1. Bespoke Analytics
Leveraging Advanced Analytics for growth and sustainability in the Financial Services Sector.

2. The Problem 1
The Financial Services Sector has often been slow to accept and suspicious of technological advancements.
Many have accepted this growing influence of technology grudgingly.
However, Financial Service providers have increasingly collected more and more data in an attempt to improve their operations, i.e. improving products, marketing, risk and fraud management.

3. The Problem 2
Though commendable, many financial service providers have left out a key component when dealing with data, namely the data analytics technologies needed to draw insight from this growing set of data.
At a basic level the equation they follow is:
Greater Data = Better Insights
This [un]equation also highlights the main problem many financial service providers have with their data.

4. The pond separating data from Intelligence
Firms often invest more resources in collecting a greater quantum of data without giving adequate thought to the need of improved tools to draw insights from this data.
The situation is exacerbated as new data structures are introduced and being recorded by firms in the financial sector.
The lack of the necessary infrastructure means that financial services often view these large data sets as cumbersome and problematic, thus completely ignoring this data.
Those who want to glean insight from the data are hindered by the lack of the technical, analytic and programing skills to effectively clean, restructure, analyze, and generate intelligence.

5. Advanced Analytics: The Role and Responsibilities of Firms.
Financial Service firms must realize the changing responsibilities that they have towards their data.
There is a need to create a data environment that makes data more valuable, rather than a valueless behemoth.
Advanced Analytics can feed into improved methods of credit-rating and risk management, to name only a few.
However, before any new value can be derived, financial firms must commit to improving their data analytics capacity – this must be their target.

6. The Analytics Value-Chain
Yoana™
Insights
Intelligence
Opportunity
Growth & Sustainability
Data
The Analytics Value-Chain

7. kdalgo – Our firm; our capabilities.
kdalgo provides invaluable data analytics solutions for the increasing and varied data challenges plaguing business decision-makers today. We wrestle big data and give clients simple, actionable insights tailored specifically to fit - we never compromise.
kdalgo identifies hidden insights and gain intelligence using
Data Analytics
Machine Learning Algorithms
Predictive Analytics
Custom Algorithm for unstructured data

8. The Changing face of Risk in the Financial Services Sector
The Financial Service sector in recent times has been plagued with damaging, high-profile fraud cases.
The inability of firms to detect and protect themselves against these highlights the need to refine the processes and technologies employed to detect the occurrences of potential adverse effects.
Advanced Analytics is an high-impact tool in the arsenal of any firm that can effectively deploy it within its business functions.
The Changing face of Risk in the Financial Services Sector

9. Advanced Analytics: A Clearer Picture
Leveraging Python and R powerful data integration and imputations tools, kdalgo will effectively enhance the picture of data by correcting for missingness, clean and restructure messy data to make it amenable to statistical and analytical processes and algorithms.
Messy Data caused by the presence of complex or uncommon data types and structures is endemic in large datasets, often compounds the stress of firms and IT professionals and thereby hampers their ability to leverage the data for improved insights.
Missing Data is a problem that hamstrings the ability of firms to draw insights from their data.

10. Understanding the Customer better than ever
In the financial services, different products are offered to different customer segments, it is important to understand the customer.
Analytics offers a 360-view of the customer.
Employing methods such as multiple discriminant analysis will highlight product preferences.
Incorporating data analytics will boost the accuracy and comprehensiveness of information on customer segments.
By incorporating big data analytics tools, customer will be better served, providing improved customer experiences, improving retention, reducing churn, and driving growth.

11. Clustering & Classification
Statistical Learning tools including multivariate cluster analytic algorithms helps in categorizing all facets of business, such as :
Investment instruments
Clients
Customers
Infusing analytics into the your processes, will increased understanding and drivability– leading to better performance and risks control.

12. Product Design and Development
Leveraging sentiment-analysis, perceptual mapping, multidimensional preference mapping to enhance market segmentation, product development and positioning.
By tapping into unstructured data such as social media and blog posts, financial service providers will unearth a new stream of insights to enhance their marketing and communications tools.
Using logit Choice modeling, can give insight into behavior choices, which in turn inform us about our branding and optimal new product(s) or brands to pursue.
Product Design and Development

13. Impact Impact on Financial Services Big Data Analytics Systems
- Ability to handle both structured and unstructured data.
- Designed to handle large data sets from a number of sources across multiple sources and platforms.
-Technology to facilitate parallel processing for faster development and deployment
- Able to respond in real-time or near real-time.
- Strong predictability of Risk and Fraud
Impact on Financial Services
-Improved decision support. 
-Respond quickly to changing business trends and capitalize on opportunities. 
-Ability to make real-time decisions.
-Provider gains a competitive advantage through increased customer insights. 
-Have the Competitive Intelligence to create innovative products to drive profitability. 
-Detect and Prevent adverse risk and fraud that may impact the sustenance and profitability of business.
Impact

14. kdalgo – How we work We are client-oriented We are Adaptive
We work with the client to highlight and fully define the problem areas and challenges they face.
We are Adaptive
At kdalgo we understand that your data needs change, so we make sure that our solutions adapt to meet ever changing business expectations
We value simplicity
kdalgo understands that business is fast, and decision makers need to be able to make decisions - fast. We provide simple, clear, and actionable information for swift decisions.
We are problem driven.
Your ‘headache’ drives us !!! We develop tools to solve your specific problems and provide competitive Intelligence and advantage- customized solutions!!!.
kdalgo – How we work

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