Monthly Archives: July 2020

Feature Corner- Transforming the Digital Banking Landscape

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Digital technologies have been helping banks and financial institutions to seize new markets, grow the business, and cut costs by providing a competitive advantage.  We see tremendous changes in the banking and financial services industry impact businesses and in an attempt to seek insights from business leaders from the industry, our Co-Founder and SVP Mr. Sridharan J. S has a conversation with Mr. Palani Balasubramanyam Nama, Head of Open Innovation and Digital Transformation, Societe Generale, who has over 21 years of experience working with Innovation & IT divisions of Investment Banks, Financial Institutions and European/American Multinationals, about the state of AI and other technologies in banking, in our exclusive ‘Feature Corner’.  As the Head of Trade Execution, Palani is also accountable for the IT & OPS team ensuring on-time and secure trade execution across global exchanges, efficiently from India.

Sridharan – Being in the banking industry for more than a decade, tell us how banks fostered innovation before COVID and how the perspective has changed during this situation? 

Palani – Pre COVID-19, innovation in banking was more focused on internal optimization, focused increasing digital footprint for efficiency, or improving customer journeys.

COVID has compelled to accelerate the adoption of contactless service delivery for customers, at a rapid pace. This constraint forced banks to partner with external eco-system for rapid transformation, to provide neo banks equivalent digital experience for customers. Apart from service channels, there is quite a bit of investment being done on employee experience, like enabling them to work from home, across multiple secure digital channels and collaboration tools.

Sridharan – Approximately what percentage of spend, do you know of, that banks spend on IT costs annually? 

Palani – Large banks spend between 5 to 10%, small & medium banks spend between 20 to 30% of their total spend on IT costs.

Sridharan – Approximately What percentage of banks’ transactions or what areas are automated?

Palani – Above 70% of P2P transactions are automated, however, B2B transactions hover between 30 to 40%. B2B transaction STP % is catching up in the recent past with the evolution of Machine Learning & Smart Automation.

Sridharan – As more devices connect to the internet and the concept of the Internet of Things gaining rapid momentum, what are the preparations banks are involved in the rapid increase in equipping themselves with the huge amount of data generated from the devices?

Palani – BFSI has been slow in the adoption of IoT before COVID, given security threats and central bank regulations. However, post-pandemic, banks are more open to adopting digital channels to deliver contactless & remote client experience.

This unprecedented disruption has increased data volumes multifold. Most of the banks have established internal data analytics teams to address basic data processing needs. Despite interest in partnering with external partners, there are roadblocks to be addressed before it can become reality, especially around secure data sharing, multiparty computation & adherence to regulatory norms (GDPR).

Sridharan – Data, being the most important factor for the digital transformation for banks, what technologies are used to leverage data to meaningful insights for smarter decisions?

Palani – Large BFSI enterprises have multiple tech stacks based on needs. However, they have well defined IS strategies guiding the usage of tech stacks based on problem patterns being addressed.

While exploring partnerships with tech giants like ORACLE, Teradata, or IBM, there is an intrinsic push to adopt opensource tech stacks, to ensure open standards and cost optimization.

Sridharan – Do you think banks are struggling with the rapidly changing technological landscape in terms of which technologies to adopt and which ones not to? 

Palani – It is a challenge to keep up with fast-paced Technology landscape evolution for any organization. It is more complex in BFSI given constraints around tech choices to be made keeping in mind the security and reliability of services. In BFSI, business capabilities and security take precedence over technology grandeur. 

There are few instances of large banks partnering with external partners to disruptive technology transformation, however, results so far haven’t been very encouraging. BFSI transformations demand as business acumen and technology expertise. External partners tend to be good at technology expertise, however most of the time they lack business acumen.

Sridharan – AI has been long seen as the next big thing in the banking and financial industry be it in the area of planning, cost-saving, customer experience, fraud prevention, or anti-money laundering.  What do you see as the future of banking given the exponential growth in IoT devices, cloud computing with Artificial intelligence capabilities?

Palani – AI, so far has been capable of helping in raising proactive alerts, simplifying decision making, and processing of large datasets. however, it is far from autonomous process execution or decision making, which limits the full-scale unsupervised deployment of AI-driven process flows, which in turn would help increase the straight-through processing rate.

Necessity is the mother of invention. Pandemic has increased BFSI’s appetite to adopt technologies like IoT, Cloud computing, and AI. The exponential growth of these technologies should be complemented by the rapid hardening of enterprise cybersecurity strategies, without which, banks may be hesitant to leverage the full potential of emerging technologies.

7 questions Contact Centre Data Analysis can answer

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 Industry Watch Corner

The lack of access to physical stores due to the pandemic has increased the traffic for contact centres worldwide. Contact centres are bridging the gap to communicate with customers, emergency helplines, on-call services, and inquiries. Even before contact centre agents were required to work from remote locations, Cisco’s 2020 survey revealed that 62% of decision-makers plan to implement a cloud contact centre in the coming year. 93% agree that technology is very important in creating a better customer experience. Contact centres are a treasure of data waiting to be discovered. They have data acquired through daily processes like telesales, telemarketing, customer surveys, collections by means of outbound services and customer services, emergency response past inbound services. Analyzing contact centre data can help not only the customers but the contact centre decision-makers as well, to improve service and increase efficiency. Artificial Intelligence-based software improves the customer experience by monitoring key phrases and then prompting the agent in giving proactive responses. They can identify challenging calls for agents to handle and route the calls depending on complexity. AI is also gaining popularity through chatbots and solving issues without the need for agent interference. Chatbots need to understand the tone of the customer and respond accordingly. A healthy Contact Centre must conserve excellent hardware and software solutions providing a direct impact on quality assurance/success metrics, call statistics, customer implementation, and proficient Contact Centre agents. Contact centres today can answer more than just calls. Let us look at what other questions can be unraveled through analyzing contact centre data.

1. Is the Customer Satisfied?

According to a 2019 survey by Deloitte Digital, Customer experience or CX is a high priority (57%) among the surveyed centers. Harvard Business Review found in a study that a focus on increasing (Customer Satisfaction) CSAT will help businesses retain 74% of customers for another year leading to a substantial increase in revenue. We can increase customer lifetime value by looking after the key determinants like customer acquisition, customer retention, and customer margin. IVR (Interactive Voice Recording) Systems have been in use recently to reduce the number of calls reaching an actual agent. Valuable insights on the reason for the call, the caller, Opt-out Rate, self-Services rates, and incorrect routes can be evaluated through IVR data.

Representative customer satisfaction metrics from FLASH, the analytical dashboard

Representative customer satisfaction metrics from FLASH, the analytical dashboard

2. Is your Product facing a regular or common problem?

Collating and categorizing issues is a great way to understand the product. A repeated complaint of the product needs to be fixed for future versions so that customers do not engage in expressing distress and reducing brand value. Categorizing these issues also helps in creating a common answer pool for contact centre employees. AI can be used to direct the calls to Subject Matter Experts to handle issues. This will reduce escalations and help employees with better ways to tackle problems. We can also perform sentiment mining to analyze the sentiment of the customers on service level parameters such as resolution effectiveness, feature variety, etc. by leveraging social media sentiments of the public on various products or services of clients for improved business services.

3. Is your Contact Centre Efficient?

First call resolution (FCR) is an important metric that measures the efficiency of the contact centre to solve issues in the first call. A long waiting time is another factor for low customer satisfaction. Measuring the average delay of calls or the call abandon rate or the response time will give us an idea about the need for more staffing to handle the surge in calls. Response time metrics and call resolution metrics are indicators of efficiency(image below depicts metrics from an AI-driven dashboard, FLASH). Customer Effort Analysis can be performed to measure the efforts spent by customers to get various services rendered through various touchpoints. Customer journey analysis can be used to identify the pain points that customers face while traversing channels for a specific purpose. Path analysis can help identify the patterns in the menu/caller path in a time slot. All metric dimensions can then be evaluated to arrive at actionable insights about the customer segment in qualifying dominant paths, dependent paths, and average time spent on the path, etc.

Flash insights

Flash analytics

Flash dashboard

 

4. Is your Employee productive?

Average Sales per Agent is the measure of sales that an agent closes within a time period. We can use this metric to award agents performing well and provide targets for employees to work towards. An agent’s Utilization and Average Handle Time are two primary contact centre metrics to focus on when trying to measure an agent’s productivity. We must also be careful of the escalations that an agent faces and train employees who need to improve performance.

Flash AI board

5. How many Customers at risk of attrition?

According to contactcenterpipeline.com, Attrition is considered the No. 1 challenge 27% (up from 19.2%) for contact centres in 2020. Measuring the Net Promoter Score or NPS of customers helps us to plan a better approach for managing customers who are at risk of attrition. Predicting churn rate qualifies the steady-state level of customers at any point in the network.

6. Are there any opportunities for Upsell and cross-sell?

Affinity analysis/association rules of mining are used to analyze the co-occurrence of relationships among activities performed by customers and discover the cross-sell/up-sell opportunities accordingly. Recommendation Systems help identify products customers need and help contact centres create personalized offers based on purchase history and products commonly bought together. Use of Uplift Modelling can be used to identify the right set of customers(the persuadable) to be targeted for marketing campaigns.

7. Can your competitor be a reason for low sales?

As contact centres are a hub of engagement, customers often give honest feedback on products. You also find that many potential clients are already using your competitor products. Employee engagement plays an important role in analyzing these potential risks to the business. Predicting the customer churn rate helps to identify the customers who are likely to leave the network.

Contact Centres are now moving into a space of self-service where customers are adapting to emerging artificial intelligence software and chatbots. Customers today do not like waiting for calls to be answered, they would rather finish queries through chatbots that do not consume time. IVR systems are slowly being replaced by intelligent assistants that provide human-like interactions. Having an advanced chatbot and analyzing its response can help you understand your customers. With these forms of service, direct calling and email, data is being collected from multiple sources. Decision-makers need regular reports to keep track of their performance. While automating this data is now a necessity, the use of AI to analyze this data is a competitive advantage. AI-based dashboards give you the insights needed to understand your data. They highlight possible improvements and forecast staffing depending on query traffic. They group dissatisfaction and anger sentiments and analyze agents who deal better with these emotions. Customer sentiments change with time, people are more impatient and now more sensitive due to long hours indoors. Many factors can be associated with good or bad performance and identifying these factors can be tricky for decision-makers. AI learning, analyses your data in real-time and helps you get a holistic view of your business. Analyzing and processing this data turns your contact center into an answering hub. Companies that ignore customer service face an inevitable fate of resentment and destroyed brand image. FLASH, a product by geniSIGHTS ensures your contact centre does more than just calls. FLASH is a one of a kind voice-powered AI tool that gives your contact centre the power to stay ahead of the competition and give highly efficient results. Our solution uses advanced analytical techniques through various statistical models and machine learning algorithms to qualify underlying patterns and mine hidden insights from data. It is lightweight and cloud-based, facilitating analysis at your fingertips even as you sit at home during this lockdown. Contact us at https://flash.genisights.com/ for a demo today.

Effective Decision Making

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  FLASH CORNER

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The BI Survey research found that 58% of the surveyed companies relied more than half of their decisions on gut feel or experience over data. But two-thirds believe that information will be valued for decision making in the future. Highly data-driven organizations are 3X more likely to report significant improvement in decision-making, according to a survey by PWC.

The HiPPO effect, coined by Avinash Kaushik and reiterated by Bernard Marr in Forbes, is usually the most experienced, most powerful, or highest paid in the room. Once they voice their opinion, others find it disrespectful to voice their own. This may not lead to desired results. Let’s think if the decision would go on a similar path if the time and resources would be different. Given more time, you would probably rely on the opinion of a board of directors or your experienced colleagues. Will you still be completely confident?

   Data however changes this. You have an unbiased opinion based on facts that leads to better results. Data analytics uses information from all sources and simplifies it to visual representations that highlight what you need. You are now capable of viewing all your information in just one screen. But data is useless until interpreted. Data-driven decision making or DDMM lies in interpreting this data for actionable insights. A term fondly called as data storytelling is considered an art. Artificial intelligence-based complex algorithms make sure to see more than what the human eye and mind are capable of. These insights help drive your decisions in directions that lead to success. So you have got your data, got your insights from this data, why then have you not used it to make the decision given to you 10 minutes ago?

The problem with many AI solutions is the inability to get exactly what you want when you want. You have a ton of data and a ton of insights but how does your BI tool know what you need to reach the answer for the question given to you 10 minutes ago. You have knocked on the door of data analytics and are seeking the solution. But can’t you just ask?

FLASH, by geniSIGHTS, gives you the power to simply talk to your BI tool and seek the information you need to come to the decisions that will open the right doors. In turn, FLASH also talks back to you with insights. FLASH is a one of a kind voice-powered dashboard that provides quick insights into your organization’s metrics. It goes beyond the functionality of Business Intelligence and uses conversational AI in the dashboard to respond to queries and generates real-time insights for actionable decision-making.

FLASH is AI-driven, lightweight, and easy to use.  It can easily be integrated with your existing data systems without having any extra software. It is also accessible from any location and insights can be exported and shared with the members of your organization. The visualization can be customizable and easily understood without any expert knowledge of data. FLASH ensures that your entire team is on the same page, making your user experience smooth and without any delay. Unlike other solutions, FLASH learns continuously to understand what you need for your business and becomes your virtual data assistant over a period of time.

FLASH is your AI agent who has all the answers you need to make decisions in a FLASH. We have seen how Amazon’s Alexa has made life easier. Shouldn’t your dashboard be able to do that? Now you can make your decisions within 10 minutes and be sure of it.

FLASH gets you what you need, you simply need to ask it. Check out FLASH at https://flash.genisights.com/

12 KPIs to measure if you are in the Manufacturing and Automobile industry

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 Industry Watch Corner

You can’t improve what you don’t measure. KPI or Key Performance Indicators are the metrics used to measure how your company is performing. If you are part of the business world, you are probably familiar with the term. It is important for every business to choose the right metrics that can measure the success of your company and work towards improving your performance. It is important to understand that KPIs vary with organization, department, and even team. There are many types of KPIs. They can be quantitative, measured as a number or qualitative, based on standards set by expert opinion. They can be leading, predictive of future success and failure or they can be lagging, reflective of success and failure of past events. But the best way to categorize KPIs is by industry.

Just like any other industry, KPIs are important to measure the health and progress of the Manufacturing and Automobile industries. Besides knowing what your KPIs are, you will need to work on ways to improve these KPIs. KPI real-time dashboards monitor your KPIs and give you insights to improve them. They help in maintaining your supply chain and manage your logistics by retrieving data of your systems in real-time. By using Artificial Intelligence they run complex algorithms of predictive analysis to forecast demand of your vehicles. They analyze your customer data and give you insights at the right time to increase and decrease production depending on the demand of the customers. They help in customer segmentation and analysis of regions to convey high performing regions. These regions will need higher demand than other low performing regions.

Let us look at key performance indicators examples for the Manufacturing and Automobile industry

  1. Overall Equipment Efficiency: It is the product of availability, performance, and quality of equipment. It measures the overall effectiveness of equipment and can even be calculated for the factory. It highlights poor performance and quantifies improvements.

  2. Production Volume: No. of units manufactured in a time period. This helps us determine if the supply meets the demand of vehicles

  3. Production Downtime: Analysing your planned downtime and optimizing it for better productivity.

  4. Utilization Rate: Measuring the capacity of production against the actual production. The utilization rate will vary according to demand during the year but low utilization for long periods may indicate losses.

  5. Cycle Time: The average time required for making a single unit of a vehicle. Recording data of the production line will help us determine if optimal time is maintained in each process and point processes that take longer. We can then optimize production time.

  6. Yield: Measure of the number of vehicles that are made without any defects in one attempt. We can measure the yield for individual processes to highlight faults in the production line.

  7. Recall Rates: It is the percentage of vehicles or parts that were sent back due to defects amongst total vehicles produced.

  8. Inventory Turnover Ratio: This is a measure of the number of vehicles sold and replaced in a time period. It is a ratio of vehicles sold and vehicles in the inventory.

  9. On-time Delivery Rate: The percentage of time that a manufacturer delivers a product on time to the customers.

  10. Back order rate: The number of orders that cannot be fulfilled when the customer places an order.

  11.  Mean time between failures (MTBF): It is the average time between failures of a system. It can be calculated by dividing the total operation hours by the number of failures during this time.

  12. Mean time to repair (MTTR): It is the average time to repair failure and return to production. A good MTTR will tell you your readiness in emergency situations and how your response is to failure.

FLASH, a product by geniSIGHTS is a real-time dashboard that can help the automobile and manufacturing industries by assisting in supply chain management. Its voice-controlled AI model solves your queries on the go. You can monitor the data across regions in a single view. The simplified visual representation will help you identify red flags quickly so you can act on them and improve your manufacturing process. Using a KPI dashboard will not only assist you to monitor your KPIs but will give you the power to optimize them.

Read about flash at https://flash.genisights.com/