www.fdtechnologies.com
FY24 interim results
Safe Harbour Statement
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Delivering on strategy
Strategic progress in KX and expect to deliver 35% ARR growth this year
Investing to accelerate growth on strong foundations
First Derivative resilient in slower market
MRP improving through first half
Evaluating Group structure to optimise value
3
In H1 we have delivered important milestones in KX
- KX product available on Azure, AWS, GCP and Snowflake
- First deals closed on Azure
- Launched KDB.AI developer edition as a SAAS product
- Delivering KDB.AI integration with Microsoft Copilot and AWS Bedrock and global system integrator partnerships
- Completed the build out of the leadership team
4
Foundations to accelerate growth have been built…..
- Completed the transition from selling custom solutions to selling scalable product on cloud or on premise
-
Ease of procurement with use of CSP commits and ease of deployment with Python &
SQL - Growth rates from new product areas exceeding 60%
- Proven ability to expand existing customers and add new logos
ARR progression
Product (£m) Solutions (£m)
63%
68%
62.0
35% | 38.1 | |||||
22.7 | ||||||
16.8 | ||||||
20.7 | 18% | 24.4 | 11% | 27.2 | (3%) | 26.3 |
Actual FY21 | Actual FY22 | Actual FY23 | Target FY24 |
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Demand with cloud partners driving pipeline to deliver 35% ARR growth
in FY24
General availability across our cloud service partners (CSPs) has driven our pipeline growth and conversion rates
- 4x increase in CSP pipeline since the start of Q2
- Q4 CSP pipeline now as large as our direct pipeline
£m
35
30
25
20
15
10
5
0
Q1 23 | Q2 23 | Q3 23 | Q4 23 | Q1 24 | Q2 24 | Q3 24 | Q4 24 |
Direct pipeline (£m) | CSP pipeline (£m) | Conversion rate (%) | |||||
60%
50%
40%
30%
20%
10%
0%
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Demonstrated success of upsell to existing customers and winning new clients in financial services
Strong relationships with long-standing customers | Ability to land and expand with new logos | |
Customer since 2001 | Customer since 2022 |
• | Expansion sale of | |
kdb+ and kdb | ||
Insights, expanding | ||
ARR | to new teams and | |
divisions | ||
Expansion sale of | • | Upsell KDB.AI, kdb |
kdb Insights to | ||
Insights Enterprise | ||
Fixed Income | ||
team |
KDB.AI
kdb Insights
Enterprise
ARR
-
Additional usage on kdb Insights and
KDB.AI - Upsell kdb Insights Enterprise
kdb Insights
Enterprise
Longstanding kdb+ | |
core customer for | £0.9m |
equities team, | |
upsold them to kdb | kdb |
Insights | Insights |
kdb | ||
£0.4m | Insights | |
kdb | ||
Insights | kdb+ | |
kdb+ | ||
kdb+ | ||
FY21 | Current | Future |
New logo in FY22; | £2.4m | KDB.AI | ||||
system size grown | ||||||
from 0.5Gb RAM to | ||||||
+10TB RAM in less | KDB.AI | |||||
than 2 years | ||||||
£0.3m | kdb | |||||
kdb | ||||||
Insights | ||||||
kdb | Insights | |||||
Insights | ||||||
FY22 | Current | Future |
Use case: research, trading, forecasting, and trading analytics
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And also expand significantly within customers across other industries
For example: Healthcare.. | ..and Defence | |
Customer since 2021 | Customer since 2021 |
• | Expanding Insights | • Kdb+ new use cases | kdb Insights | |||
and new | ||||||
Enterprise to | Enterprise | |||||
ARR | ARR | departments | ||||
external users | ||||||
Upsell KDB.AI, kdb | ||||||
• | Upsell KDB.AI | • | KDB.AI | |||
KDB.AI | Insights / Insights | |||||
Enterprise | ||||||
kdb | ||||||
Upsold to kdb | £3.2m | |||||
Insights | ||||||
Insights and kdb | Follow on deals for | |||||
Insights | kdb Insights | |||||
kdb Insights | new use cases | |||||
Enterprise | ||||||
Enterprise | ||||||
Enterprise | ||||||
£2.3m | ||||||
Licensing for on | ||||||
kdb | kdb | premise software | ||||
kdb+ and KX | kdb+ | |||||
Insights | Insights | platform | ||||
£0.1m | £0.3m | kdb+ | ||||
kdb+ | kdb+ | kdb+ | kdb+ | |||
FY21 | Current | Future | FY22 | Current | Future |
Use case: data science for clinical trials efficiency
Use case: location intelligence, anomaly detection, data science
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Applicable across multiple use cases in Financial Services
and other industries
Horizontal use cases
Real-Time
Analytics
Anomaly
Detection/
Similarity
Search
Data Science
Real time processing Event detection Predictive analytics Visualisation
Pattern detection Pattern matching Recommendation
Data exploration Historical analysis Reporting Visualisations
.....in Financial Services
- Trading analytics
- Trade execution monitoring
- Real time risk monitoring
- Real time visualisation and reporting
- Trading alerts and circuit breakers
- Signal detection
- Trade surveillance
- Risk management
- Quantitative research
- Strategy development
- Model development
- Back-testing
- Forecasting
.... applied in other verticals
Manufacturing | IOT | ||
• | location monitoring | ||
• | Yield monitoring | ||
• | Device health | ||
• | Fault detection | ||
E&U | |||
Telco | |||
• | Network flow | ||
• Self-Optimising Network | |||
• | Meter tracking | ||
Telco | IOT | ||
• | Network fault detection | • | Object identification |
Manufacturing | • | Alerting | |
• | Predictive maintenance | Health and Life Sciences | |
• | Fault detection | • | Patient identification |
Telco | Manufacturing | ||
• | Common failure analysis | ||
• | Network capacity | ||
• | Operational | ||
planning | |||
improvements | |||
IOT | |||
Health and Life Sciences | |||
• | Threat detection | ||
• | Drug discovery | ||
KDB.AI enhances
outcomes, combining
structured and
unstructured data for better decision making and increased
ROI
Cyber- security & Observability
Data ingestion, network monitoring, threat detection, anomaly detection, event play back, real-time visualisation, network optimisation
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KDB.AI combines real time and structured data with any LLM using only CPU capacity to expand existing value and enable new use cases
EXPANDING EXISTING USE CASES
Generating alpha expanded to rapid trading strategy creation: enhancing research with generative AI to create
novel trading strategies from new data sources (media, analyst reports and filings)
Algo trading expanded to algo parameter exploration:
Natural language interface to adjust algo parameters
Trade surveillance expanded to generative event detection: Augmentation of trade patterns data with voice and text communications, enhancing rules and alert engines
Predictive maintenance expanded to fault explain-ability:Auto categorisation of new "events" self-learningrules engines and natural language exploration of faults
Data science expanded to multi-dimensional data exploration: perform similarity analysis using time windows to see 'point in time' or 'progression over time' (images, numerical, text)
ENABLING NEW USE CASES
Contracts knowledge-base exploration: Interactive co-pilotfor exploration of contracts; understand changes of in-forcerules over time
Interactive client services: Combine customer service interaction information with temporal interaction data from CRM systems, transcribed conversations and other sources
Similarity search and product recommendations: Hybrid
search of product language databases along with numeric and predictive signals of interest
Code development: search, diagnose and make recommendations from proprietary code knowledge base (and changes over time)
Prompting for demand forecasting: Augment demand forecasting with natural language (web, news, social) and unstructured data (video, images, audio) to maximize insights and context
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FD Technologies plc published this content on 24 October 2023 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 24 October 2023 05:40:36 UTC.