financial symbols coming from hand

FinTech: End to End Framework for Client, Intermediary, and Institutional Services

Is it all about being the most convenient,  payment processing partner, with an affinity to the payment processing brand?  It’s a good place to start; the Amazon Payments partner program.

FinTech noun : an economic industry composed of companies that use technology to make financial systems more efficient

Throughout my career, I’ve worked with several financial services  teams to engineer, test, and deploy solutions.  Here is a brief list of the FinTech solutions I helped construct, test,  and deploy:

  1. 3K Global Investment Bankers – proprietary CRM platform, including Business Analytics, Business Objects Universe.
  2. Equity Research platform, crafted based on business expertise.
    • Custom UI for research analysts, enabled the analysts to create their research, and push into the workflow.
    • Based on a set of rules,  ‘locked down’ part of the report would  “Build Discloses” , e.g. analyst holds 10% of co.
    • Custom Documentum workflow would route research to the distribution channels; or direct research to legal review.
  3. (Multiple Financial Org.) Data Warehouse middleware solutions to assist organizations in managing,  and monitoring usage of their DW.
  4. Global Derivatives firm, migration of mainframe system to C# client / Server platform
  5. Investment Bankers and Equity Capital Markets (ECMG)  build trading platform so teams may collaborate on Deals/Trades.
  6. Global Asset Management Firm: On boarding and Fund management solutions, custom UI and workflows in SharePoint

*****

A “Transaction Management Solution” targets a mixture of FinTech services, primarily “Payments” Processing.

Target State Capabilities of a Transaction Management Solution:

  1. Fraud Detection:  The ability to identify and prevent fraud exists within many levels of the transaction from facilitators of EFT to credit monitoring and scoring agencies.  Every touch point of a transaction has its own perspective of possible fraud, and must be evaluated to the extent it can be.
    • Business experts (SMEs)  and technologists continue to expand the practical applications of Artificial Intelligence (AI) every day.  Although extensive AI fraud detection applications  exists today incorporating human populated Rules Engines,  and AI Machine learning (independent rule creation).
  2. Consumer “Financial Insurance” Products
    • Observing a business, end to end transaction may provide visibility into areas of transaction risk.   Process  and/or technology may be adopted / augmented to minimize the risk.
      • E.g. eBay auction process has a risk regarding the changing hands of currency and merchandise.  A “delayed payment”, holding funds until the merchandise has been exchanged minimized the risk, implemented using PayPal.
    • In product lifecycle of Discovery, Development, and Delivery phases, converting concept to product.
  3. Transaction Data Usage for Analytics
    • Client initiating transaction,  intermediary parties, and destination of funds may all tell ‘a story’ about the transaction.
    • Every party within a transaction, beginning to end, may benefit from the use of the transaction data using analytics.
      • e.g. Quicken – personal finance management tool; collects, parses, and augments transaction data to provide client  analytics in the form of charts / graphs, and reports.
    • Clear, consistent, and comprehensive data set available at every point in the transaction lifecycle regardless of platform .
      • e.g. funds transferred between financial institutions may  have a descriptions that are not user friendly, or may not be actionable, e.g. cryptic name, and no contact details.
      • Normalizing data may occur at an abstracted layer
    • Abstracted, and aggregated data used for analytics
      • e.g. average car price given specs XYZ;
      • e.g. 2. avg. credit score in a particular zip code.
    • Continued growth opportunities, and challenges
      • e.g. data privacy v. allowable aggregated data
  4. Affinity Brand Opportunities Transaction Management Solution
    • eWallet affinity brand promotions,
      • e.g. based on transaction items’ rules; no shipping
      • e.g.2. “Cash Back” Rewards, and/or Market Points
      • e.g.3. Optional, “Fundraiser” options at time of purchase.
  5. Credit Umbrella: Monitoring Use Case
    • Transparency into newly, activated accounts enables the Transaction Management Solution (TMS) to trigger a rule to email the card holder, if eligible, to add card to eWallet

Is Intuit an acquisition target because of Quicken’s capabilities to provide users consistent reporting of transactions across all sources?  I just found this note in Wiki while writing this post:

Quicken is a personal finance management tool developed by Intuit, Inc. On March 3, 2016, Intuit announced plans to sell Quicken to H.I.G. Capital. Terms of the sale were not disclosed.[1]

For quite some time companies have attempted to tread in this space with mixed results, either through acquisition or build out of their existing platforms.  There seems to be significant opportunities within the services, software and infrastructure areas.  It will be interesting to see how it all plays out.

Inhibitors to enclosing a transaction within an end to end Transaction Management Solutions (TMS):

  • Higher level of risk (e.g. business, regulatory) expanding out service offerings
  • Stretching too thin, beyond core vision, and lose sight of vision.
  • Transforming tech  company to hybrid financial services
  • Automation, streamlining of processes, may derive efficiencies may lead to reduction in staff / workforce
  • Multiple platforms performing functions provides redundant capabilities, reduced risk, and more consumer choices

 Those inhibitors haven’t stopped these firms:

Payments Ecosystem
Payments Ecosystem

 

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