggest challenge is managing their time. As a rough guide, many banks will tell you that their aim is for their RMs to spend two-thirds of their time either prospecting for new clients or selling products, and the remaining third on aspects like onboarding, training and administration. In practice, those proportions are reversed – largely because RMs have to do their job without much in the way of data-led insights.

The good news is that there are numerous tools that can analyse internal and external data to empower RMs. A data-driven approach means they spend more time adding value and less time on administration. This blog and the subsequent one will look at four crucial areas where technological solutions can help:

  • Lead-generation and on-boarding.
  • Next-best actions.
  • Credit-decisioning.

Using a data-driven approach doesn’t just boost RMs’ sales effectiveness; it also drives customer loyalty, lowers operating costs and improves employee attrition rates – a key factor given that the changing of RMs is often cited by commercial banking customers as the main reason they switch bank.

1. Lead-generation and on-boarding

Many RMs prospect for new customers by searching online, yet there are far better, data-driven solutions available. Bitvore, for example, uses AI to determine business sentiment, risk factors and growth prospects, eliminating the time-consuming alternative of browsing and sifting the noisy feeds of digital news providers.[2] Bitvore automatically sends RMs prospects within their required parameters – by industry, for example, or weighted by capital expenditure or a list of firms that have recently gone to market.

i2i Logic, a fintech, offers a similar solution with a platform database that hosts a range of financial metrics.[3] An RM can search for customers or simply enter key criteria – for example, firms that will most likely feel cash flow pressure based on interest rate changes.

“It is far more efficient to use a data-driven approach to conduct AML and KYC checks – it lowers risk and makes the onboarding process faster.”

Risk assessment, risk monitoring and identity verification are at the heart of the onboarding process, with RMs needing to assess anti-money laundering (AML) and know your customer (KYC) requirements. Traditionally, they conduct AML and KYC checks against a checklist of their bank’s rules. A data-driven approach is far more efficient, and can assess the potential client’s network of suppliers and vendors to determine the likelihood of financial crime. This helps the bank identify potentially fraudulent customers, and speeds up the onboarding process for the customer.

2. Next-best actions

Banks need solutions that can provide early-warning triggers to RMs to say which customers they should speak to – and why. That is increasingly important given the current low-liquidity environment associated with the COVID-19 pandemic.

Should a particular FX rate shift significantly, for example, data analysis can identify those clients whose revenues or costs are vulnerable, triggering a call from the RM. A forecasting tool, as discussed in our first blog, can identify whether an SME’s cashflow is likely to be negative in the coming months. It would flag that client to the RM, triggering a call about a loan product. Alternatively, should it forecast positive cashflow, it could suggest relevant cash products.

Aside from providing early warnings and cross-selling opportunities, data-driven tools can flag potential compliance problems. For example, they can determine whether a customer has engaged in sales misconduct or has failed to file due diligence documents. It would then notify the RM to reach out.

Many commercial banks understand the need for triggers, but it is an art not to flood the RMs with endless notifications each day. In such a situation, the most likely outcome is that the RM will simply view notifications as a box-ticking or, worse, ignore them.

Our next blog will look at the remaining two crucial areas where technological solutions can help RMs: credit-decisioning and training.

[1] Finding the balance – UK SME banking survey, Accenture (2019). See: https://www.accenture.com/gb-en/insights/banking/finding-balance-uk-sme-banking-survey

[2] For more, see: https://bitvore.com/

[3] For more, see: http://i2ilogic.com/services/

Nicholas Conlon

Nicholas Conlon

Director – Commercial Banking Lead, Growth Markets

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Bhavna Rawlley

Bhavna Rawlley

Senior Manager - Banking, Applied Intelligence

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