IN FOCUS 

AI IN THE

FINANCE SECTOR 2019

 

 

IN FOCUS 

AI IN THE

FINANCE SECTOR

2019

How technology is shaping finance
How technology is shaping finance
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Will 2019 see artificial intelligence usher in a new dawn of customer experience built on big data and intelligent systems that change the way we think of finance forever? Or will it prove to be yet another false start on the AI campaign for a brighter more augmented future?

The financial ecosystem has seen many developments within the past few years which have massively changed the way the industry is thinking about future products and services. The accessibility of new open banking laws has changed the way we can visualise our finances and how this information is shared. Also, the trusted regulation of blockchain and the visibility of historical transactions makes it rich for financial implementation, and advancements in natural language processing have opened numerous doors for additional services and functions offered by digital assistants.


In this article, we'll take a look at existing customer pain points that people are experiencing, including transparency of financial products, personalized and valued service, credit checking and historical data accuracy, and what opportunities these provide within the industry. What can AI do to make the finance world a better place?


Also, we take a look at key sectors within Finance: Mortgages, Pensions, Wealth Management, Insurance and Banking by taking a screenshot of the existing landscape to better understand where the industry is on this technological roadmap, and who are making the biggest inroads into AI adoption.

MOST IMPORTANT TECHNOLOGIES DISRUPTING FINANCE

PROJECTED GLOBAL HEALTH SPEND ON AI

Percentage of different industries who believe the following are important to their sector

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Finance_chart

OPPORTUNITIES & GOALS

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cost
Finance
Dynamic
Fraud
predict
data capture
safeguard
accuracy

EMERGING TECHNOLOGY PLATFORMS

EMERGING TECHNOLOGY PLATFORMS

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blockchain
open
recommender
ml
Biometrics
Chatbots
NLP
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86% of consumers are interested in using biometrics to verify identity or to confirm payments.

VISA

86% of consumers are interested in using biometrics to verify identity or to confirm payments.

VISA

Existing pain points
Existing pain points
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Every industry has pain points within its services and no more than finance. Burdened massively with security regulations and anti-fraud mechanics, what can AI offer the customer in making experiences more efficient and enjoyable?

1: SECURITY AND AUTHORISATION

Security procedures can become blockers for customers to complete tasks. Remembering passwords for apps, online banking, telephone banking and random password retrieval answers can cause frustration and failed tasks.

OPPORTUNITY

Biometrics offer the user the opportunity to use fingerprint, palm veins, face recognition, DNA, palm print, hand geometry and retina recognition as a form of security with no need for any recall. With a recent push for 2 step authentication, aligning all channels for single sign-on by reducing recall will help the user to complete tasks and reduce cognitive overload.

2: OMNICHANNEL SERVICE

The inconsistency of the levels of banking features and services different channels offer. 

OPPORTUNITY

When all channels are aligned and serve the customer needs regardless of the platform, we get a much better experience. A single sign-on validated by device, location or security requirements - which sees the complete customer journey and interaction points along the way - will deliver a seamless experience. Not only that, but it would create a better and more detailed view of a customer and the touch points they have accessed, providing better insight and opportunities.

3: TRANSPARENCY OF FINANCES

Keeping track of all your financial products from credit cards, student loans, mortgages to pensions.

OPPORTUNITY

Open banking has opened the door to full transparency of accounts, all in one place, via a third-party app or digital service. This has provided the customer with clarity and visibility of their finances in a way that has never before been possible, by allowing your financial products from different providers to be viewed in one place in real time. It can also offer payment alerts, budgeting advice and keep track of all your subscription services in one place. 

4: USABILITY & PERSONALISATION 

Users are expecting a personalised and relevant experience at every stage of interaction with brands and services. A one-size-fits-all design does not provide a connected experience.

OPPORTUNITY

ML and AI can recognise returning users and offer better recommendations and information related to products already held. It can also predict needs by matching user behaviour to that of other customers.

5: SIGNING UP & ACCESSING SERVICES

Financial services require a large amount of personal data input to set up or access digital services.

OPPORTUNITY

In this digital age, with so much of our data already online, customers now expect to be recognised at any touch point and be able to sign up to services even quicker with less manual input using data already stored on another service or platform. Digital onboarding is expected to plug into available personal data were possible for a frictionless, but secure experience.

6: CUSTOMER DISCONNECT

Institutions that do not understand their customers are not only missing an opportunity to engage with meaningful content, but they are also risking not giving the customer the right products or service.

OPPORTUNITY

There are moments when timely messaging or product recommendations can be really appreciated. AI can predict churn and find opportunities by analysing data and matching the life stage a customer may be at and therefore provide a more bespoke and intelligent service.

7. COMPLEXITY AND AMBIGUITY

Products and service offerings in the financial sector can sometimes be difficult for a customer to understand completely. 

OPPORTUNITY

Financial companies need to facilitate their customers to build financial literacy. AI chatbots can be used to guide customers through difficult or new actions, and can also predict pain points in a journey by historical usage and prompt the user with better-timed information when legal requirements may create a blocker.

8. CREDIT CHECKING 

It can be difficult for a customer to generate the required documentation necessary and historical fraudulent action can sometimes only become visible to a customer when going through this process. 

OPPORTUNITY

Open banking and account access have allowed a different way to credit check customers by looking at current financial data in greater depth rather than viewing only historical behaviour. The concept is simple: ML can identify salary payments, outgoings, disposable income and regular subscriptions and map these to behaviour models which match that of a viable customer. By looking at real-time behaviour and data, the customer does not have to spend time locating statements and payslips or filling out lengthy forms stating savings, utility bills and other expenses, and financial institutions get a better picture of the risk and viability of any new customers.

9. SELF-SERVICE

Customers want to be able to manage financial transactions or purchase new products on their own with minimal effort and without additional human interaction.

OPPORTUNITY

Whether it’s a customer buying home insurance, setting up a direct debit or adding a named driver on a car insurance policy, it’s important that they can complete this task in one place without any compromise to customer experience. Assistance via chatbots can guide a user through processes for added support, AI can auto-fill data that is already captured and biometric signatures remove any sign and return of legal documentation

10. PAYMENTS

Payments usually require the highest level of security and are normally the most demanding of all functions to complete.

OPPORTUNITY

Biometrics and passwords are always reliable methods of validation. But as well as this machine learning could analyse customers spending patterns, products bought, services or more commonly used online portals and grant access immediately if the behaviour or request is in line with these existing patterns.

HOW FINANCE IS USING AI

Banking
Banking
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Although the adoption of AI in finance is somewhat behind other sectors such as health and retail, Banking has historically been the first area within finance to utilise technologies. Customers are now expecting banking to mimic how they use other digital products to get things done, so it's no wonder that the scope of AI in Banking is so overarching.

BLOCKCHAIN AND DATA INTEGRITY

Blockchain technology provides immutable historical and real-time data records that are visible to everyone involved. This will improve data accuracy and security, help reduce the risk of fraud, and show compliance through an audit trail.

  • A single source of truth increases efficiency. By creating one version of a ledger that is synchronized across computers, blockchain can help eliminate out-of-sync ledgers.
  • Data integrity and security offers the opportunity to reduce fraud and errors, improve inventory management, identify issues more quickly, reduce delays, and increase trust.
  • Customer experience improvements through faster processing. Blockchain can share information with clients and vendors, companies may be able to define sales opportunities and serve customers far more quickly than with traditional systems.
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MONZO - BANKING APP

Along with a built-in money management budget tracker, Monzo also employs a very intuitive sign-up process which uses image recognition to verify identification. It does this in two ways, first of all, it asks for valid passport or driving license which the user is required to photograph front and back through the app. It then asks you to record a 5-second video selfie which not only matches your face to the photographic ID but also captures your voice for a further level of security. Along with touch ID, Monzo ensures that personal biometric security underpins the accessibility of the account.

ROBOTS IN BANKS

Santander first introduced red robots to show guests around their Spanish visitor centre in 2010. More recently HSBC have deployed a robot called Pepper, the engaging, social humanoid robot, in one of its branches in Seattle. Pepper is currently engaging in conversational interactions with banking customers helping people with simple enquiries and working alongside human coworkers to improve the customer experience.

VOICE ENABLED ASSISTANCE AT HOME

IMAGING TEST RESULTS

The Swiss bank UBS, ranked number 35 globally for its volume of assets, has partnered with Amazon to incorporate its “Ask UBS” service into Alexa-powered Echo speaker devices.

Aimed at UBS’s European wealth management clients, Ask UBS enables users to receive wide-ranging advice and analysis on global financial markets just by “asking” Alexa. “Ask UBS” also acts as a teaching resource, offering definitions and examples of acronyms and jargon related to the financial industry.

BIOMETRICS AND AUGMENTED SECURITY

A growing number of banks are utilizing biometric data, like fingerprints, facial recognition or voice to replace or augment passwords and other forms of client verification.

A report by Goode Intelligence forecast that 1.9 billion bank customers will be using some form of biometric identification by 2021, and reportedly Halifax have even experimented with Bluetooth wristbands that identified a client’s unique heartbeat to authenticate account access.

EVA - BANKING CHATBOT

EVA (Electronic Virtual Assistant) is an AI-powered banking chatbot. You can also talk to Eva through Amazon Echo devices. Eva uses the latest in AI and Natural Language Processing to understand the user query and fetch the relevant information from thousands of possible sources, all in a matter of milliseconds. Customers can get the information they are seeking instantaneously by conversing with Eva in human language instead of searching, browsing, clicking buttons or waiting on a call.

Eva has already answered more than 5 million queries from around a million customer with more than 85% accuracy. Eva holds more than 20,000 conversations every day with customers from all over the world.

EVA

FRAUD PREVENTION

The ability of AI to analyse big data and identify patterns that might elude human observers is one of its greatest strengths. One area where this capacity is particularly relevant is in fraud prevention. But just as AI is keeping fraud at bay, it is also the desired tool of hackers who are constantly attacking and probing security systems with adaptive algorithms, and lines become even more blurred when banks themselves are creating hacking AI to find weaknesses within their own systems in a never-ending battle for security. 

According to McAfee, cybercrime costs the global economy $600 billion. AI and machine learning solutions are being deployed by many financial service providers to detect fraud in real time. An additional benefit of improved fraud prevention technology is that legitimate activity is flagged as fraudulent less often.

According to Tech2, Mastercard was able to reduce “false declines” for its customers by 80 per cent using AI technology. A false decline is where a customers card is rejected because the card may have been used recently for a bigger purchase, or in quick succession due to 'false' predictions that the activity is fraudulent.

NATURAL LANGUAGE PROCESSING & SPEECH RECOGNITION

Santander customers can make payments to friends by simply asking their iPhone. The bank’s smartphone app also allows customers to see their recent transactions and report a lost card, just by talking to their phone.

First Direct and Barclays, meanwhile, are implementing voice-recognition technology that identifies customers contacting telephone banking by not only the tone of their voice but also analysing sounds created by the – larynx type and nasal passages thereby removing the need for security questions or passwords.

Nobody needs to be a bank to replace your banking app.

Cleo co-founder Barney Hussey-Yeo

Nobody needs to be a bank to replace your banking app.

Cleo co-founder Barney Hussey-Yeo

Personal Finance
Personal Finance
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Balancing personal budgets is something we do constantly within our daily lives. With more and more transactions taking place via card, or digitally, our association with cash is slowly diminishing and bringing with it a culture of devaluing money which has changed how many think about finance. From Payday nirvana to end of the month blues, most of us don’t really know what happens in between. How much did we spend on Ubers that month? Or refreshments’ in The Crown & Anchor? Or what date our Spotify subscription goes out for instance, or even how much it is for that matter? Here’s how tech is helping us understand our finances and changing behaviour towards it.

OPEN BANKING

Wouldn’t it be nice to see every penny you earn – or owe – all in one place? There’s an app for that – many apps, in fact, all of which utilise Open Banking. Open banking is the agreed sharing of customer data through third party platforms to offer a better quality of data and better access to financial products. In today’s financial market, you might have a current account with one provider, an Isa with another, a credit card with a third, and a mortgage from your local building society – not to mention a prepaid card for everyday purchases. Open banking allows banking and third-party apps to have visibility of this data and offers users new ways to see their financial ecosystem.

Day to day money management and budget tools are quick and easy ways for a user to check finances and manage finances on a salary to salary basis. With open banking paving the way for third-party access to current accounts, savings, and more, Money Management apps are becoming more and more popular for a one-stop shop of visible finance in real time.

yolt_logo

YOLT - Money Management app

Taking advantage of open banking is YOLT. Using data from a customer's current account, credit cards, mortgage etc… this app assists making informed financial decisions with a clear view of how, when and where they are spending money. Everything is categorised automatically and displayed back to the user with insights and feedback on budget goals. The system can detect salary, utility bills, and subscriptions as well as flagging any unusual activity on your account in real time. It also compares utility bills to find you the best deal.

Using ML and AI the app encourages positive behaviour change by analysing spending patterns and providing possible solutions where savings could be made and overspending needs to be more closely monitored. As YOLT is not governed by banking laws, it is much easier for advice to be given through the app.

Cleo_logo

CLEO.AI - MONEY MANAGEMENT APP

The customer problem Cleo has set out to solve is helping millennials ‘value’ their money. How they deliver this solution is also very much on par with how users communicate and interact with the world. Users access Cleo via a Facebook Messenger chatbot which answers simple questions like ‘How much do I have to spend until payday?’ ‘What’s my Credit Card balance?’ and ‘How much did I spend on Ubers this month? It gives insights into spending across multiple accounts and credit cards, broken down by transaction, category or merchant. You can choose to put money aside for a rainy day or a specific goal, donate to charity, set spending alerts, and more.

It’s a proactive bank. It talks to its users and passes on valuable information in a chatty familiar voice and supplies well-timed messages to its users - ‘Morning John, it’s Monday again and you have £155 you can spend this week!’. The messaging from Cleo is delivered in a friendly casual chatty manner befitting facebook messenger and truly resonates with its users, in particular, the millennials.

Cleo also implements the mobile wallet as a handy place for money to be put aside, it is held here to keep safe, or pay friends through Facebook, and can be accessed or transferred back into any bank account linked to the service at any point.

Many apps are also exploring the concept of saving or investing ‘loose change’. This is basically taking the small amount of money left over from a transaction that isn’t exactly rounded off to the pound and moving it to a savings or investment account.

Pensions

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There is currently a huge disconnect between pensions and their owners. Lack of clarity and information, as well as real-time visibility of status, are mirrored in the lack of trust and belief in this area of finance with employers failing to supply the tools to educate and inform workers, 43% of which say they aren’t even sure they get an annual update of their pension from employers.

Although Pensions seems to be one of the slowest areas of Finance to utilise AI, the immediate potential is already being explored. AI uses big data and can analyse and predict patterns in existing and historical pensions. It utilises long term strategy and can adapt along the way to provide a more flexible product and service to customers. AI could also define success in terms of the ability to pay out pensions and therefore reduce the need for taking the unnecessary risk trying to generate more return than is needed to pay all pensions.

 THE ‘PENSIONS TECHNOLOGY SURVEY 2018’ REPORT RESULTS BY PWC

THE ‘PENSIONS TECHNOLOGY SURVEY 2018’ REPORT RESULTS BY PWC

  • 53 % of employers surveyed plan to invest in automated member communications in the next three years.
  • More than ⅓ of employees have never viewed their pension online
  • Workers from younger generations are already more likely to view their pension savings online and now want much more sophisticated tools to manage their pensions

AI promises a much more connected experience with reduced costs, improved governance, accurate information in real time and de-risking decision making.

It’s more than inevitable that Robo-advice and AI will become a massive part of this evolution, it’s more a question of how soon?

With 80% of customers willing to use digital and remote channel options for different tasks, today's insurance lenders must prepare for the adoption of blockchain and big data, the growing challenges of cybersecurity and more.

VISA

With 80% of customers willing to use digital and remote channel options for different tasks, today's insurance lenders must prepare for the adoption of blockchain and big data, the growing challenges of cybersecurity and more.

VISA

Insurance

Insurance

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Insurtech, similar to Fintech, has seen a boom in the last 5 years. New technology savvy players have entered the sector, playing on existing pain points within AI applications that help smooth, improve and completely change existing processes.
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As can be seen from the above, the main Insurtech opportunities have been around the distribution of Insurance, which has happened through technology platforms. From Lemonade using AI and a natural language interface to get customers a home insurance quote in a matter of seconds to Cuvva changing the way we pay for car insurance and selling coverage for single journeys, the capability for customers to buy insurance that is tailored to their specific needs has increased steadily in recent years.

With many different technologies affecting the Insurance industry at present, machine learning technologies are at the heart of most - whether they are stitching several different platforms together or creating a tactical improvement to an existing process.

The implementation of machine learning/AI is being seen to have the following benefits to Insurance companies:

The main Insurtech opportunities have been around the distribution of Insurance, which has happened through technology platforms. From Lemonade using AI and a natural language interface to get customers a home insurance quote in a matter of seconds to Cuvva changing the way we pay for car insurance and selling coverage for single journeys, the capability for customers to buy insurance that is tailored to their specific needs has increased steadily in recent years.

With many different technologies affecting the Insurance industry at present, machine learning technologies are at the heart of most - whether they are stitching several different platforms together or creating a tactical improvement to an existing process.

The implementation of machine learning/AI is being seen to have the following benefits to Insurance companies:

1. CUSTOMER EXPERIENCE

By making use of external data, companies are able to speed up the experience of buying their products. Conversion can also be optimised through AI enabled customer service products such as ZenDesk and Intercom.io. By having chat installed at the right point in customer journeys, companies can improve conversion rates dramatically. By having AI driven chat, companies are able to reduce the workload of customer services by improving the wayfinding capability of their site.

2. CROSS SELLING

Insurance companies with multiple products are using AI and data to make better decisions as to when their existing customers and those interested in their services are likely to be interested in their other products.

3. UPSELLING

Insurance companies can use customer data to classify those customers that are likely to purchase extra and additional insurance services. This use of data has been happening for sometime and has proved very successful within the Car Insurance sector.

4. REDUCED RISK/CAPITAL COST

By crunching data and formulating more information about a potential client, Insurance companies are able decrease risk and make the right decisions in a cheaper way.

5. ACQUISITION EXPENSE RATIO REDUCTION

Traditionally in Insurance, there is nothing more expensive than acquiring a customer. With so many competitors out there, in most sectors, it can be difficult to fight for a single customer. By gaining an understanding of the customer and giving them a personalised policy, a company can run more efficiently and therefore reduce the investment they make on acquiring new customers.

PAY-HOW-YOU DRIVE CAR INSURANCE

Telematics sensors fitted into a vehicle allow real-time tracking. Pay-how-you-drive insurers monitor the kind of driving you do through this device and when you do it. If you accelerate hard and brake sharply, drive on dangerous roads and at dangerous times – peak commuter times and late at night – you pay more.

drive
lapetus_icon

USING IMAGE RECOGNITION TO QUOTE

WELLBEING APP BASED COURSE

Lapetus is a Life Insurance broker in the US, who are quoting people based on their selfie. The company use image recognition software to analyse facial patterns to discern signs of life-threatening habits such as smoking. As they serve as a strong predictor for lifespan, Lapetus decided to use them in lieu of expensive, uncomfortable and time-consuming medical examinations.

PAY-AS-YOU-GO CAR INSURANCE

With pay-as-you-go car insurance, the less you drive, the less opportunity there is for you to be involved in an accident. Because the risk is lower, the premium is lower also. Driving data is sent to the insurer via the tracking unit which can be viewed by the customer in a pay-as-you-go app.

vitality
vitality_logo

VITALITY - INTERACTIVE HEALTH INSURANCE

Vitality health insurance combines a wearable device and a rewards system to incentivise a better and healthier lifestyle. Customer data is sent via the device and is also visible through the Vitality app with reward points being achieved based on the results of the customer's activity, which can then be spent on retail vouchers, gym membership or technology items like Apple watches and FitBits. The growth of these ‘Interactive’ policies has recently led to the largest and oldest American Life Insurer, John Hancock, to sell only this type of insurance from 2019.

guevara_icon

POOLING PREMIUMS

Guevara is a whole new way to think about car insurance. The service allows users to pool premiums online to save money. Unlike traditional insurance, any money left in the pool at the end of the year stays with the group and lowers everyone’s price next year. Users that keep claims low can save up to 80%.

Friendsurance drive a similar concept to Guevara, only they utilise the power of social networks to take things further. Friendsurance has implemented the concept of online P2P insurance which combines social networks with well-established insurance companies. Customers can connect to form individual insurance networks, thereby lowering their annual insurance premiums by up to 50%

cuvaa

INSURANCE WHEN YOU NEED IT

Cuvva was launched in October as an iOS app that enables the user to sign up, get a quote and buy cover in less than 10 minutes. Cuvva offers a completely digital experience run from a smartphone. It is a totally new type of UK car insurance that gets users covered on a car for only as long as they need it—from a single hour to a whole day.

brolly_logo

BROLLY - INSURANCE ADVISORY APPLICATION

Brolly is the UK’s first artificially intelligent insurance advisory application that delivers contextually relevant insights through web and mobile apps which enables customers to make informed decisions about their insurance. Brolly users only need to enter their information once and purchasing new cover will be achieved with one simple tap and can also see if they are under or over insured as well as seeing where they can get a better deal from. It’s partnered with some of the largest Insurance firms and allows the customer to view all insurance policies in one place, and providing instant access to documents, prices, and contact numbers.

 Positive user experience, such as an ‘easy/quick application process’, ‘fast decision-making’ and the ‘convenience of an online platform’ all trumped ‘competitive rates’ in consumer borrowing.

Delloite

Mortgages

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Mortgages are changing to reflect current home buying trends. With older generations using pensions as savings and younger buyers priced out of the market, this field of finance is experiencing change on a grand scale. It's now more important than ever to offer better products to best-fit customers needs and mirror where the customer is, on their life journey. So how does AI benefit and add value to this momentum?

OPEN BANKING WITHIN THE MORTGAGE PROCESS

Open banking at this point has not been fully utilized within the mortgage process. Its application could be used in the release of bank statements and identification to confirm customer of salary and savings, but it could also be analysed to show the positive or negative habits relating to how the customer handles their finance. Data fields can also be pre-populated and validated within the mortgage process offering a much better assessment of risk which could also speed up the process for both the bank and customer.

RESERVATIONS AROUND OPEN BANKING

Though there are advantages to a customer, the level of trust a user will have to have in allowing their bank data to be used for estimating their spending, savings and earnings will have to outweigh their desire to have control over the variables and data they wish to present to the bank. Although the potential for open banking sounds great, research shows the majority of customers don’t understand the implications or the benefits.

ROBO BROKERS REFLECT THE CHANGING BEHAVIOURS OF MILLENIALS

According to Retail Banking Insight survey, 70% of first-time buyers are millennials, most of whom are very comfortable using digital channels. Within this survey, only 37% of participants would opt to speak with a bank representative in-branch and 5% would use a call centre.

The current reality of robo advice in mortgages is that it is a hybrid proposition. Customers still have to speak to a qualified mortgage adviser in order to confirm acceptance of the mortgage advice from the digital adviser. Robo brokers like Habito, Trussel and Mortage Gym reflect a changing shift of the mobility, speed and effort that younger people expect when researching and making transactions. Meeting with mortgage brokers reflects a context that many people find takes time, requires travel and a definitive desire to make a choice.

RESERVATIONS AROUND ROBO BROKERS

By making use of external data, companies are able to speed up the experience of buying their products. Conversion can also be optimised through AI enabled customer service products such as ZenDesk and Intercom.io. By having chat installed at the right point in customer journeys, companies can improve conversion rates dramatically. By having AI driven chat, companies are able to reduce the workload of customer services by improving the wayfinding capability of their site.

Castlight

CASTLIGHT CREDIT CHECKING

Castlight is developing an ‘affordability passport’ for customers and providing banks with a categorisation of data-as-a-service. Their use of open banking gives a real-time picture of a customer, taking into account their current situation, instead of scoring them on past data.

This means that creditworthiness could be re-scored and completely re-thought. Most importantly, such an application could automate lending approval.

It is estimated that algorithms now account for 90% of financial market trading. Yet there are only a few managed funds that are fully using machine-learning technology.

IPE - Intelligence on European Pensions and Institutional Investment

It is estimated that algorithms now account for 90% of financial market trading. Yet there are only a few managed funds that are fully using machine-learning technology.

IPE - Intelligence on European Pensions and Institutional Investment

Asset and wealth management 

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The possible applications of AI relating to investment decisions, and making use of existing big historical data is well and truly underway in this area. Supervised and unsupervised natural language learning techniques applied to financial data, news, industrial sensor data – or even social media data – could potentially offer investment firms an edge in this market.

ROBO BROKERS

Robo brokers use a platform built on AI and ML technology to help investors with their money. They are incredibly popular and generally reliable in an area of finance which carries a great deal of risk. Investors are required to fill out personal information, investment goals and risk tolerance, and then the robo broker will automatically create a portfolio for the customer based on this data and manage it, making sure it stays on that trajectory over time. The system monitors the stock markets, and analyses areas that are relevant to the investor looking for profitable times to sell or buy assets much quicker than a human broker possibly could. This role can be totally autonomous or augmented with the user if they feel more comfortable taking part in the process.

SCHWAB INTELLIGENT ADVISORY

Charles Schwab has raised the bar with their Schwab Intelligent Advisory, a hybrid service designed to be a middle ground between the online broker’s financial consultants and its existing robo-advisor.

A user can create a plan for retirement, college or savings and connect all their financial products to offer a clearer insight into future outlook. A robo-advisor will monitor the portfolio daily, automatically rebalancing it as needed, to help keep you diversified and on track.

All of this is underpinned by real-time human support via connectivity through app and desktop platforms to complimentary consultations with a certified financial planner.

WEALTH MANAGEMENT CHATBOT STARTER KIT

IBM has launched a chatbot starter kit for companies in the investment and wealth management sector. The kit offers help to companies so they can get started on the path to creating a chatbot that will enable users to query portfolios and associated holdings. The chatbot can answer questions such as, What shares are in their portfolio currently? What is the value of my portfolio? What are my top holdings?

LOOKING FORWARD TO THE FUTURE

LOOKING FORWARD TO THE FUTURE

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Summary
What's next and how it affects us all.
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2019 could be the year that Finance really advances its adoption of technology and changes the existing landscape that has so far been behind many sectors such as health and retail. One of the biggest opportunities (forced or otherwise) has been Open Banking. This has changed completely the concept of customer finance management and allowed third parties to enter what has previously been a 'members only' club. It's also allowed customers to see what is possible, and imagine what's to come.

It's easy to see other opportunities within finance and following in the footsteps of already adopted technology which has laid most of the groundwork, we should see change sooner rather than later. Millennials are pushing for better customer experience across the board and for the first time these digital natives have displayed a preference of technology than to face to face interactions. So does this mean the death to the brick and mortar branches? Or human customer service?

There will always be an evolution of job roles. As time goes by roles will adapt as intelligent automation removes mundane tasks from certain positions. For instance, for years the key role of a bank teller was to dispense cash to customers before ATM's and card payment services removed the need for this. But rather than banks employing fewer people, they have been given opportunities to expand product offerings and through this employ more staff in more human roles. It's this pattern of evolution that will take us forward into the next realm of finance which promises to augment AI and humans to create smarter more efficient financial services for us all. 

 

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For more information or to discuss your own Intelligence Audit please contact Paul Vallois, managing director.
paul.vallois@nimbletank.com
020 3828 6440
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