Archive for the ‘data’ Category

Banking and connected homes . .

May 31, 2016

Connected Homes

Post 3 of 4 of the series – The Bank of Things

Perhaps one of the most exciting areas of technology will be the connected home. Unlike connected cities the customer will be in control and be able to introduce smart devices of their choice.  

Nearly every room could have a wide array of connected devices. Clearly TV and sound might dominate the front room, but expect home to feature dedicated “vision” rooms where 3D projectors beam images to every wall and floor to fully immerse the viewer or gamer. 

For the bedroom, you can already buy a mattress that monitors and reports your sleep pattern and able to regulate temperature to optimise your sleep experience. Aside from mood lighting, light bulbs have become “multi-function” devices by doubling as speakers or WiFi extenders.  

In the bathroom expect to catch up on the news and other personal notifications in the bathroom mirror, whilst your connected toothbrush records your brushing habits and send alerts if it detects possible issues. Even the toilet will analyse content to assess your health. 

In the kitchen your fridge will manage your shopping possibly working with your bin so that items from cupboards can also be recorded. Cooking maybe a thing of the past as robotic arms take over that task unless of course you’d rather just have a 3D printed burger. Already you can buy kettles that are connected so you can use an app to ensure water is boiled before you get to the kitchen.

 Laundry rooms may get smarter with clothes identifying their washing instructions so you never have to choose a setting or risk choosing the wrong setting. It will even tell you if you mixed the wrong items. There are already socks that are connected and can tell you how often they have been worn and washed, hopefully they are the same number. However will we need to wash clothes? Will we instead simply recycle clothes and have new sets 3D printed? 3D printed clothes can be much smarter with LED lightening and smart materials that detect heat and adjust ventilation automatically.  

Most of the above has been demonstrated already and there is much more to come. But what does this mean from a banking perspective? Just like the Connected Car, the Connected Home too might have it’s own account that allows a detailed spend analysis for the home. Devices could be connected to the account for shopping or ordering recipes for the robot chef. 

Utilities could also be connected for payments but also for budgeting. So possibly a budget could be set for heating and a smart algorithm is used to manage the bills to that budget. The algorithm reduces / increases temperature not only to the weather outside but also to keep within a budget. In the UK utility companies hold £1.5bn in excess funds relating to overpaid prepayments, this could be eliminated with smart meters connected to accounts. 

Managing the home is a complex task and banks could play a role as an infomediary by managing switching between suppliers to get the best deal and provide a “single statement” for all bills. Whilst personal finance management provides spend analysis information, banks have the opportunity to provide a role that helps customers manage their expenses better. 

ASB in New Zealand is the only bank I’m aware to produce their own IOT device for the home, a smart digital savings box, Clever Kash. The device has an interactive screen and a companion app. The idea is as the child earns money their parents can flick cons from their phone to the savings box and the child can see the balance being updated. The bank provides this to help parents teach the child about money and saving. There is huge opportunity in the connected home for banks in the future but for now banks should prototype home banking experiences for this exciting future.

 

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Banking on Connected Cars

May 18, 2016

Post 2 of 4 of the ‘Bank of Things’

The future is already here with self-driving cars and the race is on globally to full legislate for them to be acceptable. Dubai has set a target of 25% of vehicles to be driverless by 2030. This alone will have huge impact not only to laws, but insurance and jobs. It is easy to see that such automation will be a big factor in predictions that within 25years we could see unemployment reaching 50% in the USA! On a positive front, today 96% of car accidents are caused by human error. However even eliminating a large number of accidents has an impact on jobs in hospitals and for insurance companies.

The connected car is a great example of IOT, compute power + huge array of connected sensors + extensive data collection. Car designers have already moved their focus to car interiors as much as if not more on the exterior as they imagine spaces we can relax or work in. There are already car panels with built in sensors so that a knock or dent is detected and can be reported automatically. Cars may automatically report potholes. Smarter interaction will allow car’s to book themselves in for a service while you work. And manufacturers are already designing boots that can be used to accept parcels while your out – the courier notifies you of their arrival and you open the boot for the delivery or collection remotely via an app.

As cars will become much more interactive what role can Banks provide? Clearly they can allow the car to make payments to pay for tolls and charging (fuel) themselves. Banks could also look to provide accounts dedicated to the car so that a full picture, including servicing and insurance, can be ascertained on the cost of owning a car (personal finance management for car’s).

Some of us may choose never to own a car, and simply use Uber to order a self-driving car on demand. This will create the possibility of “car landlords” – people buying cars to earn money by driving others. Clearly this represents an opportunity for banks in terms of mortgage style loans for “fleets” of cars as an investment.

Last year Santander teamed up with CarZapp to provide car dealership’s the option of providing a car sharing scheme to their customers. Customers of the scheme can pick up and drop off cars as they please from participating dealerships using the App. It’s a very different customer experience than just providing a loan for the car. It enables customers the option of driving different cars rather than just owning one. The scheme was launched in Germany where Santander is already one of the largest car financers in the market. It’s this market share that allowed them to innovate the concept of car sharing using an App.

In Poland you don’t need to got o a branch if you’re a business banking customer, Idea bank has a bank that comes to you! Idea bank is expanding it’s fleet of car’s that have been customised with a built in secure deposit box and ATM. It is possible to order the car to come to you and currently it is driven to the customers location. However it’s easy to see that this is a great candidate for a bank on demand ordered via Uber.

Elsewhere in Canada, Blueshore, looked at connected cars in a very different way. They thought about the passengers and how they may utilise their time. Focusing on wealth management they looked at the possibility of new user interfaces designed specifically for windscreens so that a passenger can review their portfolio whilst being taken to their destination. This allows car journeys to be much more productive.

Initially it may be difficult to think of the role of connected cars in banking beyond payments, but as you can see Banks are not short of imagination already. What is for sure is that there is much more to come and now is the time for banking to think about customer experiences and the connected car.

POST 4: Digital banking is all about Interactions not transactions

April 22, 2016

 Post 4 of the series Transformational Banking – Digital banking is all about Interactions not transactions

After my previous posts API’s and Big Data I was asked by a few people, “these are great ideas, but how does a bank make money from doing this”. This to me was an eye-opener as I assumed it was clear that this drives customer engagement, what I hadn’t appreciated is that not everyone see’s the link between engagement and creating revenue.

We know customers are moving online, banks can expect 90% of customers to interact with them through digital channels. As this happens, how do Banks sell, advise, reward and drive advocacy? The answer is simple they have to:

  • Provide good content and useful services to drive more interactions and to gather data about the customer interests, habits, life stage etc.
  • Drive even more interactions by being able to identify the customer wherever they are online be it on your or another website, mobile/internet banking or social media. Be where the customer is online, I call this Omni-Presence
  • Provide more ways to interact online email, IM, Video, social media…
  • Use each interaction to communicate with the customer, but respect privacy, channel communication preferences and acceptable frequency.
  • Provide communication in timely (real-time), relevant and appropriate way
  • Use analytics and machine learning to improve the decisions you make on what to communicate, when and how

Each opportunity (interaction) is a chance to sell, advise, reward, retain or engage the customer.

So how does this link with API’s and Big Data?

Banks can profit from API’s directly by either selling / licencing access to partners or just making money from the underlying transactions driven by the API’s. However API’s used to create more innovative services (either by the bank or partners) can drive much more interaction. Every interaction is not only a chance to communicate with the customer but is also a valuable source of data. As the result of any communication can be captured and if successful can replicated to other customers, if not then refined and another approach tried. The continuous improvement of communication creates a self-learning, self-tuning engagement model that is more effective than traditional marketing.

By incorporating 3rd party API’s Banks can also open up new revenue streams from 3rd parties, for example by taking a margin on ticket sales for travel or music festivals in the case of students.

In a similar way creative use of Big Data can also drive greater interaction and create new revenue streams. In terms of the latter some banks are already capitalising on PFM (Personal Finance Management) data to provide 3rd party offers and rewards to their customer base. The customer gets something for nothing or a discount, the bank gains a commission from the merchant and the merchant gains a customer. This is a win-win-win scenario driven by the banks being able to provide more targeted offers (based on customers spending patterns) than the merchant would be able to themselves. There are many more opportunities to profit from data that Banks hold but this is a stark change to their current business models, but one that challenger banks are already looking to exploit.

There’s money to be made from API’s, Big Data and driving customer interaction but it will require a mind-set focused on transformational banking rather than incremental change of existing banking services.

Post 2 on Transformational Banking: Big Data Not Banking Data

April 8, 2016

As everyone in the banking industry is well aware, banks hold a lot of data and many have spent several years utilising it. Some banks I know have been mining, analysing and really making their data work for them for over 25 years…but there aren’t as many banks like this.

Banking data has been used broadly: sales targeting, fraud, credit scoring, retention etc. And now in the era of “Big Data” more banking data is being collected, especially through online and mobile channels. All good? Yes, and here comes the “but”; it’s all “banking data”. Some may argue that clickstream data is not banking, but it is if the clicks are on bank pages, whether it’s internet banking or the banks web page.

Initiatives like PFM (Personal Finance Management), whilst useful, have further legitimised the collection of financial data only. However, for transformational digital banking, banks have to be more voracious about collecting data and more creative in its use.

For example a bank’s typical approach to credit scoring involves financial analysis of the customer’s income, outgoings and payments history. This approach assumes you need to check financially a person’s ability to pay. Companies like FriendlyScore and Veridu turn this model on its head and use social media data to validate a person’s identity and trustworthiness to pay. Similarly, last year China launched an initiative which will be rolled out nationwide by 2020 to create a “Social Credit” system. Initially, 8 companies have been invited to define scoring approaches, and these vary from analysing online spend (Allibaba/Sesame) to scoring on online dating (Baihe).

Imagine how much more customer service can be improved by understanding the customer’s emotional state when they are contacting you. Companies like Affectiva.com are leading the way in providing emotional detection and analytics. Similarly, several years ago Samsung demoed a prototype phone with in-built emotional detection that worked with several sensors. Their analytics worked on things such as the speed of typing, errors made, pressure and vibration. Microsoft have also demoed “mood sensing” couches and even a “mood” bra.

Some banks have investigated the use of geo-location, for example to highlight the nearest ATM or branch. Some have gone further with geo-fencing, using “beacons” to present offers in real time, or to change electronic billboards as customers walk by locations pinpointed to 5m2.  But how about using Google image search to help you identify where a picture was taken. How could this be useful to a bank? If you could identify the location, you may understand the kind of holidays the customer takes, providing you with an idea of their lifestyle. Customers that use sites like Instagram will also give away how frequently they go on holiday.

The sources and use of data that banks can access are clearly vast, and with the Internet of Things the growth of data is about to explode further still. It will soon be possible to record a person’s entire life: what they saw, what they ate, where they went, how they felt, what they like/dislike, their heart rate, how often they brush their teeth, even how often they wear the same socks before they are washed, and more.

The key to using big data to transform a digital bank will be to gain the customer’s trust, giving them reason to volunteer the data to you, and this will happen more easily if the customer sees value for themselves in the way you use data. For example, being able to extend a credit facility instantly and easily whilst out shopping, getting discounts on things the customer likes, or even just helping them to manage the privacy of their data online.

For some time, one of my favourite sites (I wish a bank would do this for the UK) has been http://peoplelikeu.com.au/ launched by UBank, which allows you to compare how you spend your money with people similar to you (by age, earning, location, marital status etc). It recognises that either consciously or sub consciously we make comparisons and decisions based on other people. This site can be used by anyone, not just bank customers.

Going back to China’s social credit system. Some of the feedback from users was that they were happy to give up their data as it simplified processes; for example they could make a hotel booking without having to pay a deposit. Also, as less than half the people in China have a financial credit history, something that works on data broader than financials will also allow people access to credit.

It is clear there is a huge amount of data available and that with the right value for the customer in providing it, they will volunteer data to you. Even regulators with initiatives like PSD2 are pushing for data to become more openly available with the aiming of improving service and products for customers.

To drive digital transformation it time for banks to think broader thank bank data and really get creative about big data, before somebody else does!