Elastic banking: How to drive scale and flexibility
- Posted on November 10, 2020
- Estimated reading time 3 minutes
The current pandemic has demonstrated the need for banks to be fast and agile. Banks’ net interest margins are slim, due to near zero interest rates in many regions. Potential nonperforming loans have generated massive rises in reserves, already leading to quarterly losses at Wells Fargo, one of the largest U.S. banks. McKinsey predicts a revenue drop of 16% to 44% for retail banks in Western Europe alone. Banks such as HSBC, Deutsche Bank and Lloyds Banking Group are now recommencing headcount reduction programs that were initially started before the pandemic.
Due to accelerated digital adoption by all consumers, banks are looking at cost reductions such as significantly reduce their branch networks and digitize end-to-end processes. There will be a continued focus on driving down costs and protecting profit and banks will be keen to keep in place those initiatives that allowed rapid decision-making during the crisis.
Many banks struggled to handle massive surges in customer demand due to lack of investment in cloud, AI and digital services. This was not helped by the need to quickly move staff to remote working and the adoption of significantly different ways of working. The need for flexibility and speed could not be higher.
To grow their business, banks are continually looking at deepening customer insights and providing greater personalized engagement. This is critical as many fintechs are not only offering superior customer experiences but targeting lucrative segments of value for the banks, especially around payments. Banks acknowledge that they need to improve both customer acquisition and retention, increase cross- and up-sell rates and simplify processes for both the customer and the employee.
It is difficult for banks to adopt faster solutions that guarantee time to market in 3-6 months. Often, this is not possible, even with leading software platforms. This was the rationale that drove our development of a Banking Accelerator. It provides:
- An enhanced 360-degree relationship view, including 12 available views on loans, credit cards and deposits; components are modularized to easily – and quickly - create new views.
- AI-powered lead prioritization, so you can apply lead and opportunity tracking, score and prioritize leads to focus on key opportunities and integrate with marketing models for targeted campaigns.
- A digital onboarding process, including a review of sample customer and loan application portals, that significantly reduces the time required.
- Reporting and dashboards, including predefined opportunity reporting for lending, branch and LOB managers; aggregated business data and KPIs highlight LOB performance and goal attainment.
- AI template modules to leverage customer data and extract insight to provide a personalized experience. For example, our affinity engine allows banks to identify the best adviser to support a specific customer. Our models are used to calculate loan propensities, customer behavior analysis, lead scoring and customer lifetime value.
- Advanced AI engines, such as pre-underwriting evaluation, customer performance analysis and Anti-Money Laundering that are able - with less information - to provide more accurate results than traditional approaches.
- The Accelerator is built on a predefined, industry relationship data model with more than 1,100 attributes, entities and templates and prewritten schema and solution documentation. In fact, the real value is in the way the accelerator enables our clients to bring all the elements of the customer journey together – from initial engagement and lead assignment to conversion through to post-sales and service management – and treat it as an end-to-end, integrated and personalized customer experience, all on one platform.
If you are conscious of the need for scale, speed or operational flexibility, consider using this approach to drive revenue growth and increase customer retention. We’ve developed a series of videos that show how this could work for retail, commercial and wealth segments. Refining your operational model to deliver greater customer engagement through AI is one of the top agenda items for banks right now. Let’s make it happen together.
For more insights into how banks can rethink their approach to handling demand, cost optimization and getting to growth, listen to our industry experts talking to The Banker.