With the digital revolution, many banks allow their costumer to manage their money using mobile devices, PC/smartphone tablets anytime and anywhere. From paying bills and transferring money to requesting loans and credits and mobile check deposit. A huge change in customer expectations has been captured in recent years, driven by positive experiences with marketplace and entertainment platforms. he has higher expectations for service delivery such as retail, corporate, commercial and small and medium-sized enterprise. The world economic situation makes a huge pressure to banks in multi regions in the world. Research was conducted by Mckinsey where they find that in the top of 500 institutions around the world, 54% are priced below book value. In 2014, the research team calculated that just 18% of banks captured all the value in the industry. to conclude, banks have a big challenge and tries with many types of improvement. The result of this research is reasonable since a few banks have yet to begin. According to Mckinsey’s survey, they founded that almost every bank has the advanced analytics as a priority. These banks invest a lot by establishing data lakes and center of excellence, building datacenters and using machine learning techniques. and few banks are already seeing wins. Most of these banks are facing complexity and numbers of threats such as:
- Lack of detailed potential quantification of analytics.
- Lack of early business leaders’ engagement, which they can propose a model they trust and use, that solve their problems.
- Business case: A significant investment in data infrastructure and data quality, without having a clear vision about the use and the benefits.
- Not asking the right questions in the business case.
Analytics and big data have given a new opportunity to Banks which it might take benefits form analytics by:
- Cross selling, which allow banks to produce many products package that grab customers attention.
- Carry out transactions and routine work. When the company or the organization is enormous, the volume of data to be utilized is large.
- Help the banks to arrange all profitable information linked to transactions. multiple solutions exist to make the data useful.
- Banks will use analytics to monitor their transactions against frauds. It’s a good opportunity to detect the attempts and deploy preventative actions.
- Banks can use AI to transform the customer experience by enabling frictionless, 24/7 customer service interactions
The top three channels where banks can use AI to reduce costs are the front office (conversational banking), middle office (fraud detection and risk management) and back office (underwriting). Banks and financial institutions must have the ability to provide all the necessary tools and technologies for the business units needs to have a real time access to high quality data, with ensuring a high availability and good management. These technologies could be:
- Data lakes
- Machine learning techniques
- Google-like search engines
- Modern data exploration and visualization tools
- Tools to analyses text, voice, video, and images
- Capabilities to leverage real-time data
The difference between the companies that adopted IA technologies and the traditional companies is huge, especially when costumer needs are met (costumer experience), by the new methods of realizing a complexes tasks and delivering services. For example, in the banking sector, marketing and sales tasks are being driven by analytics, which will generate a significant ROI, and will help to classify the costumers in categories and that will help many business units within the organization (banks and financial institutions.
By Mounib Mrani
Strategy & Transformation Consultant
Alton Morocco