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10 impacts on Fintech

10 trending impacts on Fintech and its metrics

Expectations from reading this article;

·         Understand some significant trends occurring and their impact on #Fintech

·         Propose new considerations within metrics

  • Provide some search hash tags for further research and reading

An introduction to the internet of things #IOT Trend 1:

I wrote in a previous article about the explosive trend of devices being connected to the internet. Since the internet became embraced by the global public we have seen significant waves of adoption. The next largest wave will be the expanded link of devices to the online world. The method of connection is varied and frequency of connection is for another debate!

There is every clear signal that continued connectivity of devices will provide a new opportunity for those capable of reading the information.

IOT in Fintech:

  1. Asset tracking and pay per use models of devices offers new markets within the shared economy.
  2. Geo locating devices can offer reminders of loan discounts when near high value stores like a car show room
  3. Devices acting as “ATM hubs” could be used in remote areas of the world for finance transfers
  4. Positive behavior can be rewarded when a consumer does not buy certain repetitive impulse products and become linked to a health apps
  5. Block chain technology can be used extensively to monitor and manage goods exchange (item swapping) without a true financial transaction been made.
#Fintech metric considerations: Risk models can be calculated and physical assets data trends acquired in real time to become a new #HFT High Frequency Trading metric?
— James Doyle - Founder of JAMSO

An introduction to big data #bigdata trend 2:

You create data all day via consumption, production and interaction with a modern social environment. Big data represents how to store and manage all this data. With the advancements in data heavy media such as video and audio plus the increasing number of people and devices online it is clear to see the need to manage and make use of all this data is a significant area of interest.

Big data in fintech

The finance markets operate with a few more hurdles when seeking to exploit the full benefits of big data. The solutions they find will be transferable outside their industry. Specific interest in the need to protect securely personal privacy and security of finance transactions with big data remains a priority.

  1. This may also become the strength and advantage that Fintech can lead other industries. There may become a need to identify none financial behaviour as a higher bias to decision influences. The impacts therefore to developing higher capabilities and defining correlation models will produce reverse benefits to big data structure.
  2. Collaboration partnerships with none finance industry markets will offer a doorway to useful information i.e. insurance and health industry.
  3. Tailored finance offers and deeper relationships between the investment market and consumer will create new customer clusters.
  4. Crowdfunding and peer to peer lending success models will enable investors to calculate risks at new levels of confidence.
Fintech metric considerations: The measurement of big data velocity is already important for high frequency trading, expect this trend to continue unless if becomes regulated. The selected variety of data sets may become a niche opportunity for many fintech companies to specialise in new specific markets.
— James Doyle - Founder of JAMSO

An introduction to Predictive analytics/machine learning Trend 3:

Source http://goanimate.com/

The British have a saying “red sky at night, shepherd’s delight. Red sky in the morning, shepherd’s warning” This is a weather prediction that has been used for several centuries. There is a high chance that the method of producing predictive analytics in the future will change at a much faster pace. The process is to extract relevant information from available data sources and sets to identify patterns and forecast trends or outcomes. The improvements of this technology still are in its infancy within the public domain. Machine learning takes the predictive analytics results and compares to observed actual results. From this process the algorithm is improved and adjusted to improve future predictions.

Predictive analytics and machine learning in Fintech:

There are many potential applications for predictive analytics that can reshape and make a true impact for the fintech sector.

  1. Behavioural spend levels can show to the consumer if they should purchase that new IPhone or offer a small bridging loan before payday!
  2. Incentives through gamification of savings and geo location devices offers city dwellers many interactive opportunities between the consumer and financial services provider.
  3. The long term value and risk profile of the consumer can help improve the accuracy of credit ratings for personal and business markets.
  4. Alternative currencies have already started to impact the fintech market. Their use of predictive analytics tools to prompt currency exchange between hard currency and crypto currency through community influence offers new market potentials.
  5. I think it is clear that any bank that does not make use of this technology will not survive the twenty first century.
Fintech metric considerations: Advanced applied use of analytics tools to secure the reliability and brand trust.
— James Doyle - Founder of JAMSO

Data Visualization #datavisualization Trend 4

Our consumption of data has grown over time where the consumers have grown disengaged with many traditional methods of sharing information, for example bar charts or pie charts. "Death my pie chart" is a coffee room snigger discussion amongst disengaged staff. Data visualization aims to share in a visual context certain correlations or patterns that may be missed through text representation.

Data visualization in fintech.

  1. This sector has some unique data restrictions which may offer innovative solutions to easier data access points in other industries.
  2. Potential complex behavior patterns could help reduce fraud and improve compliance to regulation.
  3. New financial modelling communication to customers offers opportunity to sell more complex financial instruments to lower finance trained consumers.
  4. Future product purchase images could be used to show how much savings is needed left based on current spend/savings behavior.
  5. Large investment portfolio representations made easier to interact on small mobile device screens  
Fintech metric considerations: The transfer of existing bank and investment trend analysis could be shared across smaller visual screens to retain higher speed and management of financial portfolios. The concept of KISS (Keep it simple stupid) is perfect for #dataviz , simple elegant representation and ease of understanding is needed when dealing with complex subjects with little time to decipher.
— James Doyle - Founder of JAMSO

Artificial intelligence (AI) #AI Trend 5

Source singularityu.org

There can be some perceived cross over of AI with machine learning and predictive analytics as their fields to converge in many areas. This is understandable but best understood to be identified separately. AI aims to seek reasoning through machine learning, knowledge, robotics, language processing and the planning of tasks.

AI in Fintech:

The term robo-advisor is used for services already in the market that simulates behavior close to AI. Using a set of pre agreed rules; the system gives financial advice tailored to the individual needs. This offers low cost financial services support for shorter term transactions. We may see this technology by the birth of true AI in the finance sector.

  1. AI could assist a unique portfolio based on age, spending patterns, family status and many external global factors to offer interesting investment opportunities. Imagine a person in California with an interest in protecting wildlife being offered a peer to peer investment opportunity for an anti-poaching product in Kenya to be produced in Taiwan?
  2. The use of AI technology in asset verification. 
  3. Security work for high value transactions.
  4. Extending the “personal” user experience by having robots providing 1:1 financial advice.
  5. Financial intelligence deployed into various other robotic devices to inform if best to repair, replace, hire new equipment.
Consideration of metrics in Fintech using AI: Embracing world class standards already achieved in the retail sector can help the finance industry implement new relevant standards.
— James Doyle - Founder of JAMSO

Gamification #gamification Trend 5

The continued rise of gamification in modern society is of key interest. The concept of using themes and rewards as motivation to behaviors has a key role in education, social and business environments. See my prior articles on gamification:  Gamification in performance management

Gamification in fintech has many global opportunities.

  1. Method to reward good credit behavior of consumers.
  2. Help gain access to additional consumer behavior information to help with credit risk measures and authentication process.
  3. Establish closer brand relationships.
  4. Help educate consumer level knowledge of more complex financial instruments for sale i.e. derivatives, options trading. 
  5. Improve the user experience and create a unique environment
Metric considerations for gamification within Fintech: Individual and population level knowledge validation of financial instruments and additional authentication data points.
— James Doyle - Founder of JAMSO

Customer Experience (CE) / User Experience (UX) ( #UX ) Trend 6

 

The globalization of commerce in B2B and B2C environments means ever higher levels of improved customer service expectations. This includes the full range and time of a person's emotions and attitudes about using a particular product, system or service.

UX in Fintech.

The user experience is is one of the unique selling points of Fintech over traditional banking!

  1. Reach to wider global audiences.
  2. Unique personalized financial experiences per customer.
  3. Faster and more convenient financial service information and transactions.
  4. A true 24/7 always on secure financial service.
  5. Make finance less of a touch-point but more an integrated action
Metric considerations for UX in Fintech: There are many individual subjective areas of measure that will need to be grouped for statistical relevance. A clear priority of the business position within the market can help define the most relevant metrics.
— James Doyle - Founder of JAMSO

Block chain #blockchain Trend 7

The technology behind the infamous Bitcoin and many other crypto-currencies is called the block chain. This technology is a significant revolution that has impacts way beyond finance. The ability of the block chain to become an open ledger is simple, pure and highly powerful for future society. 

Blockchain in Fintech.

So far we have seen bitcoin and a whole family of crypto currency options on the market. Future additional opportunity for the technology includes

  1. Cross border currency exchange.
  2. Global portfolio asset tracking.
  3. Decentralized functions and impacts of current leading banks and exchanges and government.
  4. Regulatory benefit for transaction transparency.
  5. New methods to create value outside normal state currency to exchange services and goods.
Metric considerations with block chain within Fintech: What you can do with money, you can do with the block chain plus keep a clear trace on it with exact time stamps. Metrics galore.
— James Doyle - Founder of JAMSO

Cyber security (#Cybersecurity) Trend 8

The revelations by Edward Snowden had a profound impact across the globe; we also see continued escalation and increase of hacking activity. The developed world has become as dependent upon technology and data as it has become on water. This is a bold statement to make but consider your water and electric supply could/would be seriously affected through loss of data to manage and supply it. The need to protect control and ownership of data includes from privacy, IP and physical control of our lives and touch-points.

Cybersecurity in Fintech is an obvious concern and challenge.

  1. Privacy and data protection of payment/transaction information is developing and already better than standard credit card security
  2. Block chain technology provides already many advantages and requires continued development to provide innovative solutions for security across all financial based transactions.
  3. The Edward Snowden revelation has changed the way the tech community accepts advice from “respected sources”. This increased paranoia is a positive development to ensure more secure robust technology.
  4. The service offering of Fintech is now the established "go-to" sector for cyber security challenges in finance.
  5. Applications outside of the financial services sector will allow many Fintech companies to diversify by technology transfer into new industry areas.
Metrics considerations in Fintech with the block chain : A method of gaining trust with suppliers, partners and consumers. Efficiency and effectiveness benchmark figures will provide amongst the best future metrics to share and prioritise. Positive behavior compliance and control of process are typical good examples.
— James Doyle - Founder of JAMSO

3D Printing #3DPrinting Trend 10

The methods of producing products since the industrial revolution has predominately been focused on forming solid material blocks and then removing material to create the final form or sub assembly components. A few exceptions to this rule apply but overall this has been the method. 3D printing is in its infancy and offer many dynamic flexible options to produce goods.

3D printing in Fintech.

These two technologies may at first have little connection however I will try to establish some!

  1. Payment methods of globally purchased but locally produced products can be done through mobile devices
  2. The block chain has already been identified as a great asset tracking technology and can be used within a full supply chain map and management control for the produced products, 3D printers and source materials.
  3. Pricing levels for 3D products can be created via understanding complex scarcity and desirability algorithms used within fintech
  4. Government regulation of tax collection can be automated with access to customer, consumer and product prices, thus automating tax revenue and potentially removing tax reported obligations by companies and consumer independently
  5. Become part of the full user experience by offering payment in gamed currencies for the youth toy market
Metric considerations for 3D printing in Fintech: Time of transaction and release of product or production start point after acceptance of payment and authentication areas will be amongst the key interesting metrics.
— James Doyle - Founder of JAMSO

Impacts to metrics in Fintech

Fintech metrics is primed to benefit directly and indirectly from the 10 trends shared.

The metrics and performance indicators applicable many decades ago have evolved with improved technology and new demands in the market for financial services. The explosion of growth in the above trending areas provides some interesting new metrics that should be monitored and managed.

The ultimate design of metrics and KPI’s remain the same. They should be to help the business perform to desired levels and allow correct information for actions to be taken. Too many metrics may have been a challenge for many managers over the past 20 years and yet we now enter a period of time where data collection can utilize the power of big data, machine learning and artificial intelligence to identify and communicate through use of data visualization new synergies not previously manageable, known or capitalised upon.

There are some metrics these new trends highlight as key areas of interest:

1)      Improvements in customer and user experiences in real time.

2)      Governance and compliance areas for security

3)      Supply chain quality (Mobile, plastics, bandwidth, screen sizes)

4)      Capacity utilization of computer power, information band width and processing power

5)      Uptime will remain a critical measure in an online world

6)      Rate of change from concept to market implementation

7)      Energy cost per transaction

8)      Productivity levels of employees and computer equipment

9)      Revenue growth

10)   Cost of customer acquisition

11)   User and customer churn rate

12)   Contribution margin for specific product/service lines

13)   Future technology investment costs

 

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