Why do banks struggle with CX?
- Posted on March 15, 2021
- Estimated reading time 3 minutes
The top three banking challenges our clients have told us about for 2021 can be summarised as customer experience (CX), people productivity and operational agility. We’ve already blogged about operational agility. This blog looks at improving CX and, specifically, how can we leverage AI to generate deeper customer insights and greater personalized engagement?
Every bank wants to differentiate itself through superior CX. And every bank is looking at AI, including all its related disciplines (machine learning (ML), robotic process automation (RPA), cognitive services, data analytics, etc.) to understand better how it can improve the end-to-end experience. AI can improve customer engagement in many areas: 360-degree customer view, pre-empting customer churn, predicting NBA, faster onboarding and greater cross/up-selling.
So why is it so hard?
- Often CX has no specific board owner as it cuts across a number of functional roles: sales, marketing, customer service, IT, HR (to name a few). This slows down decision-making and can end up in internal politics over resources and funding.
- Typically, there is no central customer data repository. Data is spread across the bank in different formats and located in aging systems. It often needs to be consolidated, cleaned and de-duped. If there is one system, then it’s usually in need of an upgrade and is pretty slow. AI only works if you have good data.
- Related to this, there may be multiple marketing systems in the bank for different product areas. Product divisions work in silos and there is little sharing of information. In fact, in some banks there is intense internal competition between departments.
- Acquiring and retaining AI talent (such as data scientists) is becoming very difficult due to their scarcity. Banks keep AI projects in-house to retain their teams with stimulating assignments. But banks do not invest in reskilling their people around AI. An Accenture survey found that only 3% of bank executive boards plan to significantly increase investment in reskilling programs in the next three years.
- AI still generates inherent bias in its outcomes. Apple Pay offered different credit limits to husbands and wives in the same household based on algorithmic methods. ‘Black box’ processing means you get an answer, but no audit trail to demonstrate transparency. As a result, digital ethics is becoming increasingly important.
However, for those banks that implement AI successfully, there are significant benefits for customer engagement. For example, personalised – or contextual - communications double cross- and up-selling rates, increase deposit levels by 5%-15%, improve CSAT by up to 35% and reduce customer churn by 10%-30%.
This applies to businesses as well as consumers. PNC Bank is working with UK fintech, OakNorth, to develop a ‘Covid Vulnerability Rating’ framework for its business loan portfolios. Lenders undertake portfolio diagnostics to rate loans based on their vulnerability based on liquidity, debt capacity, funding gap and profitability – a highly personalised proposition.
At Avanade, we’ve found that leveraging AI can be a major driver for CX transformation. Here are three examples:
- We built a robo-advisor platform for a US investment bank which included client onboarding, investment strategies, portfolio rebalancing and performance monitoring. This led to increased performance, security and scalability. The platform currently services half a million accounts.
- We developed an algorithm-based cash flow forecasting system to help a large German bank target their SME community. The development process and time to market was speeded up using Agile.
- A manual approach to regulation had simply increased backlog for an international bank. Our RPA/ML solution helped prioritize alerts and speed up the process. Headcount dropped by 33%, there were significant reductions in case volumes and false positives and the bank generated cost savings of $100 million+ annually.
Our new Banking Accelerator has been developed specifically to accelerate customer engagement through AI. It increases customer acquisition and retention, improves campaign effectiveness and simplifies customer processes.
Managing end-to-end CX is tricky. Customers have high expectations and are rarely forgiving when things go wrong. It’s vital banks get this right. Read our guide on top banking challenges to find out more.